Rezilion raises $30M help security operations teams with tools to automate their busywork

Security operations teams face a daunting task these days, fending off malicious hackers and their increasingly sophisticated approaches to cracking into networks. That also represents a gap in the market: building tools to help those security teams do their jobs. Today, an Israeli startup called Rezilion that is doing just that — building automation tools for DevSecOps, the area of IT that addresses the needs of security teams and the technical work that they need to do in their jobs — is announcing $30 million in funding.

Guggenheim Investments is leading the round with JVP and Kindred Capital also contributing. Rezilion said that unnamed executives from Google, Microsoft, CrowdStrike, IBM, Cisco, PayPal, JP Morgan Chase, Nasdaq, eBay, Symantec, RedHat, RSA and Tenable are also in the round. Previously, the company had raised $8 million.

Rezilion’s funding is coming on the back of strong initial growth for the startup in its first two years of operations.

Its customer base is made up of some of the world’s biggest companies, including two of the “Fortune 10” (the top 10 of the Fortune 500). CEO Liran Tancman, who co-founded Rezilion with CTO Shlomi Boutnaru, said that one of those two is one of the world’s biggest software companies, and the other is a major connected device vendor, but he declined to say which. (For the record, the top 10 includes Amazon, Apple, Alphabet/Google, Walmart and CVS.)

Tancman and Boutnaru had previously co-founded another security startup, CyActive, which was acquired by PayPal in 2015; the pair worked there together until leaving to start Rezilion.

There are a lot of tools out in the market now to help automate different aspects of developer and security operations. Rezilion focuses on a specific part of DevSecOps: large businesses have over the years put in place a lot of processes that they need to follow to try to triage and make the most thorough efforts possible to detect security threats. Today, that might involve inspecting every single suspicious piece of activity to determine what the implications might be.

The problem is that with the volume of information coming in, taking the time to inspect and understand each piece of suspicious activity can put enormous strain on an organization: it’s time-consuming, and as it turns out, not the best use of that time because of the signal to noise ratio involved. Typically, each vulnerability can take 6-9 hours to properly investigate, Tancman said. “But usually about 70-80% of them are not exploitable,” meaning they may be bad for some, but not for this particular organization and the code it’s using today. That represents a very inefficient use of the security team’s time and energy.

“Eight of out ten patches tend to be a waste of time,” Tancman said of the approach that is typically made today. He believes that as its AI continues to grow and its knowledge and solution becomes more sophisticated, “it might soon be 9 out of 10.”

Rezilion has built a taxonomy and an AI-based system that essentially does that inspection work as a human would do: it spots any new, or suspicious, code, figures out what it is trying to do, and runs it against a company’s existing code and systems to see how and if it might actually be a threat to it or create further problems down the line. If it’s all good, it essentially whitelists the code. If not, it flags it to the team.

The stickiness of the product has come out of how Tancman and Boutnaru understand large enterprises, especially those heavy with technology stacks, operate these days in what has become a very challenging environment for cybersecurity teams.

“They are using us to accelerate their delivery processes while staying safe,” Tancman said. “They have strict compliance departments and have to adhere to certain standards,” in terms of the protocols they take around security work, he added. “They want to leverage DevOps to release that.”

He said Rezilion has generally won over customers in large part for simply understanding that culture and process and helping them work better within that: “Companies become users of our product because we showed them that, at a fraction of the effort, they can be more secure.” This has special resonance in the world of tech, although financial services, and other verticals that essentially leverage technology as a significant foundation for how they operate, are also among the startup’s user base.

Down the line, Rezilion plans to add remediation and mitigation into the mix to further extend what it can do with its automation tools, which is part of where the funding will be going, too, Boutnaru said. But he doesn’t believe it will ever replace the human in the equation altogether.

“It will just focus them on the places where you need more human thinking,” he said. “We’re just removing the need for tedious work.”

In that grand tradition of enterprise automation, then, it will be interesting to watch which other automation-centric platforms might make a move into security alongside the other automation they are building. For now, Rezilion is forging out an interesting enough area for itself to get investors interested.

“Rezilion’s product suite is a game changer for security teams,” said Rusty Parks, senior MD of Guggenheim Investments, in a statement. “It creates a win-win, allowing companies to speed innovative products and features to market while enhancing their security posture. We believe Rezilion has created a truly compelling value proposition for security teams, one that greatly increases return on time while thoroughly protecting one’s core infrastructure.”

#agile-software-development, #alphabet, #amazon, #apple, #articles, #artificial-intelligence, #automation, #ceo, #cisco, #computer-security, #crowdstrike, #cto, #cyactive, #devops, #ebay, #energy, #entrepreneurship, #europe, #financial-services, #funding, #google, #ibm, #jp-morgan-chase, #kindred-capital, #maryland, #microsoft, #paypal, #security, #software, #software-development, #startup-company, #symantec, #technology

Fin names former Twilio exec Evan Cummack as CEO, raises $20M

Work insights platform Fin raised $20 million in Series A funding and brought in Evan Cummack, a former Twilio executive, as its new chief executive officer.

The San Francisco-based company captures employee workflow data from across applications and turns it into productivity insights to improve the way enterprise teams work and remain engaged.

Fin was founded in 2015 by Andrew Kortina, co-founder of Venmo, and Facebook’s former VP of product and Slow Ventures partner Sam Lessin. Initially, the company was doing voice assistant technology — think Alexa but powered by humans and machine learning — and then workplace analytics software. You can read more about Fin’s origins at the link below.

In 2020, the company pivoted again to the company it is today. The new round was led by Coatue, with participation from First Round Capital, Accel and Kleiner Perkins. The original team was talented, but small, so the new funding will build out sales, marketing and engineering teams, Cummack said.

“At that point, the right thing was to raise money, so at the end of last year, the company raised a $20 million Series A, and it was also decided to find a leadership team that knows how to build an enterprise,” Cummack told TechCrunch. “The company had completely pivoted and removed ‘Analytics’ from our name because it was not encompassing what we do.”

Fin’s software measures productivity and provides insights on ways managers can optimize processes, coach their employees and see how teams are actually using technology to get their work done. At the same time, employees are able to manage their workflow and highlight areas where there may be bottlenecks. All combined, it leads to better operations and customer experiences, Cummack said.

Graphic showing how work is really done. Image Credits: Fin

Fin’s view is that as more automation occurs, the company is looking at a “renaissance of human work.” There will be more jobs and more types of jobs, but people will be able to do them more effectively and the work will be more fulfilling, he added.

Particularly with the use of technology, he notes that in the era before cloud computing, there was a small number of software vendors. Now with the average tech company using over 130 SaaS apps, it allows for a lot of entrepreneurs and adoption of best-in-breed apps so that a viable company can start with a handful of people and leverage those apps to gain big customers.

“It’s different for enterprise customers, though, to understand that investment and what they are spending their money on as they use tools to get their jobs done,” Cummack added. “There is massive pressure to improve the customer experience and move quickly. Now with many people working from home, Fin enables you to look at all 130 apps as if they are one and how they are being used.”

As a result, Fin’s customers are seeing metrics like 16% increase in team utilization and engagement, a 25% decrease in support ticket handle time and a 71% increase in policy compliance. Meanwhile, the company itself is doubling and tripling its customers and revenue each year.

Now with leadership and people in place, Cummack said the company is positioned to scale, though it already had a huge head start in terms of a meaningful business.

Arielle Zuckerberg, partner at Coatue, said via email that she was part of a previous firm that invested in Fin’s seed round to build a virtual assistant. She was also a customer of Fin Assistant until it was discontinued.

When she heard the company was pivoting to enterprise, she “was excited because I thought it was a natural outgrowth of the previous business, had a lot of potential and I was already familiar with management and thought highly of them.”

She believed the “brains” of the company always revolved around understanding and measuring what assistants were doing to complete a task as a way to create opportunities for improvement or automation. The pivot to agent-facing tools made sense to Zuckerberg, but it wasn’t until the global pandemic that it clicked.

“Service teams were forced to go remote overnight, and companies had little to no visibility into what people were doing working from home,” she added. “In this remote environment, we thought that Fin’s product was incredibly well-suited to address the challenges of managing a growing remote support team, and that over time, their unique data set of how people use various apps and tools to complete tasks can help business leaders improve the future of work for their team members. We believe that contact center agents going remote was inevitable even before COVID, but COVID was a huge accelerant and created a compelling ‘why now’ moment for Fin’s solution.”

Going forward, Coatue sees Fin as “a process mining company that is focused on service teams.” By initially focusing on customer support and contact center use case — a business large enough to support a scaled, standalone business — rather than joining competitors in going after Fortune 500 companies where implementation cycles are long and there is slow time-to-value, Zuckerberg said Fin is better able to “address the unique challenges of managing a growing remote support team with a near-immediate time-to-value.”

 

#accel, #andrew-kortina, #arielle-zuckerberg, #artificial-intelligence, #automation, #business-intelligence, #business-process-management, #cloud, #cloud-computing, #coatue, #enterprise, #fin, #first-round-capital, #funding, #groupware, #kleiner-perkins, #machine-learning, #process-mining, #recent-funding, #saas, #sam-lessin, #slow-ventures, #startups, #talent, #tc, #twilio, #workflow

Peak raises $75M for a platform that helps non-tech companies build AI applications

As artificial intelligence continues to weave its way into more enterprise applications, a startup that has built a platform to help businesses, especially non-tech organizations, build more customized AI decision making tools for themselves has picked up some significant growth funding. Peak AI, a startup out of Manchester, England, that has built a “decision intelligence” platform, has raised $75 million, money that it will be using to continue building out its platform as well as to expand into new markets, and hire some 200 new people in the coming quarters.

The Series C is bringing a very big name investor on board. It is being led by SoftBank Vision Fund 2, with previous backers Oxx, MMC Ventures, Praetura Ventures, and Arete also participating. That group participated in Peak’s Series B of $21 million, which only closed in February of this year. The company has now raised $118 million; it is not disclosing its valuation.

(This latest funding round was rumored last week, although it was not confirmed at the time and the total amount was not accurate.)

Richard Potter, Peak’s CEO, said the rapid follow-on in funding was based on inbound interest, in part because of how the company has been doing.

Peak’s so-called Decision Intelligence platform is used by retailers, brands, manufacturers and others to help monitor stock levels, build personalized customer experiences, as well as other processes that can stand to have some degree of automation to work more efficiently, but also require sophistication to be able to measure different factors against each other to provide more intelligent insights. Its current customer list includes the likes of Nike, Pepsico, KFC, Molson Coors, Marshalls, Asos, and Speedy, and in the last 12 months revenues have more than doubled.

The opportunity that Peak is addressing goes a little like this: AI has become a cornerstone of many of the most advanced IT applications and business processes of our time, but if you are an organization — and specifically one not built around technology — your access to AI and how you might use it will come by way of applications built by others, not necessarily tailored to you, and the costs of building more tailored solutions can often be prohibitively high. Peak claims that those using its tools have seen revenues on average rise 5%; return on ad spend double; supply chain costs reduce by 5%; and inventory holdings (a big cost for companies) reduce by 12%.

Peak’s platform, I should point out, is not exactly a “no-code” approach to solving that problem — not yet at least: it’s aimed at data scientists and engineers at those organizations so that they can easily identify different processes in their operations where they might benefit from AI tools, and to build those out with relatively little heavy lifting.

There have also been different market factors that have also played a role. Covid-19, for example, and the boost that we have seen both in increasing “digital transformation” in businesses, and making e-commerce processes more efficient to cater to rising consumer demand and more strained supply chains, have all led to businesses being more open to and keen to invest in more tools to improve their automation intelligently.

This, combined with Peak AI’s growing revenues, is part of what interested SoftBank. The investor has been long on AI for a while, but it has been building out a section of its investment portfolio to provide strategic services to the kinds of businesses that it invests in. Those include e-commerce and other consumer-facing businesses, which make up one of the main segments of Peak’s customer base.

“In Peak we have a partner with a shared vision that the future enterprise will run on a centralized AI software platform capable of optimizing entire value chains,” Max Ohrstrand, senior investor for SoftBank Investment Advisers, said in a statement. “To realize this a new breed of platform is needed and we’re hugely impressed with what Richard and the excellent team have built at Peak. We’re delighted to be supporting them on their way to becoming the category-defining, global leader in Decision Intelligence.”

Longer term, it will be interesting to see how and if Peak evolves to be extend its platform to a wider set of users at the organizations that are already its customers.

Potter said he believes that “those with technical predispositions” will be the most likely users of its products in the near and medium term. You might assume that would cut out, for example, marketing managers, although the general trend in a lot of software tools has precisely been to build versions of the same tools used by data scientists for these tell technical people to engage in the process of building what it is that they want to use. “I do think it’s important to democratize the ability to stream data pipelines, and to be able to optimize those to work in applications,” he added.

#ai, #articles, #artificial-intelligence, #automation, #business-process-management, #ceo, #e-commerce, #enterprise, #europe, #funding, #kfc, #manchester, #mmc-ventures, #nike, #partner, #peak, #peak-ai, #pepsico, #science-and-technology, #series-b, #softbank-group, #softbank-vision-fund, #software-platform, #tc, #united-kingdom, #vodafone

Sora’s HR automation software raises $14M Series A

HR automation software startup Sora announced this morning that it closed a $14 million Series A round of funding. Two Sigma Ventures led the financing event, putting in $10 million, with prior investors completing the round.

The round comes after Sora raised a $5.3 million seed round in July 2020. First Round and Elad Gil led that investment.

TechCrunch caught up with Sora CEO Laura Del Beccaro to chat about the round. We were curious about why this was the right moment for the company to raise more capital — the startup noted last year that it had around 2.5 years of runway — and what it intends to do with the money.

Regarding the first question, Del Beccaro said that her company raised its seed round to validate its market after finding early traction with its product. The CEO added that her company found better problem validation — product-market fit, essentially — than it had anticipated in the following quarters, and that after a year of scaling “thoughtfully” is now ready to accelerate its growth in both financial and human terms.

Sora reached an inflection point, she said, sometime in the first half of 2020. The early COVID days, in other words. The pandemic was tough on HR teams, Del Beccaro explained: With employees going remote, and a shift to hiring over Zoom, you can imagine why HR teams were having a time and a half during the rapid shakeups of the labor market.

The startup’s growth accelerated toward the end of 2020, the CEO said, leading to 7x customer growth and 8x revenue growth since its seed round.

To better understand why Sora found strong traction during COVID, let’s remind ourselves what the startup’s software actually does. It helps HR operations teams collect and sync data from various systems, create standardized processes for particular tasks, and aids collaboration among the larger people or HR team at a company. To do that, Sora can trigger automated emails from HR, centralize HR ops tasks, and shuttle data to and from disparate software tools used by a larger human resources team.

The result, per Del Beccaro, is a reduction in busywork and rote tasks for HR operations teams, saving time and reducing the chance that a particular task falls through the cracks; because HR operations teams often oversee onboarding, for example, not making mistakes is pretty key.

TechCrunch was curious if Sora might eventually become a hub for employees to interact with HR systems more broadly; if the startup is already doing the work to connect deeply to HR software, why not save employees time by providing them with a single portal? Del Beccaro said that her company was becoming a source of truth for the HR world, but that an explosion of HR tooling in recent years has left some companies leery of adding another employee-facing tool to their collection.

Ask anyone who works for a major company what their Okta or similar dashboard looks like for an explanation of what she means, if it’s not clear.

Sora said that its target customer base is companies with around 100 employees and up, though some smaller customers that see more rapid onboarding and offboarding also make good Sora targets. The startup charges per employee managed, with no limit on processes because Sora wants HR teams to build as many workflows inside of its service as they want. The more integrated a company’s HR operations become in Sora, we reckon, the less likely it is to churn, so the pricing model makes sense.

Off a good year of growth, Sora has 11 employees today, essentially the same size that it was when it raised its seed round. Given its growth since that point, the startup has demonstrated notable operating leverage for a company of its size. Flush with new funds, Sora intends to double its staff in the next year.

Why did Sora pick Two Sigma to lead its round? Per the CEO, it is a newer firm, which means that her startup won’t be competing with dozens of other portfolio companies. But more importantly, Del Beccaro spoke highly of the partner at the firm who led the Series A, Frances Schwiep, telling TechCrunch that she immediately understood what Sora wanted to do.

TechCrunch spoke briefly with Schwiep about her investment. The venture capitalist said that she had been looking at the HR tech world for some time. And having seen at her prior gig how much work in the robotic process automation space went into employee onboarding and offboarding, Sora fit where she saw HR tech heading. She also cited a few macro trends that are favorable for the startup, including declining average employee tenure — the more headcount turnover, the more HR work there is to either do by hand or automate — and a move to more remote work.

When we last checked in with Sora, we noted the no-code elements of its service, designed to let HR operations teams set workflows that they might want to automate. This time around, such a setup felt more like table stakes than something to call out in particular. Technology moves quickly.

The next time we talk to Sora, we’ll expect harder revenue figures given that it is no longer a seed-stage startup. For now, let’s see how far it can get with $14 million.

#automation, #fundings-exits, #hr, #human-resource-management, #human-resources, #laura-del-beccaro, #no-code, #onboarding, #sora, #startups, #two-sigma-ventures

Japan’s B2B ordering and supply platform CADDi raises $73 million Series B funding

With COVID-19 disrupting the entire manufacturing supply chain including semiconductor shortages, companies across multiple industries have been struggling to seek a procurement solution that can rebalance the gap between supply and demand.

CADDi, a Tokyo-based B2B ordering and supply platform in the manufacturing and procurement industry, helps both procurement (demand side) and manufacturing facilities (supply side) by aggregating and rebalancing supply and demand via its automated calculation system for manufacturing costs and databases of fabrication facilities across Japan.

The company announced this morning a $73 million Series B round co-led by Globis Capital Partners and World Innovation Lab (WiL), with participation from existing investors DCM and Global Brain. Six new investors also have joined the round including Arena Holdings, DST Global, Minerva Growth Partners, Tybourne Capital Management, JAFCO Group and SBI Investment.

CADDi was founded by CEO Yushiro Kato and CTO Aki Kobashi in November 2017.

The post-money valuation is estimated at $450 million, according to sources close to the deal.

The new funding brings CADDi’s total raised so far to $90.5 million. In December 2018, the company closed a $9 million Series A round led by DCM and followed by Globis Capital Partners and WiL and Global Brain.

The funding proceeds will be used for accelerating digital transformation of the platform, hiring and expanding to global markets.

“We enable integrated production of complete sets of equipment consisting of custom-made parts such as sheet metal, machined parts and structural frames. Using an automatic quotation system based on a proprietary cost calculation algorithm, we select the processing company that best matches the quality, delivery date and price of the order and build an optimal supply chain,” CEO and co-founder Yushiro Kato said.

The goal of CADDi’s ordering platform is to transform the manufacturing industry from a multiple subcontractor pyramid structure to a flat, connected structure based on each manufacturers’ individual strengths, thus creating a world where those on the front lines of manufacturing can spend more time on essential and creative work, Kato said.

CADDi’s ordering platform, backed by its unique technology including automatic cost calculation system, optimal ordering and production management system, and drawing management system, offers a 10%-15% cost reduction, stable capacity and balanced order placement to its more than 600 Japanese supply partners spanning a multitude of industries.

“The demand for CADDi’s services has seen significant acceleration. Our business has been growing very fast, and our latest orders have grown more than six times compared to the previous year, leading to the company’s expanded presence into both eastern and western Japan in order to meet this increase in demand,” Kato said.

“Going forward, in addition to continuously expanding our ordering platform, we will also start to provide purchases (manufacturers) and supply partners with our technology directly to promote digital transformation of their operations, for example, the production management system and drawing management system,” Kato continued.

“As a start point, in the near future, we are thinking about selling ‘Drawing Management SaaS,’” which has been used internally for CADDi’s ordering operation, to help customers solve operational pains in handling piles of drawings. “Our ‘Drawing Management SaaS’ technology will not only help manage drawings as documents properly but also allow utilization of data of drawings in a practical way for future decision-making and action in their procurement process.”

CADDi’s next axis of growth will be other growing markets, especially in Southeast Asia, Kato pointed out. “Many of our Japanese customers have subsidiaries and branches in these countries, so it’s a natural expansion opportunity for us to strengthen our value proposition and provide more continuity and seamless service to our customers,” Kato added.

Kato also said it wants to continue investing in hiring, especially engineers, to further the development of its platform CADDi and new business. It plans to hire 1,000 employees in the next three years. CADDi had 102 employees as of March 2021.

The company aims to become a global platform with sales of USD 9.1 billion (that is 1 trillion YEN) by 2030, Kato said.

COVID-19 had a different impact on different industries in the procurement and manufacturing sector, with “the automobile and machine tool industries were negatively affected by the pandemic and experienced an up to 90% temporary drop in sales, while other industries such as the medical and semiconductor industries have experienced explosive growth in demand. The overall result of COVID-19 is that the company has captured more demand because CADDi’s system rebalances receipts across multiple industries,” according to Kato.

Masaya Kubota, partner at World Innovation Lab, told TechCrunch, “CADDi’s solution of aggregating and rebalancing supply and demand has once again proven to be indispensable to both purchasers and manufacturers, with the pandemic disrupting the entire supply chain in manufacturing. We first invested in CADDi in 2018, because we strongly believed in their mission of digitally transforming one of the most analog industries, the $1 trillion procurement market.”

Another investor principal at DCM, Kenichiro Hara, also said in an email interview with TechCrunch, “The pandemic made the manufacturing industry’s supply chain vulnerabilities quite clear early on. For example, if a country is on lockdown or a factory stalls the operations, their customers cannot procure necessary parts to produce their products. This impact amplifies, and the entire supply chain is affected. Therefore, the demand for finding new, available and accessible suppliers in a timely manner increased in importance, which is CADDi’s primary value-add.”

#asia, #automation, #b2b, #caddi, #funding, #japan, #manufacturing, #recent-funding, #saas, #southeast-asia, #startups, #tc

Tesla Bot is the company’s troubled Autopilot system in humanoid form

Not sure how those joints will work...

Enlarge / Not sure how those joints will work… (credit: Tesla)

Not content to be an automaker or even an energy company, Tesla now wants people to think of it as a robotics company.

At Tesla’s “AI Day” presentation yesterday, CEO Elon Musk made the surprise announcement that the company is working on a humanoid robot. The endeavor, he argued, makes sense given the company’s experience working toward self-driving vehicles.

“Tesla is arguably the world’s biggest robotics company because our cars are semi-sentient robots on wheels,” Musk said. “We think we’ll probably have a prototype sometime next year.”

Read 11 remaining paragraphs | Comments

#automation, #cars, #robotics, #robots, #tech, #tesla

UIPath CEO Daniel Dines is coming to TC Sessions: SaaS to talk RPA and automation

UIPath came seemingly out of nowhere in the last several years, going public last year in a successful IPO during which it raised over $527 million. It raised $2 billion in private money prior to that with its final private valuation coming in at an amazing $35 billion. UIPath CEO Daniel Dines will be joining us on a panel on automation at TC Sessions: Saas on October 27th.

The company has been able capture all this investor attention doing something called Robotic Process Automation, which provides a way to automate a series of highly mundane tasks. It has become quite popular, especially to help bring a level of automation to legacy systems that might not be able to handle more modern approaches to automation involving artificial intelligence and machine learning. In 2019 Gartner found that RPA was the fastest growing category in enterprise software.

In point of fact,  UIPath didn’t actually come out of nowhere. It was founded in 2005 as a consulting company and transitioned to software over the years. The company took its first VC funding, a modest $1.5 million seed round in 2015, according to Crunchbase data.

As RPA found its market, the startup began to take off, raising gobs of money including a $568 million round in April 2019 and $750 million in its final private raise in February 2021.

Dines will be appearing on a panel discussing the role of automation in the enterprise. Certainly, the pandemic drove home the need for increased automation as masses of office workers moved to work from home, a trend that is likely to continue even after the pandemic slows.

As the RPA market leader, he is uniquely positioned to discuss how this software and other similar types will evolve in the coming years and how it could combine with related trends like no-code and process mapping. Dines will be joined on the panel by investor Laela Sturdy from Capital G and ServiceNow’s Dave Wright where they will discuss the state of the automation market, why it’s so hot and where the next opportunities could be.

In addition to our discussion with Dines, the conference will also include Databricks’ Ali Ghodsi, Salesforce’s Kathy Baxter and Puppet’s Abby Kearns, as well as investors Casey Aylward and Sarah Guo, among others. We hope you’ll join us. It’s going to be a stimulating day.

Buy your pass now to save up to $100. We can’t wait to see you in October!

Is your company interested in sponsoring or exhibiting at TC Sessions: SaaS 2021? Contact our sponsorship sales team by filling out this form.

#abby-kearns, #ali-ghodsi, #articles, #artificial-intelligence, #automation, #business-process-automation, #business-process-management, #business-software, #casey-aylward, #ceo, #daniel-dines, #databricks, #dave-wright, #enterprise, #kathy-baxter, #laela-sturdy, #machine-learning, #robotic-process-automation, #rpa, #salesforce, #sarah-guo, #servicenow, #software, #tc, #tc-sessions-saas-2021, #technology, #uipath

The Nuro EC-1

Six years ago, I sat in the Google self-driving project’s Firefly vehicle — which I described, at the time, as a “little gumdrop on wheels” — and let it ferry me around a closed course in Mountain View, California.

Little did I know that two of the people behind Firefly’s ability to see and perceive the world around it and react to that information would soon leave to start and steer an autonomous vehicle company of their very own.

Dave Ferguson and Jiajun Zhu aren’t the only Google self-driving project employees to launch an AV startup, but they might be the most underrated. Their company, Nuro, is valued at $5 billion and has high-profile partnerships with leaders in retail, logistics and food including FedEx, Domino’s and Walmart. And, they seem to have navigated the regulatory obstacle course with success — at least so far.

Yet, Nuro has remained largely in the shadows of other autonomous vehicle companies. Perhaps it’s because Nuro’s focus on autonomous delivery hasn’t captured the imagination of a general public that envisions themselves being whisked away in a robotaxi. Or it might be that they’re quieter.

Those quiet days might be coming to an end soon.

This series aims to look under Nuro’s hood, so to speak, from its earliest days as a startup to where it might be headed next — and with whom.

The lead writer of this EC-1 is Mark Harris, a freelance reporter known for investigative and long-form articles on science and technology. Our resident scoop machine, Harris is based in Seattle and also writes for Wired, The Guardian, The Economist, MIT Technology Review and Scientific American. He has broken stories about self-driving vehicles, giant airships, AI body scanners, faulty defibrillators and monkey-powered robots. In 2014, he was a Knight Science Journalism Fellow at MIT, and in 2015 he won the AAAS Kavli Science Journalism Gold Award.

The lead editor of this EC-1 was Kirsten Korosec, transportation editor at TechCrunch (that’s me), who has been writing about autonomous vehicles and the people behind them since 2014; OK maybe earlier. The assistant editor for this series was Ram Iyer, the copy editor was Richard Dal Porto, and illustrations were drawn by Nigel Sussman. The EC-1 series editor is Danny Crichton.

Nuro had no say in the content of this analysis and did not get advance access to it. Harris nor Korosec have any financial ties to Nuro.

The Nuro EC-1 comprises four articles numbering 10,600 words and a reading time of 43 minutes. Here are the topics we’ll be dialing into:

We’re always iterating on the EC-1 format. If you have questions, comments or ideas, please send an email to TechCrunch Managing Editor Danny Crichton at danny@techcrunch.com.

#automation, #automotive, #california, #cvs, #dave-ferguson, #dominos-pizza, #dominos, #ec-mobility-hardware, #ec-1, #electric-vehicles, #emerging-technologies, #extra-crunch-ec-1, #fedex, #google, #kroger, #mit, #nuro, #nuro-ec-1, #robotaxi, #robotics, #science-and-technology, #seattle, #self-driving-cars, #tc, #technology, #transportation, #walmart

How Google’s self-driving car project accidentally spawned its robotic delivery rival

Nuro doesn’t have a typical Silicon Valley origin story. It didn’t emerge after a long, slow slog from a suburban garage or through a flash of insight in a university laboratory. Nor was it founded at the behest of an eccentric billionaire with money to burn.

Nuro was born — and ramped up quickly — thanks to a cash windfall from what is now one of its biggest rivals.

Nuro was born — and ramped up quickly — thanks to a cash windfall from what is now one of its biggest rivals.

In the spring of 2016, Dave Ferguson and Jiajun Zhu were teammates on Google’s self-driving car effort. Ferguson was directing the project’s computer vision, machine learning and behavior prediction teams, while Zhu (widely JZ) was in charge of the car’s perception technologies and cutting-edge simulators.

“We both were leading pretty large teams and were responsible for a pretty large portion of the Google car’s software system,” Zhu recalls.

As Google prepared to spin out its autonomous car tech into the company that would become Waymo, it first needed to settle a bonus program devised in the earliest days of its so-called Chauffeur project. Under the scheme, early team members could choose staggered payouts over a period of eight years — or leave Google and get a lump sum all at once.

Ferguson and Zhu would not confirm the amount they received, but court filings released as part of Waymo’s trade secrets case against Uber suggest they each received payouts in the neighborhood of $40 million by choosing to leave.

“What we were fortunate enough to receive as part of the self-driving car project enabled us to take riskier opportunities, to go and try to build something that had a significant chance of not working out at all,” Ferguson says.

Within weeks of their departure, the two had incorporated Nuro Inc, a company with the non-ironic mission to “better everyday life through robotics.” Its first product aimed to take a unique approach to self-driving cars: Road vehicles with all of the technical sophistication and software smarts of Google’s robotaxis, but none of the passengers.

In the five years since, Nuro’s home delivery robots have proven themselves smart, safe and nimble, outpacing Google’s vehicles to secure the first commercial deployment permit for autonomous vehicles in California, as well as groundbreaking concessions from the U.S. government.

While robotaxi companies struggle with technical hitches and regulatory red tape, Nuro has already made thousands of robotic pizza and grocery deliveries across the U.S., and Ferguson (as president) and Zhu (as CEO) are now heading a company that as of its last funding round in November 2020 valued it at $5 billion with more than 1,000 employees.

But how did they get there so fast, and where are they headed next?

Turning money into robots

“Neither JZ nor I think of ourselves as classic entrepreneurs or that starting a company is something we had to do in our lives,” Ferguson says. “It was much more the result of soul searching and trying to figure out what is the biggest possible impact that we could have.”

#artificial-intelligence, #automation, #autonomous-vehicles, #dave-ferguson, #dominos-pizza, #ec-1, #electric-vehicles, #extra-crunch-ec-1, #fidelity-management-research-company, #google, #greylock-capital, #machine-learning, #nuro, #nuro-ec-1, #robotics, #self-driving-cars, #series-a, #softbank, #startups, #transportation, #waymo, #woven-planet

Why regulators love Nuro’s self-driving delivery vehicles

Nuro’s delivery autonomous vehicles (AVs) don’t have a human driver on board. The company’s founders Dave Ferguson (president) and Jiajun Zhu’s (CEO) vision of a driverless delivery vehicle sought to do away with a lot of the stuff that is essential for a normal car to have, like doors and airbags and even a steering wheel. They built an AV that spared no room in the narrow chassis for a driver’s seat, and had no need for an accelerator, windshield or brake pedals.

So when the company petitioned the U.S. government in 2018 for a minor exemption from rules requiring a rearview mirror, backup camera and a windshield, Nuro might have assumed the process wouldn’t be very arduous.

They were wrong.

If Nuro is to become the generation-defining company its founders desire, it will be due as much to innovation in regulation as advances in the technology it develops.

In a 2019 letter to the U.S. Department of Transportation, The American Association of Motor Vehicle Administrators (AAMVA) “[wondered] about the description of pedestrian ‘crumple zones,’ and whether this may impact the vehicle’s crash-worthiness in the event of a vehicle-to-vehicle crash. Even in the absence of passengers, AAMVA has concerns about cargo ejection from the vehicle and how Nuro envisions protections from loose loads affecting the driving public.”

The National Society of Professional Engineers similarly complained that Nuro’s request lacked information about the detection of moving objects. “How would the R2X function if a small child darts onto the road from the passenger side of the vehicle as a school bus is approaching from the driver’s side?” it asked. It also recommended the petition be denied until Nuro could provide a more detailed cybersecurity plan against its bots being hacked or hijacked. (R2X is now referred to as R2)

The Alliance of Automobile Manufacturers (now the Alliance Automotive Innovation), which represents most U.S. carmakers, wrote that the National Highway Transportation Safety Agency (NHTSA) should not use Nuro’s kind of petition to “introduce new safety requirements for [AVs] that have not gone through the rigorous rule-making process.”

“What you can see is that many comments came from entrenched interests,” said David Estrada, Nuro’s chief legal and policy officer. “And that’s understandable. There are multibillion dollar industries that can be disrupted if autonomous vehicles become successful.”

To be fair, critical comments also came from nonprofit organizations genuinely concerned about unleashing robots on city streets. The Center for Auto Safety, an independent consumer group, thought that Nuro did not provide enough information on its development and testing, nor any meaningful comparison with the safety of similar, human-driven vehicles. “Indeed, the planned reliance on ‘early on-road tests … with human-manned professional safety drivers’ suggests that Nuro has limited confidence in R2X’s safe operation,” it wrote.

Nuro-R2-specs-infographic

Nuro’s R2 delivery autonomous vehicle. Image Credits: Nuro

Despite such concerns, the National Highway Traffic Safety Administration (NHTSA) granted Nuro the exemptions it sought in February last year. Up to 5,000 R2 vehicles could be produced for a limited period of two years and subject to Nuro reporting any incidents, without a windshield, rearview mirror or backup camera. Although only a small concession, it was the first — and so far, only — time the U.S. government had relaxed vehicle safety requirements for an AV.

Now Estrada and Nuro hope to use that momentum to chip away at a mountain of regulations that never envisaged vehicles controlled by on-board robots or distant humans, extending from the foothills of local and state government to the peaks of federal and international safety rules.

If Nuro is to become the generation-defining company its founders desire, it will be due as much to innovation in regulation as advances in the technology it develops.

Regulate for success

“I don’t think any of the credible, big AV players want this to be a free-for-all,” said Dave Ferguson, Nuro’s co-founder and president. “We need the confidence of a clear regulatory framework to invest the hundreds of millions or billions of dollars necessary to manufacture vehicles at scale. Otherwise, it’s really going to limit our ability to deploy.”

#alliance-of-automobile-manufacturers, #auto-safety, #automation, #automotive, #autonomous-vehicles, #av, #california, #dave-ferguson, #department-of-defense, #ec-1, #extra-crunch, #extra-crunch-ec-1, #google, #government, #lyft, #national-highway-traffic-safety-administration, #national-science-foundation, #nuro, #nuro-ec-1, #robotics, #self-driving-car, #startups, #transport, #transportation, #u-s-department-of-transportation, #united-states

When robots screw up, how can they regain human trust?

A toy robot with sparkler hands.

Enlarge / Today, in robots-and-fireworks news. (credit: Getty Images)

Establishing human-robot harmony in the workplace isn’t always easy. Beyond the common fear of automation taking human jobs, robots sometimes simply mess up. When this happens, reestablishing trust between robots and their human colleagues can be a tricky affair.

However, new research sheds some light on how automated workers can restore confidence. Largely, the study suggests that humans have an easier time trusting a robot that makes a mistake if it appears somewhat human and if the machine offers some kind of explanation, according to Lionel Robert, an associate professor at the University of Michigan’s School of Information.

When robots mess up

Even though robots are made of metal and plastic, Robert said we need to start considering our interactions with them in social terms, particularly if we want to have humans trust and rely on their automated co-workers. “Humans mess up and are able to keep working together,” he told Ars.

Read 14 remaining paragraphs | Comments

#automation, #human-robot-trust, #robotics, #robots, #science

Salesforce steps into RPA buying Servicetrace and teaming it with Mulesoft

Over the last couple of years, Robotic Process Automation or RPA has been red hot with tons of investor activity and M&A from companies like SAP, IBM and ServiceNow. UIPath had a major IPO in April and has a market cap over $30 billion. I wondered when Salesforce would get involved and today the company dipped its toe into the RPA pool, announcing its intent to buy German RPA company Servicetrace.

Salesforce intends to make Servicetrace part of Mulesoft, the company it bought in 2018 for $6.5 billion. The companies aren’t divulging the purchase price, suggesting it’s a much smaller deal. When Servicetrace is in the fold, it should fit in well with Mulesoft’s API integration, helping to add an automation layer to Mulesoft’s tool kit.

“With the addition of Servicetrace, MuleSoft will be able to deliver a leading unified integration, API management, and RPA platform, which will further enrich the Salesforce Customer 360 — empowering organizations to deliver connected experiences from anywhere. The new RPA capabilities will enhance Salesforce’s Einstein Automate solution, enabling end-to-end workflow automation across any system for Service, Sales, Industries, and more,” Mulesoft CEO Brent Hayward wrote in a blog post announcing the deal.

While Einstein, Salesforce’s artificial intelligence layer, gives companies with more modern tooling the ability to automate certain tasks, RPA is suited to more legacy operations, and this acquisition could be another step in helping Salesforce bridge the gap between older on-prem tools and more modern cloud software.

Brent Leary, founder and principal analyst at CRM Essentials says that it brings another dimension to Salesforce’s digital transformation tools. “It didn’t take Salesforce long to move to the next acquisition after closing their biggest purchase with Slack. But automation of processes and workflows fueled by realtime data coming from a growing variety sources is becoming a key to finding success with digital transformation. And this adds a critical piece to that puzzle for Salesforce/MulseSoft,” he said.

While it feels like Salesforce is joining the market late, in an investor survey we published in May Laela Sturdy, general partner at CapitalG told us that we are just skimming the surface so far when it comes to RPA’s potential.

“We’re a long way from needing to think about the space maturing. In fact, RPA adoption is still in its early infancy when you consider its immense potential. Most companies are only now just beginning to explore the numerous use cases that exist across industries. The more enterprises dip their toes into RPA, the more use cases they envision,” Sturdy responded in the survey.

Servicetrace was founded in 2004, long before the notion of RPA even existed. Neither Crunchbase nor Pitchbook shows any money raised, but the website suggests a mature company with a rich product set. Customers include Fujitsu, Siemens, Merck and Deutsche Telekom.

#automation, #cloud, #enterprise, #fundings-exits, #ma, #mergers-and-acquisitions, #rpa, #salesforce, #tc

Widespread AV adoption starts with driver assistance systems consumers can trust

In the past year, many of the conversations around autonomous vehicles (AVs) have been dominated by the same question: When will self-driving cars be the norm on public roads?

While industry leaders talked a big game on AVs monopolizing our roads back in 2016, today some experts have put widespread Level 4 adoption over a decade away. However, even that timeline only works if automakers overcome significant barriers — both technical and behavioral. The challenge of bringing AVs to consumers will be tougher than anticipated, with a central part of the effort being focused on earning the public’s trust.

Consumer confidence and mass adoption of AVs go hand in hand. To meet the projected timelines and start building this critical trust today, automakers should accelerate the adoption of autonomous capabilities into advanced driver assistance systems (ADAS).

The challenges facing current ADAS technologies

The truth is that consumers do not yet trust the ADAS capabilities in their vehicles. A 2021 AAA Foundation for Traffic Safety survey found that 80% of drivers wanted current vehicle safety systems, like automatic emergency braking and lane-keeping assistance, to work better, noting the lack of confidence consumers feel around current offerings.

While consumers seem to be aware that AV technologies are advancing quickly, this lack of trust from users will be a major barrier to full adoption and can pose a threat to the industry — no matter how far along the technology develops.

Despite significant recent advancements in the industry, including announcements from Cruise gaining permission to give rides in driverless test vehicles to passengers in California, AAA studies indicate that still only one in 10 drivers would be comfortable riding in a self-driving car. While consumers seem to be aware that AV technologies are advancing quickly, this lack of trust from users will be a major barrier to full adoption and can pose a threat to the industry — no matter how far along the technology develops.

To aid in building the public’s confidence, the industry must focus today on more advanced and reliable ADAS to meet consumer demands. However, current offerings face major challenges that must be resolved before the majority of consumers will get on board:

  1. Lack of reliability in common adverse conditions: Technologies including lidar and camera are limited to what they can “see” around them. These systems can be easily obstructed by snow, dirt and debris covering the vehicle’s sensors. Additionally, without clear, crisp lane markings — in the event of snow, heavy rainfall or off-road conditions — or strong GPS signals, the typical sensors tracking vehicle location will not function properly.
  2. Poor detection: There have been several cases where ADAS technologies have been unable to detect degraded lane markings, pedestrians, other vehicles or common on-road objects, resulting in injury and even death for drivers and pedestrians.
  3. Low understanding by the general public: While some ADAS features are designed to operate independently, there is still a consistent lack of public knowledge when it comes to understanding how to best utilize the systems’ abilities to maximize safety. This lack of awareness poses an unnecessary threat to drivers who inadvertently misuse the technology as well as to those with whom they share the roads.

Addressing these challenges and creating better automated driving experiences for consumers is a critical step to mass adoption of future AV technology. The most immediate opportunity to move the needle with consumer acceptance in this area is to target improving reliability and user experience — especially with dynamic vehicle safety systems. To do so, automated and autonomous vehicles need improved sensors and software that enhance today’s systems and, as a result, boost consumer confidence in the safety of automated capabilities.

A fresh perspective on vehicle positioning

In the last decade, the industry has made various advancements in positioning systems, which locate a vehicle to the centimeter on roadways and are critical additions to traditional hardware stacks. As a result, experts have been placing bets on technologies such as ground-penetrating radar and novel mapping techniques as the final missing piece to robust vehicle positioning due to their ability to operate in adverse driving conditions and navigate highly dynamic environments.

While it is clear there are different avenues AVs can take to increase their reliability on the road, automakers are still trying to determine which approach can unlock the change in performance required for broad adoption.

When taking a closer look at the differentiators that make these technologies stand out, a common thread is how they address three critical issues: the absence of roadside features such as on open highways, within parking lots or when a car is boxed in by trucks and vision is limited; the reliance of camera-based systems on clear, consistent lane markings; and quickly changing environments in which the scene on the surface looks different from one moment to the next and HD maps quickly become unusable. These common challenges have left consumers frustrated with inconsistent and unreliable ADAS features.

One way to overcome these critical gaps is to explore other avenues for reliable vehicle positioning such as ground-penetrating radar — which allows vehicles to determine their precise location in adverse weather or in rough terrain, amid poor GPS availability and other common barriers faced by automated systems today — to show improved autonomy is possible. By adding these novel approaches into vehicles, automakers can create more reliable and accurate ADAS features — safeguarding the automated driving experience.

Leaning on ADAS as a vehicle for consumer confidence and mass AV adoption

A recent study from Partners for Automated Vehicle Education (PAVE) found that consumers familiar with ADAS technology were more likely to feel positive about autonomous cars and that 75% who currently own a vehicle with ADAS features say they are excited about future safety technology. This shows consumer engagement in today’s ADAS features can lead to more positive attitudes on tomorrow’s AV adoption.

As an industry, where do we go from here? Many are finding that there is a unique opportunity to resolve the future issues of autonomous vehicle operations by attacking them head-on in present-day ADAS systems — where they will otherwise be a future problem that will block mass adoption.

We need to address these critical issues with ADAS technologies and create better driving experiences to earn the public’s trust. By using higher-performing ADAS as a pathway to mass AV adoption, we can arrive at the destination safely.

The industry, along with consumers, can build a safe autonomous future.

#adas, #automation, #automotive, #av, #column, #opinion, #self-driving-car, #tc, #transport, #transportation

Achieving digital transformation through RPA and process mining

Understanding what you will change is most important to achieve a long-lasting and successful robotic process automation transformation. There are three pillars that will be most impacted by the change: people, process and digital workers (also referred to as robots). The interaction of these three pillars executes workflows and tasks, and if integrated cohesively, determines the success of an enterprisewide digital transformation.

Robots are not coming to replace us, they are coming to take over the repetitive, mundane and monotonous tasks that we’ve never been fond of. They are here to transform the work we do by allowing us to focus on innovation and impactful work. RPA ties decisions and actions together. It is the skeletal structure of a digital process that carries information from point A to point B. However, the decision-making capability to understand and decide what comes next will be fueled by RPA’s integration with AI.

From a strategic standpoint, success measures for automating, optimizing and redesigning work should not be solely centered around metrics like decreasing fully loaded costs or FTE reduction, but should put the people at the center.

We are seeing software vendors adopt vertical technology capabilities and offer a wide range of capabilities to address the three pillars mentioned above. These include powerhouses like UiPath, which recently went public, Microsoft’s Softomotive acquisition, and Celonis, which recently became a unicorn with a $1 billion Series D round. RPA firms call it “intelligent automation,” whereas Celonis targets the execution management system. Both are aiming to be a one-stop shop for all things related to process.

We have seen investments in various product categories for each stage in the intelligent automation journey. Process and task mining for process discovery, centralized business process repositories for CoEs, executives to manage the pipeline and measure cost versus benefit, and artificial intelligence solutions for intelligent document processing.

For your transformation journey to be successful, you need to develop a deep understanding of your goals, people and the process.

Define goals and measurements of success

From a strategic standpoint, success measures for automating, optimizing and redesigning work should not be solely centered around metrics like decreasing fully loaded costs or FTE reduction, but should put the people at the center. To measure improved customer and employee experiences, give special attention to metrics like decreases in throughput time or rework rate, identify vendors that deliver late, and find missed invoice payments or determine loan requests from individuals that are more likely to be paid back late. These provide more targeted success measures for specific business units.

The returns realized with an automation program are not limited to metrics like time or cost savings. The overall performance of an automation program can be more thoroughly measured with the sum of successes of the improved CX/EX metrics in different business units. For each business process you will be redesigning, optimizing or automating, set a definitive problem statement and try to find the right solution to solve it. Do not try to fit predetermined solutions into the problems. Start with the problem and goal first.

Understand the people first

To accomplish enterprise digital transformation via RPA, executives should put people at the heart of their program. Understanding the skill sets and talents of the workforce within the company can yield better knowledge of how well each employee can contribute to the automation economy within the organization. A workforce that is continuously retrained and upskilled learns how to automate and flexibly complete tasks together with robots and is better equipped to achieve transformation at scale.

#api, #artificial-intelligence, #automation, #business-process-management, #cloud-elements, #column, #ec-column, #ec-enterprise-applications, #enterprise, #microsoft, #ml, #process-mining, #robot-process-automation, #uipath, #workflow

Ghost raises $100M Series D for autonomous driving and crash prevention tech

Autonomous driving system developer Ghost Locomotion has raised a $100 million Series D funding round, led by Sutter Hill Ventures. Returning investor Founders Fund also participated in the round, along with Coatue. The money will be used toward R&D as the company continues to develop its highway self-driving and crash prevention technology.

Ghost has been working on a universal collision avoidance technology. The system is premised on the idea that an autonomous driving system doesn’t need to recognize and categorize objects prior to avoiding them – a major paradigm shift. Most systems begin by identifying an object and then use image localization to determine its size, distance and other relevant features.

“We skip that step,” Ghost CEO John Hayes told TechCrunch. “We’re going to recognize anything, any mass that appears in the scene, and then we can get a distance and relative velocity to that. We can start making decisions directly off that data before we’ve classified anything.”

Ghost instead tracks the movement of clusters of pixels in a scene. Hayes pointed to instances where an object is misclassified, or objects that the system hasn’t trained on, as possible failure modes and a reason why classification does not need to be a prerequisite for collision avoidance. Much of this comes down to the certainty of the system’s decisions. According to Ghost, an autonomous system that starts from image recognition is one loaded with lots of opportunity for uncertainty – and it argues, less safe actions on the road.

One obvious counter-argument is that objects should be classified because they behave differently – a vehicle acts differently than a pedestrian, so classification is what allows a system to predict their behavior. But Hayes said that one shouldn’t start with classification, but collision avoidance. “And then if you want to make predictions, you can still do classification,” he said.

One benefit of its system, according to Ghost, is that it requires less computational power – an important consideration for vehicle owners, as higher processing demands can translate into less fuel efficiency. It’s also important for battery electric vehicles that have autonomous driving systems, as each watt of computer power demanded by the AV system can cause a reduction in driving range. Tesla, for example, revealed in 2019 that driving range could be reduced by up to 25% when the driver-assist system was enabled.

Ghost has performed most if its tests off-road, by setting up physical obstacles or by using augmented reality up against a real vehicle. It has not yet started testing its collision avoidance system in an urban environment, where decision complexity skyrockets considerably. Nor has it started testing on public highways – that will begin this year, and scale up next year, with a human safety driver behind the wheel, Hayes said.

The company seems to have slightly altered its market roadmap since it last talked to TechCrunch in 2019. Then, Ghost was developing a consumer kit that would give privately owned passenger vehicles autonomous driving capability on highways. It had estimated that it would debut the kit in 2020, for less than Tesla’s Autopilot package (which went for around $7,000 at the time).

The company hasn’t completely closed the door on this model – Hayes said that “we want to get this in front of customers” – but now it’s also talking about working with automakers directly to get its technology stack into vehicles before they’re even sold.

“We’ll find any path to market we can take,” he added. Under the straight-to-consumer model, the company is starting with a limited number of compatible models, and the cars must be relatively new due to the minimum technological requirements of the system.

Along with the funding news, Ghost also said it had brought on Jacqueline Glassman, former Chief Counsel and Acting Administrator of the National Highway Traffic Safety Administration, as General Counsel. She joined the company in April and will likely play a key role as Ghost joins other autonomous driving technology developers in the path to commercialization.

#automation, #automotive, #autonomous-driving, #autonomous-vehicles, #av, #ghost-locomotion, #tc, #transportation

How to launch a successful RPA initiative

Robotic process automation (RPA) is rapidly moving beyond the early adoption phase across verticals. Automating just basic workflow processes has resulted in such tremendous efficiency improvements and cost savings that businesses are adapting automation at scale and across the enterprise.

While there is a technical component to robotic automation, RPA is not a traditional IT-driven solution. It is, however, still important to align the business and IT processes around RPA. Adapting business automation for the enterprise should be approached as a business solution that happens to require some technical support.

A strong working relationship between the CFO and CIO will go a long way in getting IT behind, and in support of, the initiative rather than in front of it.

A strong working relationship between the CFO and CIO will go a long way in getting IT behind, and in support of, the initiative rather than in front of it.

More important to the success of a large-scale RPA initiative is support from senior business executives across all lines of business and at every step of the project, with clear communications and an advocacy plan all the way down to LOB managers and employees.

As we’ve seen in real-world examples, successful campaigns for deploying automation at scale require a systematic approach to developing a vision, gathering stakeholder and employee buy-in, identifying use cases, building a center of excellence (CoE) and establishing a governance model.

Create an overarching vision

Your strategy should include defining measurable, strategic objectives. Identify strategic areas that benefit most from automation, such as the supply chain, call centers, AP or revenue cycle, and start with obvious areas where business sees delays due to manual workflow processes. Remember, the goal is not to replace employees; you’re aiming to speed up processes, reduce errors, increase efficiencies and let your employees focus on higher value tasks.

#automation, #business-process-automation, #business-process-management, #column, #ec-column, #ec-enterprise-applications, #ec-how-to, #enterprise, #robotic-process-automation, #rpa, #saas, #workflow

SoftBank, Uber, Tencent set to reap rewards from Didi IPO

After years of speculation, Didi Chuxing, China’s ride-sharing behemoth, finally unveiled its IPO filing in the U.S., giving a glimpse into its money-losing history.

Didi didn’t disclose the size of its raise. Reuters reported the company could raise around $10 billion at a valuation of close to $100 billion.

Cheng Wei, Didi’s 38-year-old founder owns 7% of the company’s shares and controls 15.4% of its voting power before the IPO, according to the prospectus. Major shareholder SoftBank Vision Fund owns 21.5% of the company, followed by Uber with 12.8% and Tencent at 6.8%.

The nine-year-old company, which famously acquired Uber’s China operations in 2016, is more than a ride-hailing platform now. It has a growing line of businesses like bike-sharing, grocery, intra-city freight, financial services for drivers, electric vehicles and Level 4 robotaxis, which it defines as “the pinnacle of our design for future mobility” for its potential to lower costs and improve safety.

Didi set up an autonomous driving subsidiary that banked $500 million from SoftBank in May last year. The unit now operates a team of over 500 members and a fleet of over 100 autonomous vehicles.

For the twelve months ended March, Didi served 493 million annual active users and saw 41 million transactions on a daily basis.

Didi had been operating in the red from 2018 to 2020, when it finished the year with a $1.6 billion net loss, but managed to turn the tide in the first quarter of 2021 by racking up a net profit of $837 million, which it recognized was primarily due to the investment income from the deconsolidation of Chengxin, its cash-burning grocery group buying initiative, and an equity investment disposal.

Revenue from the quarter also more than doubled year-over-year to $6.6 billion. China accounts for over 90% of Didi’s revenues as of late. The company has tried to expand its presence in a dozen overseas countries like Brazil, where it bought local ride-hailing business 99 Taxis.

Of its mobility revenues in China, more than 97% came from ride-hailing between 2018 and 2020. Taxi hailing, chauffeur and carpooling, a lucrative business that was revamped following two deadly accidents, made up a trifling share.

Didi plans to spend 30% of its IPO proceeds on shared mobility, electric vehicles, autonomous driving and other technologies. 30% will go towards its international expansion and another 20% will be used for new product development.

#asia, #automation, #carsharing, #china, #didi, #didi-chuxing, #funding, #robotaxi, #robotics, #softbank, #softbank-group, #transport, #transportation, #uber

Here’s what’s on tap today at TC Sessions: Mobility 2021

It’s game day for mobility tech mavens around the world. Well, at least for the ones who made the savvy decision to attend TC Sessions: Mobility 2021. Are you ready for a day packed with potential, overflowing with opportunity and focused on the future of transportation? Yeah, you are, and so are we!

No FOMO zone: Did you wait until the last minute? We don’t judge — simply purchase a pass at the virtual door.

Let’s take a look at just some of the speakers, presentations and breakout sessions on tap today. We’re talking about leading visionaries, founders and makers of mobility tech. They just might have info you need to know, amirite? The times listed below are EDT, but the event agenda will automatically reflect your time zone,

Throughout the course of the day: Be sure to make time to meet, greet and network with the 28 early-stage startups exhibiting in our virtual expo area (seriously, they’re an impressive bunch). The platform lets exhibitors present live demos, host Q&As about their products or hold private 1:1 meetings. Go mining for opportunities!

2:05 pm – 2:15 pm

EV Founders in Focus: We sit down with Ben Schippers, co-founder and CEO of TezLab, an app that operates like a Fitbit for Tesla vehicles (and soon other EVs) and allows drivers to go deep into their driving data. The app also breaks down the exact types and percentages of fossil fuels and renewable energy coming from charging locations.

2:40 pm – 3:10 pm

Equity, Accessibility and Cities: Can mobility be accessible, equitable and remain profitable? We have brought together community organizer, transportation consultant and lawyer Tamika L. Butler; Remix by Via co-founder and CEO Tiffany Chu and Revel co-founder and CEO Frank Reig to discuss how (and if) shared mobility can provide equity in cities, while still remaining a viable and even profitable business. The trio will also dig into the challenges facing cities and how policy may affect startups.

3:10 pm – 3:40 pm

The Rise of Robotaxis in China: Silicon Valley has long been viewed as a hub for autonomous vehicle development. But another country is also leading the charge. Executives from three leading Chinese robotaxi companies (WeRide, AutoX and Momenta) — that also have operations in Europe or the U.S. — will join us to provide insight into the unique challenges of developing and deploying the technology in China and how it compares to other countries.

That’s just a tiny taste of what today has in store for you. Choosing which of the 20 presentations and breakout sessions to attend could be tough. The good news is that you can catch anything you missed — or want to review again — with video-on-demand.

TC Sessions: Mobility 2021 kicks off today — go drive this opportunity-packed day like you stole it.

#articles, #automation, #ben-schippers, #china, #europe, #fitbit, #frank-reig, #judge, #mining, #momenta, #renewable-energy, #robotaxi, #robotics, #science-and-technology, #tamika-l-butler, #tc, #tc-sessions-mobility-2021, #technology, #tezlab, #tiffany-chu, #united-states

Apple is bringing Shortcuts to the Mac and starts transition from Automator

Apple has announced the next major version of macOS at WWDC 2021 — macOS Monterey. Among other features, Apple is going to release Shortcuts on macOS. It’s going to look and work a lot like Shortcuts on iOS and iPadOS.

“The Mac has a long history of automation with command line, shell scripts, Apple scripts and Automator. And on iOS, we've made automation even easier with Shortcuts,” SVP of Software Engineering Craig Federighi said. “And this year we're bringing Shortcuts to the Mac.”

In the new Shortcuts app, you can see a gallery of popular shortcuts. It’s going to be interesting to see what exactly you can trigger with shortcuts, but you can expect to be able to launch apps, create GIFs, send a message, create an email, launch a website, etc.

After that, you can trigger your shortcuts in the right column of the Finder, in the menubar and in Spotlight. You can also trigger them with Siri.

With this announcement, Apple is also setting the stage for the end of Automator. “This is just the start of a multi-year transition Automator will continue to be supported, and you can import Automator workflows into beginning one with shortcuts,” Federighi said.

If you read between the lines, it sounds like Apple doesn’t plan to add new features to Automator. Shortcuts is the future of automation on macOS, iOS and iPadOS.

read more about Apple's WWDC 2021 on TechCrunch

#apple, #apps, #automation, #automator, #developer, #macos, #macos-monterey, #shortcuts

Tezlab CEO Ben Schippers to discuss the Tesla effect and the next wave of EV startups at TC Sessions: Mobility 2021

As Tesla sales have risen, interest in the company has exploded, prompting investment and interest in the automotive industry, as well as the startup world.

Tezlab, a free app that’s like a Fitbit for a Tesla vehicle, is just one example of the numerous startups that have sprung up in the past few years as electric vehicles have started to make the tiniest of dents in global sales. Now, as Ford, GM, Volvo, Hyundai along with newcomers Rivian, Fisker and others launch electric vehicles into the marketplace, more startups are sure to follow.

Ben Schippers, the co-founder and CEO of Tezlab, is one of two early-stage founders who will join us at TC Sessions: Mobility 2021 to talk about their startups and the opportunities cropping up in this emerging age of EVs. The six-person team behind TezLab was born out of HappyFunCorp, a software engineering shop that builds apps for mobile, web, wearables and Internet of Things devices for clients that include Amazon, Facebook and Twitter, as well as an array of startups.

HFC’s engineers, including Schippers, who also co-founded HFC, were attracted to Tesla  because of its techcentric approach and one important detail: the Tesla API endpoints are accessible to outsiders. The Tesla API is technically private. But it exists allowing the Tesla’s app to communicate with the cars to do things like read battery charge status and lock doors. When reverse-engineered, it’s possible for a third-party app to communicate directly with the API.

Schippers’ experience extends beyond scaling up Tezlab. Schippers consults and works with companies focused on technology and human interaction, with a sub-focus in EV.

The list of speakers at our 2021 event is growing by the day and includes Motional’s president and CEO Karl Iagnemma and Aurora co-founder and CEO Chris Urmson, who will discuss the past, present and future of AVs. On the electric front is Mate Rimac, the founder of Rimac Automobili, who will talk about scaling his startup from a one-man enterprise in a garage to more than 1,000 people and contracts with major automakers.

We also recently announced a panel dedicated to China’s robotaxi industry, featuring three female leaders from Chinese AV startups: AutoX’s COO Jewel Li, Huan Sun, general manager of Momenta Europe with Momenta, and WeRide’s VP of Finance Jennifer Li.

Other guests include, GM’s VP of Global Innovation Pam Fletcher, Scale AI CEO Alexandr Wang, Joby Aviation founder and CEO JoeBen Bevirt, investor and LinkedIn founder Reid Hoffman (whose special purpose acquisition company just merged with Joby), investors Clara Brenner of Urban Innovation Fund, Quin Garcia of Autotech Ventures and Rachel Holt of Construct Capital, and Zoox co-founder and CTO Jesse Levinson.

And we may even have one more surprise — a classic TechCrunch stealth company reveal to close the show.

Don’t wait to book your tickets to TC Sessions: Mobility as prices go up at our virtual door.

#alexandr-wang, #amazon, #api, #articles, #aurora, #automation, #autotech-ventures, #autox, #av, #ben-schippers, #ceo, #china, #chris-urmson, #clara-brenner, #construct-capital, #coo, #facebook, #fitbit, #founder, #happyfuncorp, #hyundai, #jesse-levinson, #jewel-li, #joby, #joby-aviation, #joeben-bevirt, #karl-iagnemma, #linkedin, #major, #mate-rimac, #momenta, #motional, #pam-fletcher, #quin-garcia, #rachel-holt, #reid-hoffman, #rimac-automobili, #rivian, #robotaxi, #robotics, #scale-ai, #science-and-technology, #self-driving-cars, #startup-company, #tc, #technology, #tesla, #tezlab, #urban-innovation-fund, #volvo, #weride, #zoox

Cognigy raises $44M to scale its enterprise-focused conversational AI platform

Artificial intelligence is becoming an increasingly common part of how customer service works — a trend that was accelerated in this past year as so many other services went virtual and digital — and today a startup that has built a set of low-code tools to help enterprises integrate more AI into their customer service processes is announcing some funding to fuel its growth.

Cognigy, which provides a low-code conversational AI platform that notably can be used flexibly across a range of applications and geographies — it supports 120 languages; it can be used in external or internal service applications; it can support voice services but also chatbots; it provides real-time assistance for human agents and usage analytics or fully-automated responses; it can integrate with standard call center software, and also with RPA packages; and it can be run in the cloud or on-premise — has closed a round of $44 million, funding that it will be using to continue scaling its business internationally.

Insight Partners is leading the Series B investment, with previous backers DN Capital, Global Brain, Nordic Makers, Inventures and Digital Innovation and Growth also participating. The Dusseldorf-based company had previously only raised $11 million and spent the first several years of business bootstrapped.

Cognigy is not disclosing its valuation but it has up to now built up a concentration of customers in areas like transportation, e-commerce and insurance and counts a number of big multinational companies among its customer list, including Lufthansa, Mobily, BioNTech, Vueling Airlines, Bosch, and Daimler, with “thousands” of virtual assistants now powered by Cognigy live in the market.

With 25% of Cognigy’s business already coming from the U.S., the plan now is to use some funding to invest in building out its service deeper into the U.S., Asia and across more of Europe, CEO and founder Philipp Heltewig said in an interview.

“Conversational AI” these days appears in many guises: it can be a chatbot you come across on a website when you’re searching for something, or it can be prompts provided to agents or salespeople, information and real-time feedback to help them do their jobs better. Conversational AI can also be a personal assistant on your company’s HR application to help you book time off or deal with any number of other administrative jobs, or a personal assistant that helps you use your phone or set your house alarm.

There are a number of companies in the tech world that have built tools to address these various use cases. Specifically in the area of services aimed at enterprises, some of them, like Gong, are raising huge money right now. What is notable about Cognigy is that it has built a platform that is attempting to address a wide swathe of applications: one platform, many uses, in other words.

Cognigy’s other selling point is that it is playing into the new interest in low- and no-code tools, which in Cognigy’s case makes the integration of AI into a customer assistance process a relatively easy task, something that can be built not just by developers, but data scientists, those working directly on conversation design, and non-technical business users using the tools themselves.

“The low-code platform helps enterprises adopt what is otherwise complex technology in an easy and flexible way, whether it is customer or employee contact center,” said Heltewig. As you might expect, there are some direct competitors in the low- and no-code conversational AI space, too, including Ada, Talkie, Snaps and more.

Flexibility seems to be the order of the day for enterprises, and also the companies building tools for them: it means that a company can grow into a larger customer, and that in theory Cognigy will also evolve the platform based on what its customers need. As one example, Heltewig pointed out that a number of its customers are — contrary to the beating drum and march you see every day towards cloud services — running a fair number of applications on-premises, since this appears to be a key way to ensure the security of the customer data that they handle.

“Lufthansa could never run its customer services in the cloud because they handle a lot of sensitive data and they want full ownership of it,” he noted. “We can run cloud services and have a full offering for those who want it, but many large enterprises prefer to run their services on premises.”

Teddie Wardi, an MD at Insight, is joining the board with this round. “We are thrilled to be leading Cognigy’s Series B as the company continues on their ScaleUp journey,” he said in a statement. “Evident by their strong customer retention, Cognigy has created an essential product for global businesses to improve their customer experience in an efficient and effortless manner. With the new funding, Cognigy will be able to expand their leadership position to reach new markets and acquire more customers.”

#artificial-intelligence, #automation, #cognigy, #conversational-ai, #customer-support, #enterprise, #funding, #nlp

ChargerHelp co-founder, CEO Kameale C. Terry is heading to TC Sessions: Mobility 2021

Thousands of electric vehicle charging stations will be built around the country over the next decade. ChargerHelp!, founded in January 2020 by Kameale C. Terry and Evette Ellis, wants to make sure they stay up and running.

The idea for the on-demand repair app for EV charging stations came to Terry when she was working at EV Connect, where she held a number of roles including director of programs and head of customer experience. She noticed long wait times to fix non-electrical issues at charging stations due to the industry practice to use electrical contractors.

“When the stations went down we really couldn’t get anyone on site because most of the issues were communication issues, vandalism, firmware updates or swapping out a part — all things that were not electrical,” Terry said in an interview with TechCrunch earlier this year.

After Terry quit her job to start ChargerHelp!, she joined the Los Angeles Cleantech Incubator, where she developed a first-of-its-kind EV Network Technician Training Curriculum. Shortly after, Terry and Ellis were accepted into Elemental Excelerator’s startup incubator and have landed contracts with major EV charging network providers like EV Connect and SparkCharge.

The company uses a workforce-development approach to hiring, meaning that they only hire in cohorts. Workers receive full training, earn two safety licenses, are guaranteed a wage of $30 an hour and receive shares in the startup, Terry said.

We’re excited to announce that Kameale Terry will be joining us at TC Sessions: Mobility 2021, a one-day virtual event that is scheduled June 9. We’ll be covering a lot of ground with Terry, from how she developed her EV repair curriculum to what she sees in the company’s future.

Each year TechCrunch brings together founders, investors, CEOs and engineers who are working on all things transportation and mobility. If it moves people and packages from Point A to Point B, we cover it. This year’s agenda is filled with leaders in the mobility space who are shaping the future of transportation, from EV charging to autonomous vehicles to urban air taxis.

Among the growing list of speakers are Rimac Automobili founder Mate RimacRevel Transit CEO Frank Reig, community organizer, transportation consultant and lawyer Tamika L. Butler and Remix/Via co-founder and CEO Tiffany Chu, who will come together to discuss how (and if) urban mobility can increase equity while still remaining a viable business.

Other guests include Motional’s President and CEO Karl Iagnemma, Aurora co-founder and CEO Chris Urmson, GM‘s VP of Global Innovation Pam FletcherScale AI CEO Alexandr WangJoby Aviation founder and CEO JoeBen Bevirt, investor and LinkedIn founder Reid Hoffman (whose special purpose acquisition company just merged with Joby), investors Clara Brenner of Urban Innovation FundQuin Garcia of Autotech Ventures and Rachel Holt of Construct CapitalZoox co-founder and CTO Jesse Levinson.

We also recently announced a panel dedicated to China’s robotaxi industry, featuring three female leaders from Chinese AV startups: AutoX’s COO Jewel LiHuan Sun, general manager of Momenta Europe with Momenta, and WeRide’s VP of Finance Jennifer Li.

Don’t wait to book your tickets to TC Sessions: Mobility as prices go up at the door. Grab your passes right now and hear from today’s biggest mobility leaders.

#alexandr-wang, #aurora, #automation, #automotive, #autotech-ventures, #autox, #av, #ceo, #chargerhelp, #charging-station, #china, #chris-urmson, #clara-brenner, #construct-capital, #coo, #electric-vehicle, #electric-vehicle-charging-station, #electric-vehicles, #ev-connect, #events, #frank-reig, #jesse-levinson, #jewel-li, #joby, #joby-aviation, #joeben-bevirt, #karl-iagnemma, #linkedin, #mate-rimac, #momenta, #motional, #pam-fletcher, #quin-garcia, #rachel-holt, #reid-hoffman, #revel-transit, #rimac-automobili, #robotaxi, #robotics, #scale-ai, #science-and-technology, #sparkcharge, #startups, #tamika-l-butler, #tc, #tc-sessions-mobility-2021, #technology, #tiffany-chu, #transport, #transportation, #urban-innovation-fund, #weride, #zoox

See what’s new from Wejo, CMC, iMerit, Plus, oVice, & Michigan at TechCrunch’s mobility event

We’re in the final run-up to TC Sessions: Mobility 2021 on October 9, and the great stuff just keeps on coming. We’ve stacked the one-day agenda with plenty of programming to keep you engaged, informed and on track to build a stronger business. You’ll always find amazing speakers — some of the most innovative minds out there — on the main stage and in breakout sessions.

Dramatic pause for a pro tip: Don’t have a pass yet? Buy one here now for $125, before prices go up at the door.

“I enjoyed the big marquee speakers from companies like Uber, but it was the individual presentations where you really started to get into the meat of the conversation and see how these mobile partnerships come to life.” — Karin Maake, senior director of communications at FlashParking.

We have another exciting bit of news. We’re hosting pitch session for early-stage startup founders who exhibit in the expo at TC Sessions: Mobility. Each startup gets five minutes to pitch to attendees in a breakout session. Remember, this conference has a global reach — talk about visibility! Want to pitch? Buy an Early Stage Startup Exhibitor Package as we only have 2 packages left.

Alrighty then…let’s look at some of the breakout & main stage sessions waiting for you at TC Sessions: Mobility 20201.

Innovating Future Mobility for Global Scale

Wednesday, October 9, 10:00 am -10:50 am PDT

Learn how the CMC’s model of bringing their Clients’ new technologies to market is new and innovative, going beyond a typical demonstration or pilot program, to the point of product launch and sustaining market viability. Hear from an expert panel about how the CMC’s programming is unique, innovative, and game-changing.

  • Neal Best, Director of Client Services, California Mobility Center (CMC)
  • Bill Brandt, Business Development Advisor, Zeus Electric Chassis
  • Mark Rawson, Chief Operating Officer, California Mobility Center (CMC)
  • Scott Ungerer, Founder and Managing Director, EnerTech Capital

Public-Private Partnerships: Advancing the Future of Mobility and Electrification

Wednesday, October 9, 10:45 am -11:05 am PDT

The future of mobility starts with the next generation of transportation solutions. Attendees will hear from some of the most innovative names on opportunities that await when public and private entities team up to revolutionize the way we think about technology. Trevor Pawl, Michigan’s Chief Mobility Officer, will be joined by Nina Grooms Lee, Chief Product Officer of May Mobility.

  • Nina Grooms Lee, Chief Product Officer, May Mobility
  • Trevor Pawl, Chief Mobility Officer, State of Michigan

How Edge Cases and Data Will Enable Autonomous Transportation in Cities Across the U.S.

Delivering Supervised Autonomous Trucks Globally

Wednesday, October 9, 12:40pm – 1:00pm PDT

Plus is applying autonomous driving technology to launch supervised autonomous trucks today in order to dramatically improve safety, efficiency and driver comfort, while addressing critical challenges in long-haul trucking — driver shortage and high turnover, rising fuel costs, and reaching sustainability goals. Mass production of our supervised autonomous driving solution, PlusDrive, starts this summer. In the next few years, tens of thousands of heavy trucks powered by PlusDrive will be on the road. Plus’s COO and Co-Founder Shawn Kerrigan will introduce PlusDrive and our progress of deploying this driver-in solution globally. He will also share our learnings from working together with world-leading OEMs and fleet partners to develop and deploy autonomous trucks at scale.

  • Shawn Kerrigan, COO and Co-Founder, Plus

How Edge Cases and Data Will Enable Autonomous Transportation in Cities Across the U.S.

Wednesday, October 9, 11:00 am – 11:50am

Data will play a vital role in solving the critical edge cases required to gain city approval and deploy autonomous transportation at scale. Pilot projects are underway across the U.S. and cities such as Las Vegas are leading the way for progressive policies, testing and adoption. But, how do these projects involving a limited number of vehicles gain city approval, expand to larger geographic areas, include more use cases and service more people? Join our expert panel discussion as we examine the progress, challenges and road ahead in harnessing data to enable multiple modes of autonomous transportation in major cities across the U.S.

  • Chris Barker, Founder & CEO, CBC
  • Radha Basu, Founder & CEO, iMerit
  • Michael Sherwood, CIO, City of Las Vegas

Making Mobility Data Accessible to Governmental Agencies to Meet New Transportation Demands

Wednesday, October 9, 1:45pm – 2:05pm

Wejo provides accurate and unbiased unique journey data, curated from millions of connected cars, to help local, state, province and federal government agencies visualize traffic and congestion conditions. Unlock a deeper understanding of mobility trends, to make better decisions, support policy development and solve problems more effectively for your towns and cities.

  • Brett Scott, VP of Partnerships

Will Remote Work Push Japan’s Rural Mobility Forward?

Wednesday, October 9, 1:45pm – 2:05pm

With remote work becoming the new normal and the mass movement from the city to the Japanese countryside, the trend of private car ownership is growing day by day. During this session, we’ll be hearing from Sae Hyung Jung, serial entrepreneur, founder and CEO of oVice. oVice is an agile communication tool that facilitates hybrid remote and virtual meetups. Most notably, a hope that can trigger a sudden expansion in the Japanese mobility and vehicle infrastructure.

  • Sae Hyung Jung, Founder & CEO, oVice

#automation, #california, #car-ownership, #ceo, #chief, #chief-operating-officer, #driver, #flashparking, #may-mobility, #michigan, #mobility, #nina-grooms-lee, #officer, #plus, #robotics, #science-and-technology, #self-driving-cars, #self-driving-truck, #tc, #technology, #transport, #uber, #vp

JD.com, Meituan and Neolix to test autonomous deliveries on Beijing public roads

People in a Beijing suburb will begin to see autonomous delivery mini-vans across their neighborhood, moving cautiously alongside human delivery riders belting down the streets.

Beijing has greenlighted JD.com, Meituan, and Neolix to trial self-driving delivery vehicles on designated public roads in the Yizhuang Development Area, an economic and technological growth pilot initiated by the municipal government of the capital city, according to an announcement made by local authorities at a mobility conference on Tuesday. Yizhuang has aggressively rolled out 5G coverage in part to prepare the infrastructure for autonomous driving ventures.

All three companies are using dainty box-on-wheels vehicles similar to those of Nuro to shuffle goods around. Three-year-old Neolix, backed by Chinese electric vehicle startup Li Auto, focuses on making self-driving vehicles for retail, surveillance and other city services, while both JD.com and Meituan are tech heavyweights that find unmanned delivery increasingly important to their existing core business.

Meituan’s self-driving delivery vehicle / Photo: Meituan via WeChat

Online retailer JD.com hires its own in-house delivery staff while Meituan relies on a national network of riders to bring restaurant takeout to customers. Both have been working on autonomous driving technologies internally in recent years and are also testing small fleets of delivery drones in China.

Neolix will place 150 delivery robots on Beijing roads by June. JD.com declined to disclose its deployment number. Meituan can’t be immediately reached for comment.

At the Tuesday event, authorities from the Beijing pilot zone also laid out rules for operating zero-occupant delivery vehicles in the area. The robots are categorized as “non-motor vehicles,” which suggests they will be moving next to bicycles and electric scooters instead of faster-moving cars. Road conditions in Chinese cities are often much more complicated than in the United States, even on sidewalks and bike lanes thanks to unpredictable pedestrians, unleashed pets, and reckless scooter riders.

Importantly, the rules also stipulate that the robots need to have safety drivers “on the spot and remotely.”

Neolix’s delivery robot / Photo: Neolix via WeChat

JD.com says its technology allows every remote safety driver to monitor up to 50 operating delivery robots simultaneously. Its vehicles will carry packages from logistics centers and supermarkets to nearby office buildings, residential complexes and school campuses. Customers will then fetch their order directly from the van using a pick-up code sent to them through a text message ahead of time.

Neolix’s vehicles in the pilot area, in comparison, act more like mobile vending machines peddling snacks and lunchboxes to workers around office complexes. Users can place their order on a little screen attached to the robot, pay by a QR code and get their warm bento or ice cream instantaneously.

#artificial-intelligence, #asia, #automation, #beijing, #china, #electric-vehicles, #jd-com, #li-auto, #meituan, #nuro, #robotics, #self-driving-cars, #take-out, #tc, #transportation

Only 3 startup demo booths left at TC Sessions: Mobility 2021

Listen up mobility mavericks. TC Sessions: Mobility 2021 is right around the corner of your calendar (June 9). If you want to place your ground-breaking, edge-cutting, envelope-pushing (no extra charge for clichés) early-stage startup in front of the world’s leading mobility movers, shakers and makers you gotta hustle. You have just one week left to buy one of our remaining three Startup Exhibitor Packages.

Here’s what the $380 package includes, plus a few suggestions on ways to take full advantage of the virtual platform’s capabilities and boost the opportunity factor. Note: Exhibitors must be pre-Series A, early-stage startups in the mobility field.

  • Virtual booth space
  • Lead generation
  • 4 conference passes
  • Full event access
  • Videos on-demand
  • Breakout sessions
  • Networking with CrunchMatch

Hopin, our virtual platform, lets you tap into your creativity. Include a product walk-through video — complete with links to your website and social media accounts — at your virtual booth. But get this. Your booth also includes live stream capability. Make the most of that opportunity. Share your screen, host a live demo or a product tutorial and moderate the chat area.

Maybe you’d like to host and live stream your own Q&A session. Go for it. Or why not establish yourself as a subject matter expert? Choose your topic and combine your virtual booth and CrunchMatch, our AI-powered networking platform, to send invitations to the people you want to impress and get the conversation started. And of course, you can always schedule 1:1 video calls.

Since you’ll have four event passes, you and your team can tend to booth business and take in a range of presentations. Here are just two examples of what’s in store. Check out the event agenda and plan your schedule now.

Supercharging Self-Driving Super Vision: Few startups were as prescient as Scale AI when it came to anticipating the need for massive sets of tagged data for use in AI. Co-founder and CEO Alex Wang also made a great bet on addressing the needs of lidar sensing companies early on, which has made the company instrumental in deploying AV networks. We’ll hear about what it takes to make sense of sensor data in driverless cars and look at where the industry is headed.

AVs: Past, Present and Future: TechCrunch Mobility will talk to two pioneers, and competitors, who are leading the charge to commercialize autonomous vehicles. Karl Iagnemma, president of the $4 billion Hyundai-Aptiv joint venture known as Motional, and Chris Urmson, the co-founder and CEO of Aurora, will discuss — and maybe even debate — the best approach to AV development and deployment, swap stories of the earliest days of the industry and provide a few forecasts of what’s to come.

TC Sessions: Mobility 2021 takes place on June 9, but you have just one week left to reserve your virtual demo booth. Grab this opportunity and get your startup in front of the industry’s top movers and makers.

Is your company interested in sponsoring or exhibiting at TC Sessions: Mobility 2021? Contact our sponsorship sales team by filling out this form.

#alex-wang, #aptiv, #artificial-intelligence, #aurora, #automation, #av, #chris-urmson, #consumer-electronics-show, #economy, #entrepreneurship, #hyundai, #karl-iagnemma, #president, #private-equity, #robotics, #science-and-technology, #self-driving-car, #startup-company, #tc, #tc-sessions-mobility-2021, #techcrunch, #technology

Artificial raises $21M led by Microsoft’s M12 for a lab automation platform aimed at life sciences R&D

Automation is extending into every aspect of how organizations get work done, and today comes news of a startup that is building tools for one industry in particular: life sciences. Artificial, which has built a software platform for laboratories to assist with, or in some cases fully automate, research and development work, has raised $21.5 million.

It plans to use the funding to continue building out its software and its capabilities, to hire more people, and for business development, according to Artificial’s CEO and co-founder David Fuller. The company already has a number of customers including Thermo Fisher and Beam Therapeutics using its software directly and in partnership for their own customers. Sold as aLab Suite, Artificial’s technology can both orchestrate and manage robotic machines that labs might be using to handle some work; and help assist scientists when they are carrying out the work themselves.

“The basic premise of what we’re trying to do is accelerate the rate of discovery in labs,” Fuller said in an interview. He believes the process of bringing in more AI into labs to improve how they work is long overdue. “We need to have a digital revolution to change the way that labs have been operating for the last 20 years.”

The Series A is being led by Microsoft’s venture fund M12 — a financial and strategic investor — with Playground Global and AME Ventures also participating. Playground Global, the VC firm co-founded by ex-Google exec and Android co-creator Andy Rubin (who is no longer with the firm), has been focusing on robotics and life sciences and it led Artificial’s first and only other round. Artificial is not disclosing its valuation with this round.

Fuller hails from a background in robotics, specifically industrial robots and automation. Before founding Artificial in 2018, he was at Kuka, the German robotics maker, for a number of years, culminating in the role of CTO; prior to that, Fuller spent 20 years at National Instruments, the instrumentation, test equipment and industrial software giant. Meanwhile, Artificial’s co-founder, Nikhita Singh, has insight into how to bring the advances of robotics into environments that are quite analogue in culture. She previously worked on human-robot interaction research at the MIT Media Lab, and before that spent years at Palantir and working on robotics at Berkeley.

As Fuller describes it, he saw an interesting gap (and opportunity) in the market to apply automation, which he had seen help advance work in industrial settings, to the world of life sciences, both to help scientists track what they are doing better, and help them carry out some of the more repetitive work that they have to do day in, day out.

This gap is perhaps more in the spotlight today than ever before, given the fact that we are in the middle of a global health pandemic. This has hindered a lot of labs from being able to operate full in-person teams, and increased the reliance on systems that can crunch numbers and carry out work without as many people present. And, of course, the need for that work (whether it’s related directly to Covid-19 or not) has perhaps never appeared as urgent as it does right now.

There have been a lot of advances in robotics — specifically around hardware like robotic arms — to manage some of the precision needed to carry out some work, but up to now no real efforts made at building platforms to bring all of the work done by that hardware together (or in the words of automation specialists, “orchestrate” that work and data); nor link up the data from those robot-led efforts, with the work that human scientists still carry out. Artificial estimates that some $10 billion is spent annually on lab informatics and automation software, yet data models to unify that work, and platforms to reach across it all, remain absent. That has, in effect, served as a barrier to labs modernising as much as they could.

A lab, as he describes it, is essentially composed of high-end instrumentation for analytics, alongside then robotic systems for liquid handling. “You can really think of a lab, frankly, as a kitchen,” he said, “and the primary operation in that lab is mixing liquids.”

But it is also not unlike a factory, too. As those liquids are mixed, a robotic system typically moves around pipettes, liquids, in and out of plates and mixes. “There’s a key aspect of material flow through the lab, and the material flow part of it is much more like classic robotics,” he said. In other words, there is, as he says, “a combination of bespoke scientific equipment that includes automation, and then classic material flow, w