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MIT is reviewing its relationship with AI startup SenseTime, one of the Chinese tech firms blacklisted by the US
The Massachusetts Institute of Technology said it is reviewing the university’s relationship with SenseTime, one of eight Chinese tech companies placed on the U.S. Entity List yesterday for their alleged role in human rights abuses against Muslim minority groups in China.
An MIT spokesperson told Bloomberg that “MIT has long had a robust export controls function that pays careful attention to export control regulations and compliance. MIT will review all existing relationships with organizations added to the U.S. Department of Commerce’s Entity List, and modify any interactions, as necessary.”
A SenseTime representative told Bloomberg, “We are deeply disappointed with this decision by the U.S. Department of Commerce. We will work closely with all relevant authorities to fully understand and resolve the situation.”
The companies placed on the blacklist included several of China’s top AI startups and companies that have supplied software to mass surveillance systems that may have been used by the Chinese government to persecute Uighurs and other Muslim minority groups.
Over one million Uighurs are believed to currently be held in detention camps, where human rights observers report they have been subjected to forced labor and torture.
SenseTime, the world’s mostly highly valued AI startup, provided software to the Chinese government for its national surveillance system, including CCTV cameras. It was the first company to join an MIT Intelligence Quest initiative launched last year with the goal of “driv[ing] technological breakthroughs in AI that have the potential to confront some of the world’s greatest challenges.” Since then, it has provided funding for 27 projects by MIT researchers.
Earlier this year, MIT ended its working relationships with Huawei and ZTE over alleged sanction violations.
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Element AI raises $151M on a $600-700M valuation to help companies build and run AI solutions
While tech giants like Google and Amazon build and invest in a multitude of artificial intelligence applications to grow their businesses, a startup has raised a big round of funding to help those that are not technology businesses by nature also jump into the AI fray.
Element AI, the very well-funded, well-connected Canadian startup that has built an AI systems integrator of sorts to help other companies develop and implement artificial intelligence solutions — an “Accenture” for machine learning, neural network-based solutions, computer vision applications and so on — is today announcing a further 200 million Canadian dollars ($151.3 million) in funding, money that it plans to use to commercialise more of its products, as well as to continue working on R&D, specifically working on new AI solutions.
“Operationalising AI is currently the industry’s toughest challenge, and few companies have been successful at taking proofs-of-concept out of the lab, imbedding them strategically in their operations, and delivering actual business impact,” said Element AI CEO Jean-François (JF) Gagné in a statement. “We are proud to be working with our new partners, who understand this challenge well, and to leverage each other’s expertise in taking AI solutions to market.”
The company did not disclose its valuation in the short statement announcing the funding, nor has it ever talked about it publicly, but PitchBook notes that as of its previous funding round of $102 million back in 2017, it had a post-money valuation of $300 million, a figure a source close to the company confirmed to me. From what I understand, the valuation now is between $600 million and $700 million, a mark of how Element AI has grown, which is especially interesting, considering how quiet is has been.
The funding is being led by Caisse de dépôt et placement du Québec (CDPQ), along with participation from McKinsey & Company and its advanced analytics company QuantumBlack; and the Québec government. Previous investors DCVC (Data Collective), Hanwha Asset Management, BDC (Business Development Bank of Canada), Real Ventures and others also participated, with the total raised to date now at C$340 million ($257 million). Other strategic investors in the company have included Microsoft, Nvidia and Intel.
Element AI was started under an interesting premise that goes something like this: AI is the next major transformational shift — not just in computing, but in how businesses operate. But not every business is a technology business by DNA, and that creates a digital divide of sorts between the companies that can identify a problem that can be fixed by AI and build/invest in the technology to do that and those that cannot.
Element AI opened for business from the start as a kind of “AI shop” for the latter kinds of enterprises, to help them identify areas where they could build AI solutions to work better, and then build and implement those solutions. Today it offers products in insurance, financial services, manufacturing, logistics and retail — a list that is likely to get longer and deeper with this latest funding.
One catch about Element AI is that the company has not been very forthcoming about its customer list up to now — those that have been named as partners include Bank of Canada and Gore Mutual, but there is a very notable absence of case studies or reference customers on its site.
However, from what we understand, this is more a by-product of the companies (both Element AI and its customers) wishing to keep involvement quiet for competitive and other reasons; and in fact there are apparently a number of large enterprises that are building and deploying long-term products working with the startup. We have also been told big investors in this latest round (specifically McKinsey) are bringing in customers of their own by way of this deal, expanding that list. Total bookings are a “significant double digit million number” at the moment.
“With this transaction, we are investing capital and expertise alongside partners who are ideally suited to transform Element AI into a company with a commercial focus that anticipates and creates AI products to address clients’ needs,” said Charles Émond, EVP and head of Québec Investments and Global Strategic Planning at la Caisse, in a statement. CDPQ launched an AI Fund this year and this is coming out of that fund to help export more of the AI tech and IP that has been incubated and developed in the region. “Through this fund, la Caisse wants to actively contribute to build and strengthen Québec’s global presence in artificial intelligence.”
Management consultancies like McKinsey would be obvious competitors to Element AI, but in fact, they are turning out to be customer pipelines, as traditional system integrators also often lack the deeper expertise needed in newer areas of computing. (And that’s even considering that McKinsey itself has been investing in building its own capabilities, for example through its acquisition of the analytics firm QuantumBlack.
“For McKinsey, this investment is all about helping our clients to further unlock the potential of AI and Machine Learning to improve business performance,” said Patrick Lahaie, senior partner and Montreal managing partner for McKinsey & Company, in a statement. “We look forward to collaborating closely with the talented team at Element AI in Canada and globally in our shared objective to turn cutting-edge thinking and technology into AI assets which will transform a wide range of industries and sectors. This investment fits into McKinsey’s long-term AI strategy, including the 2015 acquisition of QuantumBlack, which has grown substantially since then and will spearhead the collaboration with Element AI on behalf of our Firm.”
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Megvii, the Chinese startup unicorn known for facial recognition tech, files to go public in Hong Kong
Megvii Technology, the Beijing-based artificial intelligence startup known in particular for its facial recognition brand Face++, has filed for a public listing on the Hong Kong stock exchange.
Its prospectus did not disclose share pricing or when the IPO will take place, but Reuters reports that the company plans to raise between $500 million and $1 billion and list in the fourth quarter of this year. Megvii’s investors include Alibaba, Ant Financial and the Bank of China. Its last funding round was a Series D of $750 million announced in May that reportedly brought its valuation to more than $4 billion.
Founded by three Tsinghua University graduates in 2011, Megvii is among China’s leading AI startups, with its peers (and rivals) including SenseTime and Yitu. Its clients include Alibaba, Ant Financial, Lenovo, China Mobile and Chinese government entities.
The company’s decision to list in Hong Kong comes against the backdrop of an economic recession and political unrest, including pro-democracy demonstrations, factors that have contributed to a slump in the value of the benchmark Hang Seng index. Last month, Alibaba reportedly decided to postpone its Hong Kong listing until the political and economic environment becomes more favorable.
Megvii’s prospectus discloses both rapid growth in revenue and widening losses, which the company attributes to changes in the fair value of its preferred shares and investment in research and development. Its revenue grew from 67.8 million RMB in 2016 to 1.42 billion RMB in 2018, representing a compound annual growth rate of about 359%. In the first six months of 2019, it made 948.9 million RMB. Between 2016 and 2018, however, its losses increased from 342.8 million RMB to 3.35 billion RMB, and in the first half of this year, Megvii has already lost 5.2 billion RMB.
Investment risks listed by Megvii include high R&D costs, the U.S.-China trade war and negative publicity over facial recognition technology. Earlier this year, Human Rights Watch published a report that linked Face++ to a mobile app used by Chinese police and officials for mass surveillance of Uighurs in Xinjiang, but it later added a correction that said Megvii’s technology had not been used in the app. Megvii’s prospectus alluded to the report, saying that in spite of the correction, the report “still caused significant damages to our reputation which are difficult to completely mitigate.”
The company also said that despite internal measures to prevent misuse of Megvii’s tech, it cannot assure investors that those measures “will always be effective,” and that AI technology’s risks and challenges include “misuse by third parties for inappropriate purposes, for purposes breaching public confidence or even violate applicable laws and regulations in China and other jurisdictions, bias applications or mass surveillance, that could affect user perception, public opinions and their adoption.”
From a macroeconomic perspective, Megvii’s investment risks include the restrictions and tariffs placed on Chinese exports to the U.S. as part of the ongoing trade war. It also cited reports that Megvii is among the Chinese tech companies the U.S. government may add to trade blacklists. “Although we are not aware of, nor have we received any notification, that we have been added as a target of any such restrictions as of the date this Document, the existence of such media reports itself has already damaged our reputation and diverted our management’s attention,” the prospectus said. “Whether or not we will be included as a target for economic and trade restrictions is beyond our control.”
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Lucidworks raises $100M to expand in AI-powered search-as-a-service for organizations
If the sheer amount of information that we can tap into using the internet has made the world our oyster, then the huge success of Google is a testament to how lucrative search can be in helping to light the way through that data maze.
Now, in a sign of the times, a startup called Lucidworks, which has built an AI-based engine to help individual organizations provide personalised search services for their own users, has raised $100 million in funding. Lucidworks believes its approach can produce better and more relevant results than other search services in the market, and it plans to use the funding for its next stage of growth to become, in the words of CEO Will Hayes, “the world’s next important platform.”
The funding is coming from PE firm Francisco Partners and TPG Sixth Street Partners. Existing investors in the company include Top Tier Capital Partners, Shasta Ventures, Granite Ventures and Allegis Cyber.
Lucidworks has raised around $200 million in funding to date, and while it is not disclosing the valuation, the company says it has been doubling revenues each year for the last three and counts companies like Reddit, Red Hat, REI and the U.S. Census among some 400 others of its customers using its flagship product, Fusion. PitchBook notes that its last round in 2018 was at a modest $135 million, and my guess is that is up by quite some way.
The idea of building a business on search, of course, is not at all new, and Lucidworks works is in a very crowded field. The likes of Amazon, Google and Microsoft have built entire empires on search — in Google’s and Microsoft’s case, by selling ads against those search results; in Amazon’s case, by generating sales of items in the search results — and they have subsequently productised that technology, selling it as a service to others.
Alongside that are companies that have been building search-as-a-service from the ground up — like Elastic, Sumo Logic and Splunk (whose founding team, coincidentally, went on to found Lucidworks…) — both for back-office processes as well as for services that are customer-facing.
In an interview, Hayes said that what sets Lucidworks apart is how it uses machine learning and other AI processes to personalise those results after “sorting through mountains of data,” to provide enterprise information to knowledge workers, shopping results on an e-commerce site to consumers, data to wealth managers or whatever it is that is being sought.
Take the case of a shopping experience, he said by way of explanation. “If I’m on REI to buy hiking shoes, I don’t just want to see the highest-rated hiking shoes, or the most expensive,” he said.
The idea is that Lucidworks builds algorithms that bring in other data sources — your past shopping patterns, your location, what kind of walking you might be doing, what other people like you have purchased — to produce a more focused list of products that you are more likely to buy.
“Amazon has no taste,” he concluded, a little playfully.
Today, around half of Lucidworks’ business comes from digital commerce and digital content — searches of the kind described above for products, or monitoring customer search queries sites like Red Hat or Reddit — and half comes from knowledge worker applications inside organizations.
The plan will be to continue that proportion, while also adding other kinds of features — more natural language processing and more semantic search features — to expand the kinds of queries that can be made, and also cues that Fusion can use to produce results.
Interestingly, Hayes said that while it’s come up a number of times, Lucidworks doesn’t see itself ever going head-to-head with a company like Google or Amazon in providing a first-party search platform of its own. Indeed, that may be an area that has, for the time being at least, already been played out. Or it may be that we have turned to a time when walled gardens — or at least more targeted and curated experiences — are coming into their own.
“We still see a lot of runway in this market,” said Jonathan Murphy of Francisco Partners. “We were very attracted to the idea of next-generation search, on one hand serving internet users facing the pain of the broader internet, and on the other enterprises as an enterprise software product.”
Lucidworks, it seems, has also entertained acquisition approaches, although Hayes declined to get specific about that. The longer-term goal, he said, “is to build something special that will stay here for a long time. The likelihood of needing that to be a public company is very high, but we will do what we think is best for the company and investors in the long run. But our focus and intention is to continue growing.”
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VMware acquires ML acceleration startup Bitfusion
VMware today announced that it has acquired Bitfusion, a former participant in our Startup Battlefield competition. Bitfusion was one of the earliest companies to help businesses accelerate their complex computing workloads on GPUs, FPGAs and ASICs. In its earliest iteration, over four years ago, the company’s focus was less on AI and machine learning and more on other areas of high-performance computing, but, unsurprisingly, that shifted as the interested in AI and ML increased in recent years.
VMware will use Bitfusion’s technology, which is vendor- and hardware-agnostic, to bring similar capabilities to its customers. Specifically, it plans to integrate Bitfusion into its vSphere platform.
“Once closed, the acquisition of Bitfusion will bolster VMware’s strategy of supporting AI- and ML-based workloads by virtualizing hardware accelerators,” writes Krish Prasad, senior vice president and general manager of VMware’s Cloud Platform Business Unit. “Multi-vendor hardware accelerators and the ecosystem around them are key components for delivering modern applications. These accelerators can be used regardless of location in the environment – on-premises and/or in the cloud.”
Prasad also notes that to get the most out of hardware accelerators like GPUs, most enterprises deploy them on bare metal. VMware, however, argues that this leads to poor utilization and poor efficiencies (as it would, of course, given that it is in the business of virtualization). “This provides a perfect opportunity to virtualize them—providing increased sharing of resources and lowering costs,” writes Prasad.
The two companies did not disclose the price of the acquisition. Bitfusion had raised $5 million in 2017 and a smaller, strategic investment from Samsung Ventures in 2018.
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RealityEngines.AI raises $5.25M seed round to make ML easier for enterprises
RealityEngines.AI, a research startup that wants to help enterprises make better use of AI, even when they only have incomplete data, today announced that it has raised a $5.25 million seed funding round. The round was led by former Google CEO and Chairman Eric Schmidt and Google founding board member Ram Shriram. Khosla Ventures, Paul Buchheit, Deepchand Nishar, Elad Gil, Keval Desai, Don Burnette and others also participated in this round.
The fact that the service was able to raise from this rather prominent group of investors clearly shows that its overall thesis resonates. The company, which doesn’t have a product yet, tells me that it specifically wants to help enterprises make better use of the smaller and noisier data sets they have and provide them with state-of-the-art machine learning and AI systems that they can quickly take into production. It also aims to provide its customers with systems that can explain their predictions and are free of various forms of bias, something that’s hard to do when the system is essentially a black box.
As RealityEngines CEO Bindu Reddy, who was previously the head of products for Google Apps, told me, the company plans to use the funding to build out its research and development team. The company, after all, is tackling some of the most fundamental and hardest problems in machine learning right now — and that costs money. Some, like working with smaller data sets, already have some available solutions like generative adversarial networks that can augment existing data sets and that RealityEngines expects to innovate on.
Reddy is also betting on reinforcement learning as one of the core machine learning techniques for the platform.
Once it has its product in place, the plan is to make it available as a pay-as-you-go managed service that will make machine learning more accessible to large enterprise, but also to small and medium businesses, which also increasingly need access to these tools to remain competitive.
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The team behind Baidu’s first smart speaker is now using AI to make films
The HBO sci-fi blockbuster Westworld has been an inspiring look into what humanlike robots can do for us in the meatspace. While current technologies are not quite advanced enough to make Westworld a reality, startups are attempting to replicate the sort of human-robot interaction it presents in virtual space.
Rct studio, which just graduated from Y Combinator and ranked among TechCrunch’s nine favorite picks from the batch, is one of them. The “Westworld” in the TV series, a far-future theme park staffed by highly convincing androids, lets visitors live out their heroic and sadistic fantasies free of consequences.
There are a few reasons why rct studio, which is keeping mum about the meaning of its deliberately lower-cased name for later revelation, is going for the computer-generated world. Besides the technical challenge, playing a fictional universe out virtually does away the geographic constraint. The Westworld experience, in contrast, happens within a confined, meticulously built park.
“Westworld is built in a physical world. I think in this age and time, that’s not what we want to get into,” Xinjie Ma, who heads up marketing for rct, told TechCrunch. “Doing it in the physical environment is too hard, but we can build a virtual world that’s completely under control.”
Rct studio wants to build the Westworld experience in virtual worlds. / Image: rct studio
The startup appears suitable to undertake the task. The eight-people team is led by Cheng Lyu, the 29-year-old entrepreneur who goes by Jesse and helped Baidu build up its smart speaker unit from scratch after the Chinese search giant acquired his voice startup Raven in 2017. Along with several of Raven’s core members, Lyu left Baidu in 2018 to start rct.
“We appreciate a lot the support and opportunities given by Baidu and during the years we have grown up dramatically,” said Ma, who previously oversaw marketing at Raven.
Let AI write the script
Immersive films, or games, depending on how one wants to classify the emerging field, are already available with pre-written scripts for users to pick from. Rct wants to take the experience to the next level by recruiting artificial intelligence for screenwriting.
At the center of the project is the company’s proprietary engine, Morpheus. Rct feeds it mountains of data based on human-written storylines so the characters it powers know how to adapt to situations in real time. When the codes are sophisticated enough, rct hopes the engine can self-learn and formulate its own ideas.
“It takes an enormous amount of time and effort for humans to come up with a story logic. With machines, we can quickly produce an infinite number of narrative choices,” said Ma.
To venture through rct’s immersive worlds, users wear a virtual reality headset and control their simulated self via voice. The choice of audio came as a natural step given the team’s experience with natural language processing, but the startup also welcomes the chance to develop new devices for more lifelike journeys.
“It’s sort of like how the film Ready Player One built its own gadgets for the virtual world. Or Apple, which designs its own devices to carry out superior software experience,” explained Ma.
On the creative front, rct believes Morpheus could be a productivity tool for filmmakers as it can take a story arc and dissect it into a decision-making tree within seconds. The engine can also render text to 3D images, so when a filmmaker inputs the text “the man throws the cup to the desk behind the sofa,” the computer can instantly produce the corresponding animation.
Path to monetization
Investors are buying into rct’s offering. The startup is about to close its Series A funding round just months after banking seed money from Y Combinator and Chinese venture capital firm Skysaga, the startup told TechCrunch.
The company has a few imminent tasks before achieving its Westworld dream. For one, it needs a lot of technical talent to train Morpheus with screenplay data. No one on the team had experience in filmmaking, so it’s on the lookout for a creative head who appreciates AI’s application in films.
Rct studio’s software takes a story arc and dissects it into a decision-making tree within seconds. / Image: rct studio
“Not all filmmakers we approach like what we do, which is understandable because it’s a very mature industry, while others get excited about tech’s possibility,” said Ma.
The startup’s entry into the fictional world was less about a passion for films than an imperative to shake up a traditional space with AI. Smart speakers were its first foray, but making changes to tangible objects that people are already accustomed to proved challenging. There has been some interest in voice-controlled speakers, but they are far from achieving ubiquity. Then movies crossed the team’s mind.
“There are two main routes to make use of AI. One is to target a vertical sector, like cars and speakers, but these things have physical constraints. The other application, like Alpha Go, largely exists in the lab. We wanted something that’s both free of physical limitation and holds commercial potential.”
The Beijing and Los Angeles-based startup isn’t content with just making the software. Eventually, it wants to release its own films. The company has inked a long-term partnership with Future Affairs Administration, a Chinese sci-fi publisher representing about 200 writers, including the Hugo award-winning Cixin Liu. The pair is expected to start co-producing interactive films within a year.
Rct’s path is reminiscent of a giant that precedes it: Pixar Animation Studios . The Chinese company didn’t exactly look to the California-based studio for inspiration, but the analog was a useful shortcut to pitch to investors.
“A confident company doesn’t really draw parallels with others, but we do share similarities to Pixar, which also started as a tech company, publishes its own films, and has built its own engine,” said Ma. “A lot of studios are asking how much we price our engine at, but we are targeting the consumer market. Making our own films carry so many more possibilities than simply selling a piece of software.”
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CoParenter helps divorced parents settle disputes using AI and human mediation
A former judge and family law educator has teamed up with tech entrepreneurs to launch an app they hope will help divorced parents better manage their co-parenting disputes, communications, shared calendar and other decisions within a single platform. The app, called coParenter, aims to be more comprehensive than its competitors, while also leveraging a combination of AI technology and on-demand human interaction to help co-parents navigate high-conflict situations.
The idea for coParenter emerged from co-founder Hon. Sherrill A. Ellsworth’s personal experience and entrepreneur Jonathan Verk, who had been through a divorce himself.
Ellsworth had been a presiding judge of the Superior Court in Riverside County, California for 20 years and a family law educator for 10. During this time, she saw firsthand how families were destroyed by today’s legal system.
“I witnessed countless families torn apart as they slogged through the family law system. I saw how families would battle over the simplest of disagreements like where their child will go to school, what doctor they should see and what their diet should be — all matters that belong at home, not in a courtroom,” she says.
Ellsworth also notes that 80 percent of the disagreements presented in the courtroom didn’t even require legal intervention — but most of the cases she presided over involved parents asking the judge to make the co-parenting decision.
As she came to the end of her career, she began to realize the legal system just wasn’t built for these sorts of situations.
She then met Jonathan Verk, previously EVP Strategic Partnerships at Shazam and now coParenter CEO. Verk had just divorced and had an idea about how technology could help make the co-parenting process easier. He already had on board his longtime friend and serial entrepreneur Eric Weiss, now COO, to help build the system. But he needed someone with legal expertise.
That’s how coParenter was born.
The app, also built by CTO Niels Hansen, today exists alongside a whole host of other tools built for different aspects of the co-parenting process.
That includes those apps designed to document communication, like OurFamilyWizard, Talking Parents, AppClose and Divvito Messenger; those for sharing calendars, like Custody Connection, Custody X Exchange and Alimentor; and even those that offer a combination of features like WeParent, 2houses, SmartCoparent and Fayr, among others.
But the team at coParenter argues that their app covers all aspects of co-parenting, including communication, documentation, calendar and schedule sharing, location-based tools for pickup and drop-off logging, expense tracking and reimbursements, schedule change requests, tools for making decisions on day-to-day parenting choices like haircuts, diet, allowance, use of media, etc. and more.
Notably, coParenter also offers a “solo mode” — meaning you can use the app even if the other co-parent refuses to do the same. This is a key feature that many rival apps lack.
However, the biggest differentiator is how coParenter puts a mediator of sorts in your pocket.
The app begins by using AI, machine learning and sentiment analysis technology to keep conversations civil. The tech will jump in to flag curse words, inflammatory phrases and offensive names to keep a heated conversation from escalating — much like a human mediator would do when trying to calm two warring parties.
When conversations take a bad turn, the app will pop up a warning message that asks the parent if they’re sure they want to use that term, allowing them time to pause and think. (If only social media platforms had built features like this!)
When parents need more assistance, they can opt to use the app instead of turning to lawyers.
The company offers on-demand access to professionals as both monthly ($12.99/mo – 20 credits, or enough for two mediations) or yearly ($119.99/year – 240 credits) subscriptions. Both parents can subscribe for $199.99/year, each receiving 240 credits.
“Comparatively, an average hour with a lawyer costs between $250 and upwards of $500, just to file a single motion,” Ellsworth says.
These professionals are not mediators, but are licensed in their respective fields — typically family law attorneys, therapists, social workers or other retired bench officers with strong conflict resolution backgrounds. Ellsworth oversees the professionals to ensure they have the proper guidance.
All communication between the parent and the professional is considered confidential and not subject to admission as evidence, as the goal is to stay out of the courts. However, all the history and documentation elsewhere in the app can be used in court, if the parents do end up there.
The app has been in beta for nearly a year, and officially launched this January. To date, coParenter claims it has already helped to resolve more than 4,000 disputes and more than 2,000 co-parents have used it for scheduling. Indeed, 81 percent of the disputing parents resolved all their issues in the app, without needing a professional mediator or legal professional, the company says.
CoParenter is available on both iOS and Android.
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Automation Hero picks up $14.5 million led by Atomico
Automation Hero, formerly SalesHero, has secured $14.5 million in new funding led by Atomico, with participation by Baidu Ventures and Cherry Ventures. As part of the deal, Atomico principal Ben Blume will join the company’s board of directors.
The automation startup launched in 2017 as SalesHero, giving sales orgs a simple way to automate back-office processes like filing an expense report or updating the CRM. It does this through an AI assistant called Robin — “Batman and Robin, it worked with the superhero theme, and it’s gender neutral,” co-founder and CEO Stefan Groschupf explained — that can be configured to go through the regular workflow and take care of repetitive tasks.
“We brought computers into the workplace because we believed they could make us more productive,” said Groschupf. “But in many companies, people spend a lot of time entering data and doing painful manual processes to make these machines happy.”
The idea was to give salespeople more time to actually do their job, which is selling to clients. If all the administrative and repetitive “paperwork” is done by a computer, human employees can become more productive and efficient at skilled tasks.
By weaving together click robots, Automation Hero users can build out their own workflows through a no-code interface, tying together a wide variety of both structured and unstructured data sources. Those workflows are then presented in the inbox each morning by Robin, the AI assistant, and are executed as soon as the user gives the go-ahead.
After launch, the team realized that other types of organizations, beyond sales departments, were building out automations. Insurance firms, in particular, were using the software to automate some of the repetitive tasks involved with filing and assessing claims.
This led to today’s rebrand to Automation Hero.
Groschupf said that by automating the process of filling out a single closing form, it saved one insurance firm’s 430 sales reps 18.46 years per year.
Automation Hero has now raised a total of $19 million.
“We’re really excited with Atomico to bring on a great VC and good people,” said Groschupf. “I’ve raised capital before and I’ve worked with some of the more questionable VCs, as it turns out. We’re super-excited we’ve found an investor that really bakes important things, like a diversity policy and a family leave policy, right into the company’s investment agreement.”
Though he didn’t confirm, it’s likely that Groschupf is referring to KPCB, which has run into its fair share of controversy over the past few years and was an investor in Groschupf’s previous startup, Datameer.
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Databricks raises $250M at a $2.75B valuation for its analytics platform
Databricks, the company founded by the original team behind the Apache Spark big data analytics engine, today announced that it has raised a $250 million Series E round led by Andreessen Horowitz. Coatue Management, Green Bay Ventures, Microsoft and NEA, also participated in this round, which brings the company’s total funding to $498.5 million. Microsoft’s involvement here is probably a bit of a surprise, but it’s worth noting that it also worked with Databricks on the launch of Azure Databricks as a first-party service on the platform, something that’s still a rarity in the Azure cloud.
As Databricks also today announced, its annual recurring revenue now exceeds $100 million. The company didn’t share whether it’s cash flow-positive at this point, but Databricks CEO and co-founder Ali Ghodsi shared that the company’s valuation is now $2.75 billion.
Current customers, which the company says number around 2,000, include the likes of Nielsen, Hotels.com, Overstock, Bechtel, Shell and HP.
“What Ali and the Databricks team have built is truly phenomenal,” Green Bay Ventures co-founder Anthony Schiller told me. “Their success is a testament to product innovation at the highest level. Databricks is without question best-in-class and their impact on the industry proves it. We were thrilled to participate in this round.”
While Databricks is obviously known for its contributions to Apache Spark, the company itself monetizes that work by offering its Unified Analytics platform on top of it. This platform allows enterprises to build their data pipelines across data storage systems and prepare data sets for data scientists and engineers. To do this, Databricks offers shared notebooks and tools for building, managing and monitoring data pipelines, and then uses that data to build machine learning models, for example. Indeed, training and deploying these models is one of the company’s focus areas these days, which makes sense, given that this is one of the main use cases for big data, after all.
On top of that, Databricks also offers a fully managed service for hosting all of these tools.
“Databricks is the clear winner in the big data platform race,” said Ben Horowitz, co-founder and general partner at Andreessen Horowitz, in today’s announcement. “In addition, they have created a new category atop their world-beating Apache Spark platform called Unified Analytics that is growing even faster. As a result, we are thrilled to invest in this round.”
Ghodsi told me that Horowitz was also instrumental in getting the company to re-focus on growth. The company was already growing fast, of course, but Horowitz asked him why Databricks wasn’t growing faster. Unsurprisingly, given that it’s an enterprise company, that means aggressively hiring a larger sales force — and that’s costly. Hence the company’s need to raise at this point.
As Ghodsi told me, one of the areas the company wants to focus on is the Asia Pacific region, where overall cloud usage is growing fast. The other area the company is focusing on is support for more verticals like mass media and entertainment, federal agencies and fintech firms, which also comes with its own cost, given that the experts there don’t come cheap.
Ghodsi likes to call this “boring AI,” since it’s not as exciting as self-driving cars. In his view, though, the enterprise companies that don’t start using machine learning now will inevitably be left behind in the long run. “If you don’t get there, there’ll be no place for you in the next 20 years,” he said.
Engineering, of course, will also get a chunk of this new funding, with an emphasis on relatively new products like MLFlow and Delta, two tools Databricks recently developed and that make it easier to manage the life cycle of machine learning models and build the necessary data pipelines to feed them.
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