H20.ai announces $72.5M Series D led by Goldman Sachs

H20.ai‘s mission is to democratize AI by providing a set of tools that frees companies from relying on teams of data scientists. Today it got a bushel of money to help. The company announced a $72.5 million Series D round led by Goldman Sachs and Ping An Global Voyager Fund.

Previous investors Wells Fargo, NVIDIA and Nexus Venture Partners also participated. Under the terms of the deal, Jade Mandel from Goldman Sachs will be joining the H2O.ai Board. Today’s investment brings the total raised to $147 million.

It’s worth noting that Goldman Sachs isn’t just an investor. It’s also a customer. Company CEO and co-founder Sri Ambati says the fact that customers, Wells Fargo and Goldman Sachs, have led the last two rounds is a validation for him and his company. “Customers have risen up from the ranks for two consecutive rounds for us. Last time the Series C was led by Wells Fargo where we were their platform of choice. Today’s round was led by Goldman Sachs, which has been a strong customer for us and strong supporters of our technology,” Ambati told TechCrunch.

The company’s main product, H20 Driverless AI, introduced in 2017, gets its name from the fact it provides a way for people who aren’t AI experts to still take advantage of AI without a team of data scientists. “Driverless AI is automatic machine learning, which brings the power of a world class data scientists in the hands of everyone. lt builds models automatically using machine learning algorithms of every kind,” Ambati explained.

They introduced a new recipe concept today, that provides all of the AI ingredients and instructions for building models for different business requirements. H20.ai’s team of data scientists has created and open sourced 100 recipes for things like credit risk scoring, anomaly detection and property valuation.

The company has been growing since its Series C round in 2017 when it had 70 employees. Today it has 175 and has tripled the number of customers since the prior round, although Ambati didn’t discuss an exact number.  The company has its roots in open source and has 20,000 users of its open source products, according to Ambati.

He didn’t want to discuss valuation and wouldn’t say when the company might go public, saying it’s early days for AI and they are working hard to build a company for the long haul.


By Ron Miller

Ally raises $8M Series A for its OKR solution

OKRs, or Objectives and Key Results, are a popular planning method in Silicon Valley. Like most of those methods that make you fill in some form once every quarter, I’m pretty sure employees find them rather annoying and a waste of their time. Ally wants to change that and make the process more useful. The company today announced that it has raised an $8 million Series A round led by Accel Partners, with participation from Vulcan Capital, Founders Co-op and Lee Fixel. The company, which launched in 2018, previously raised a $3 million seed round.

Ally founder and CEO Vetri Vellore tells me that he learned his management lessons and the value of OKR at his last startup, Chronus. After years of managing large teams at enterprises like Microsoft, he found himself challenged to manage a small team at a startup. “I went and looked for new models of running a business execution. And OKRs were one of those things I stumbled upon. And it worked phenomenally well for us,” Vellore said. That’s where the idea of Ally was born, which Vellore pursued after selling his last startup.

Most companies that adopt this methodology, though, tend to work with spreadsheets and Google Docs. Over time, that simply doesn’t work, especially as companies get larger. Ally, then, is meant to replace these other tools. The service is currently in use at “hundreds” of companies in more than 70 countries, Vellore tells me.

One of its early adopters was Remitly . “We began by using shared documents to align around OKRs at Remitly. When it came time to roll out OKRs to everyone in the company, Ally was by far the best tool we evaluated. OKRs deployed using Ally have helped our teams align around the right goals and have ultimately driven growth,” said Josh Hug, COO of Remitly.

Desktop Team OKRs Screenshot

Vellore tells me that he has seen teams go from annual or bi-annual OKRs to more frequently updated goals, too, which is something that’s easier to do when you have a more accessible tool for it. Nobody wants to use yet another tool, though, so Ally features deep integrations into Slack, with other integrations in the works (something Ally will use this new funding for).

Since adopting OKRs isn’t always easy for companies that previously used other methodologies (or nothing at all), Ally also offers training and consulting services with online and on-site coaching.

Pricing for Ally starts at $7 per month per user for a basic plan, but the company also offers a flat $29 per month plan for teams with up to 10 users, as well as an enterprise plan, which includes some more advanced features and single sign-on integrations.


By Frederic Lardinois

Simon Data hauls in $30M Series C to continue building customer data platform

As businesses use an increasing variety of marketing software solutions, the goal around collecting all of that data is to improve customer experience. Simon Data announced a $30 million Series C round today to help.

The round was led by Polaris Partners . Previous investors .406 Ventures and F-Prime Capital also participated. Today’s investment brings the total raised to $59 million, according to the company.

Jason Davis, co-founder and CEO, says his company is trying to pull together a lot of complex data from a variety of sources, while driving actions to improve customer experience. “It’s about taking the data, and then building complex triggers that target the right customer at the right time,” Davis told TechCrunch. He added, “This can be in the context of any sort of customer transaction, or any sort of interaction with the business.”

Companies tend to use a variety of marketing tools, and Simon Data takes on the job of understanding the data and activities going on in each one. Then based on certain actions — such as, say, an abandoned shopping cart — it delivers a consistent message to the customer, regardless of the source of the data that triggered the action.

They see this ability to pull together data as a customer data platform (CDP). In fact, part of its job is to aggregate data and use it as the basis of other activities. In this case, it involves activating actions you define based on what you know about the customer at any given moment in the process.

As the company collects this data, it also sees an opportunity to use machine learning to create more automated and complex types of interactions. “There are a tremendous number of super complex problems we have to solve. Those include core platform or infrastructure, and we also have a tremendous opportunity in front of us on the predictive and data science side as well,” Davis said. He said that is one of the areas where they will put today’s money to work.

The company, which launched in 2014, is based in NYC. The company currently has 87 employees in total, and that number is expected to grow with today’s announcement. Customers include Equinox, Venmo and WeWork. The company’s most recent funding round was a $20 million in July 2018.


By Ron Miller

Incorta raises $30M Series C for ETL-free data processing solution

Incorta, a startup founded by former Oracle executives who want to change the way we process large amounts data, announced a $30 million Series C today led by Sorenson Capital.

Other investors participating in the round included GV (formerly Google Ventures), Kleiner Perkins, M12 (formerly Microsoft Ventures), Telstra Ventures and Ron Wohl. Today’s investment brings the total raised to $75 million, according to the company.

Incorta CEO and co-founder Osama Elkady says he and his co-founders were compelled to start Inccorta because they saw so many companies spending big bucks for data projects that were doomed to fail. “The reason that drove me and three other guys to leave Oracle and start Incorta is because we found out with all the investment that companies were making around data warehousing and implementing advanced projects, very few of these projects succeeded,” Elkady told TechCrunch.

A typical data project of involves ETL (extract, transform, load). It’s a process that takes data out of one database, changes the data to make it compatible with the target database and adds it to the target database.

It takes time to do all of that, and Incorta is trying to give access to the data much faster by stripping out this step. Elkady says that this allows customers to make use of the data much more quickly, claiming they are reducing the process from one that took hours to one that takes just seconds. That kind of performance enhancement is garnering attention.

Rob Rueckert, managing director for lead investor Sorenson Capital sees a company that’s innovating in a mature space. “Incorta is poised to upend the data warehousing market with innovative technology that will end 30 years of archaic and slow data warehouse infrastructure,” he said in a statement.

The company says revenue is growing by leaps and bounds, reporting 284% year over year growth (although they did not share specific numbers). Customers include Starbucks, Shutterfly and Broadcom.

The startup, which launched in 2013, currently has 250 employees with developers in Egypt and main operations in San Mateo, California. They recently also added offices in Chicago, Dubai and Bangalore.


By Ron Miller

Rimeto lands $10M Series A to modernize the corporate directory

The notion of the corporate directory has been around for many years, but in a time of more frequent turnover and shifting responsibilities, the founders of Rimeto, a 3 year old San Francisco startup, wanted to update it to reflect those changes.

Today, the company announced a $10 million Series A investment from USVP, Bow Capital, Floodgate and Ray Dalio, founder of Bridgewater Associates.

Co-founder Ted Zagat says that the founders observed shifting workplace demographics and changes in the way people work. They believed it required a better to way to locate people inside large organizations, which typically used homegrown methods or relied on Outlook or other corporate email systems.

“On one hand, we have people being asked to work much more collaboratively and cross-functionally. On the other, is an increasingly fragmented workplace. Employees really need help to be able to understand each other and work together effectively. That’s a real challenge for them,” Zagat explained.

Rimeto has developed a richer directory by sitting between various corporate systems like HR, CRM and other tools that contain additional details about the employee. It of course includes a name, title, email and phone like the basic corporate system, but it goes beyond that to find areas of expertise, projects the person is working on and other details that can help you find the right person when you’re searching the directory.

Rimeto product version 1 1

Rimeto directory on mobile and web. Screenshot: Rimeto

Zagat says that by connecting to these various corporate systems and layering on a quality search tool with a variety of filters to narrow the search, it can help employees connect to others inside an organization more easily, something that is often difficult to do in large companies.

The tool can be accessed via web or mobile app, or incorporated into a company intranet. It could also be accessed from a tool like Slack or Microsoft Teams.

The three founders — Zagat, Neville Bowers and Maxwell Hayman — all previously worked at Facebook. Unlike a lot of early stage startups, the company has paying customers (although it won’t share exactly how many) and reports that it’s cash-flow positive. Up to this point, the three founders had boot-strapped the company, but they wanted to go out and raise some capital to begin to expand more rapidly.


By Ron Miller

Salesforce is acquiring ClickSoftware for $1.35B

Another day, another Salesforce acquisition. Just days after closing the hefty $15.7 billion Tableau deal, the company opened its wallet again, this time announcing it has bought field service software company ClickSoftware for a tidy $1.35 billion.

This one is designed to beef up the company’s field service offering under the Service Cloud umbrella. In its June earnings report, the company reported that Service Cloud crossed the $1 billion revenue threshold for the first time. This acquisition is designed to keep those numbers growing.

“Our acquisition of ClickSoftware will not only accelerate the growth of Service Cloud, but drive further innovation with Field Service Lightning to better meet the needs of our customers,” Bill Patterson, EVP and GM of Salesforce Service Cloud said in a statement announcing the deal.

ClickSoftware is actually older than Salesforce having been founded in 1997. The company went public in 2000, and remained listed until it went private again in 2015 in a deal with private equity company Francisco Partners, which bought it for $438 million. Francisco did alright for itself, holding onto the company for four years before more than doubling its money.

The deal is expected to close in the Fall and is subject to the normal regulatory approval process.


By Ron Miller

With MapR fire sale, Hadoop’s promise has fallen on hard times

If you go back about a decade, Hadoop was hot and getting hotter. It was a platform for processing big data, just as big data was emerging from the domain of a few web-scale companies to one where every company was suddenly concerned about processing huge amounts of data. The future was bright, an open source project with a bunch of startups emerging to fulfill that big data promise in the enterprise.

Three companies in particular emerged out of that early scrum — Cloudera, Hortonworks and MapR — and between them raised more than $1.5 billion. The lion’s share of that went to Cloudera in one massive chunk when Intel Capital invested a whopping $740 million in the company. But times have changed.

2018 china ipos

Via TechCrunch, Crunchbase, Infogram

Falling hard

Just yesterday, HPE bought the assets of MapR, a company that had raised $280 million. The deal was pegged at under $50 million, according to multiple reports. That’s not what you call a healthy return on investment.


By Ron Miller

Rookout lands $8M Series A to expand debugging platform

Rookout, a startup that provides debugging across a variety of environments including serverless and containers, announced an $8 million Series A investment today. It plans to use the money to expand beyond its debugging roots.

The round was led by Cisco Investments along with existing investors TLV Partners and Emerge. Nat Friedman, CEO of GitHub; John Kodumal, CTO and co-founder of LaunchDarkly, and Raymond Colletti, VP of revenue at Codecov also participated.

Rookout from day one has been working to provide production debugging and collection capabilities to all platforms,” Or Weis, co-founder and CEO of Rookout told TechCrunch. That has included serverless like AWS Lambda, containers and Kubernetes and Platform as a Service like Google App Engine and Elastic Beanstalk

The company is also giving visibility into platforms that are sometimes hard to observe because of the ephemeral nature of the technology, and that go beyond its pure debugging capabilities. “In the last year, we’ve discovered that our customers are finding completely new ways to use Rookout’s code-level data collection capabilities and that we need to accommodate, support and enhance the many varied uses of code-level observability and pipelining,” Weiss said in a statement.

It was particularly telling that a company like Cisco was deeply involved in the round. Rob Salvagno, vice president of Cisco Global Corporate Development and Cisco Investments, likes the developer focus of the company.

“Developers have become key influencers of enterprise IT spend. By collecting data on-demand without re-deploying, Rookout created a Developer-centric software, which short-circuits complexities in the production debugging, increases Developer efficiency and reduces the friction which exists between IT Ops and Developers,” Salvagno said in a statement.

Rookout, which launched in 2017, has offices in San Francisco and Tel Aviv with a total of 20 employees so far. It has raised over $12 million.


By Ron Miller

Cockroach Labs announces $55M Series C to battle industry giants

Cockroach Labs, makers of CockroachDB, sits in a tough position in the database market. On one side, it has traditional database vendors like Oracle, and on the other there’s AWS and its family of databases. It takes some good technology and serious dollars to compete with those companies. Cockroach took care of the latter with a $55 million Series C round today.

The round was led by Altimeter Capital and Tiger Global along with existing investor GV. Other existing investors including Benchmark, Index Ventures, Redpoint Ventures, FirstMark Capital and Work-Bench also participated. Today’s investment brings the total raised to over $110 million, according to the company.

Spencer Kimball, co-founder and CEO, says the company is building a modern database to compete with these industry giants. “CockroachDB is architected from the ground up as a cloud native database. Fundamentally, what that means is that it’s distributed, not just across nodes in a single data center, which is really table stakes as the database gets bigger, but also across data centers to be resilient. It’s also distributed potentially across the planet in order to give a global customer base what feels like a local experience to keep the data near them,” Kimball explained.

At the same time, even while it has a cloud product hosted on AWS, it also competes with several AWS database products including Amazon Aurora, Redshift and DynamoDB. Much like MongoDB, which changed its open source licensing structure last year, Cockroach did as well, for many of the same reasons. They both believed bigger players were taking advantage of the open source nature of their products to undermine their markets.

“If you’re trying to build a business around an open source product, you have to be careful that a much bigger player doesn’t come along and extract too much of the value out of the open source product that you’ve been building and maintaining,” Kimball explained.

As the company deals with all of these competitive pressures, it takes a fair bit of money to continue building a piece of technology to beat the competition, while going up against much deeper-pocketed rivals. So far the company has been doing well with Q1 revenue this year doubling all of last year. Kimball indicated that Q2 could double Q1, but he wants to keep that going, and that takes money.

“We need to accelerate that sales momentum and that’s usually what the Series C is about. Fundamentally, we have, I think, the most advanced capabilities in the market right now. Certainly we do if you look at the differentiator around just global capability. We nevertheless are competing with Oracle on one side, and Amazon on the other side. So a lot of this money is going towards product development too,” he said.

Cockroach Labs was founded in 2015, and is based in New York City.


By Ron Miller

Dasha AI is calling so you don’t have to

While you’d be hard pressed to find any startup not brimming with confidence over the disruptive idea they’re chasing, it’s not often you come across a young company as calmly convinced it’s engineering the future as Dasha AI.

The team is building a platform for designing human-like voice interactions to automate business processes. Put simply, it’s using AI to make machine voices a whole lot less robotic.

“What we definitely know is this will definitely happen,” says CEO and co-founder Vladislav Chernyshov. “Sooner or later the conversational AI/voice AI will replace people everywhere where the technology will allow. And it’s better for us to be the first mover than the last in this field.”

“In 2018 in the US alone there were 30 million people doing some kind of repetitive tasks over the phone. We can automate these jobs now or we are going to be able to automate it in two years,” he goes on. “If you multiple it with Europe and the massive call centers in India, Pakistan and the Philippines you will probably have something like close to 120M people worldwide… and they are all subject for disruption, potentially.”

The New York based startup has been operating in relative stealth up to now. But it’s breaking cover to talk to TechCrunch — announcing a $2M seed round, led by RTP Ventures and RTP Global: An early stage investor that’s backed the likes of Datadog and RingCentral. RTP’s venture arm, also based in NY, writes on its website that it prefers engineer-founded companies — that “solve big problems with technology”. “We like technology, not gimmicks,” the fund warns with added emphasis.

Dasha’s core tech right now includes what Chernyshov describes as “a human-level, voice-first conversation modelling engine”; a hybrid text-to-speech engine which he says enables it to model speech disfluencies (aka, the ums and ahs, pitch changes etc that characterize human chatter); plus “a fast and accurate” real-time voice activity detection algorithm which detects speech in under 100 milliseconds, meaning the AI can turn-take and handle interruptions in the conversation flow. The platform can also detect a caller’s gender — a feature that can be useful for healthcare use-cases, for example.

Another component Chernyshov flags is “an end-to-end pipeline for semi-supervised learning” — so it can retrain the models in real time “and fix mistakes as they go” — until Dasha hits the claimed “human-level” conversational capability for each business process niche. (To be clear, the AI cannot adapt its speech to an interlocutor in real-time — as human speakers naturally shift their accents closer to bridge any dialect gap — but Chernyshov suggests it’s on the roadmap.)

“For instance, we can start with 70% correct conversations and then gradually improve the model up to say 95% of correct conversations,” he says of the learning element, though he admits there are a lot of variables that can impact error rates — not least the call environment itself. Even cutting edge AI is going to struggle with a bad line.

The platform also has an open API so customers can plug the conversation AI into their existing systems — be it telephony, Salesforce software or a developer environment, such as Microsoft Visual Studio.

Currently they’re focused on English, though Chernyshov says the architecture is “basically language agnostic” — but does requires “a big amount of data”.

The next step will be to open up the dev platform to enterprise customers, beyond the initial 20 beta testers, which include companies in the banking, healthcare and insurance sectors — with a release slated for later this year or Q1 2020.

Test use-cases so far include banks using the conversation engine for brand loyalty management to run customer satisfaction surveys that can turnaround negative feedback by fast-tracking a response to a bad rating — by providing (human) customer support agents with an automated categorization of the complaint so they can follow up more quickly. “This usually leads to a wow effect,” says Chernyshov.

Ultimately, he believes there will be two or three major AI platforms globally providing businesses with an automated, customizable conversational layer — sweeping away the patchwork of chatbots currently filling in the gap. And of course Dasha intends their ‘Digital Assistant Super Human Alike’ to be one of those few.

“There is clearly no platform [yet],” he says. “Five years from now this will sound very weird that all companies now are trying to build something. Because in five years it will be obvious — why do you need all this stuff? Just take Dasha and build what you want.”

“This reminds me of the situation in the 1980s when it was obvious that the personal computers are here to stay because they give you an unfair competitive advantage,” he continues. “All large enterprise customers all over the world… were building their own operating systems, they were writing software from scratch, constantly reinventing the wheel just in order to be able to create this spreadsheet for their accountants.

“And then Microsoft with MS-DOS came in… and everything else is history.”

That’s not all they’re building, either. Dasha’s seed financing will be put towards launching a consumer-facing product atop its b2b platform to automate the screening of recorded message robocalls. So, basically, they’re building a robot assistant that can talk to — and put off — other machines on humans’ behalf.

Which does kind of suggest the AI-fuelled future will entail an awful lot of robots talking to each other… 🤖🤖🤖

Chernyshov says this b2c call screening app will most likely be free. But then if your core tech looks set to massively accelerate a non-human caller phenomenon that many consumers already see as a terrible plague on their time and mind then providing free relief — in the form of a counter AI — seems the very least you should do.

Not that Dasha can be accused of causing the robocaller plague, of course. Recorded messages hooked up to call systems have been spamming people with unsolicited calls for far longer than the startup has existed.

Dasha’s PR notes Americans were hit with 26.3BN robocalls in 2018 alone — up “a whopping” 46% on 2017.

Its conversation engine, meanwhile, has only made some 3M calls to date, clocking its first call with a human in January 2017. But the goal from here on in is to scale fast. “We plan to aggressively grow the company and the technology so we can continue to provide the best voice conversational AI to a market which we estimate to exceed $30BN worldwide,” runs a line from its PR.

After the developer platform launch, Chernyshov says the next step will be to open up access to business process owners by letting them automate existing call workflows without needing to be able to code (they’ll just need an analytic grasp of the process, he says).

Later — pegged for 2022 on the current roadmap — will be the launch of “the platform with zero learning curve”, as he puts it. “You will teach Dasha new models just like typing in a natural language and teaching it like you can teach any new team member on your team,” he explains. “Adding a new case will actually look like a word editor — when you’re just describing how you want this AI to work.”

His prediction is that a majority — circa 60% — of all major cases that business face — “like dispatching, like probably upsales, cross sales, some kind of support etc, all those cases” — will be able to be automated “just like typing in a natural language”.

So if Dasha’s AI-fuelled vision of voice-based business process automation come to fruition then humans getting orders of magnitude more calls from machines looks inevitable — as machine learning supercharges artificial speech by making it sound slicker, act smarter and seem, well, almost human.

But perhaps a savvier generation of voice AIs will also help manage the ‘robocaller’ plague by offering advanced call screening? And as non-human voice tech marches on from dumb recorded messages to chatbot-style AIs running on scripted rails to — as Dasha pitches it — fully responsive, emoting, even emotion-sensitive conversation engines that can slip right under the human radar maybe the robocaller problem will eat itself? I mean, if you didn’t even realize you were talking to a robot how are you going to get annoyed about it?

Dasha claims 96.3% of the people who talk to its AI “think it’s human”, though it’s not clear what sample size the claim is based on. (To my ear there are definite ‘tells’ in the current demos on its website. But in a cold-call scenario it’s not hard to imagine the AI passing, if someone’s not paying much attention.)

The alternative scenario, in a future infested with unsolicited machine calls, is that all smartphone OSes add kill switches, such as the one in iOS 13 — which lets people silence calls from unknown numbers.

And/or more humans simply never pick up phone calls unless they know who’s on the end of the line.

So it’s really doubly savvy of Dasha to create an AI capable of managing robot calls — meaning it’s building its own fallback — a piece of software willing to chat to its AI in future, even if actual humans refuse.

Dasha’s robocall screener app, which is slated for release in early 2020, will also be spammer-agnostic — in that it’ll be able to handle and divert human salespeople too, as well as robots. After all, a spammer is a spammer.

“Probably it is the time for somebody to step in and ‘don’t be evil’,” says Chernyshov, echoing Google’s old motto, albeit perhaps not entirely reassuringly given the phrase’s lapsed history — as we talk about the team’s approach to ecosystem development and how machine-to-machine chat might overtake human voice calls.

“At some point in the future we will be talking to various robots much more than we probably talk to each other — because you will have some kind of human-like robots at your house,” he predicts. “Your doctor, gardener, warehouse worker, they all will be robots at some point.”

The logic at work here is that if resistance to an AI-powered Cambrian Explosion of machine speech is futile, it’s better to be at the cutting edge, building the most human-like robots — and making the robots at least sound like they care.

Dasha’s conversational quirks certainly can’t be called a gimmick. Even if the team’s close attention to mimicking the vocal flourishes of human speech — the disfluencies, the ums and ahs, the pitch and tonal changes for emphasis and emotion — might seem so at first airing.

In one of the demos on its website you can hear a clip of a very chipper-sounding male voice, who identifies himself as “John from Acme Dental”, taking an appointment call from a female (human), and smoothly dealing with multiple interruptions and time/date changes as she changes her mind. Before, finally, dealing with a flat cancelation.

A human receptionist might well have got mad that the caller essentially just wasted their time. Not John, though. Oh no. He ends the call as cheerily as he began, signing off with an emphatic: “Thank you! And have a really nice day. Bye!”

If the ultimate goal is Turing Test levels of realism in artificial speech — i.e. a conversation engine so human-like it can pass as human to a human ear — you do have to be able to reproduce, with precision timing, the verbal baggage that’s wrapped around everything humans say to each other.

This tonal layer does essential emotional labor in the business of communication, shading and highlighting words in a way that can adapt or even entirely transform their meaning. It’s an integral part of how we communicate. And thus a common stumbling block for robots.

So if the mission is to power a revolution in artificial speech that humans won’t hate and reject then engineering full spectrum nuance is just as important a piece of work as having an amazing speech recognition engine. A chatbot that can’t do all that is really the gimmick.

Chernyshov claims Dasha’s conversation engine is “at least several times better and more complex than [Google] Dialogflow, [Amazon] Lex, [Microsoft] Luis or [IBM] Watson”, dropping a laundry list of rival speech engines into the conversation.

He argues none are on a par with what Dasha is being designed to do.

The difference is the “voice-first modelling engine”. “All those [rival engines] were built from scratch with a focus on chatbots — on text,” he says, couching modelling voice conversation “on a human level” as much more complex than the more limited chatbot-approach — and hence what makes Dasha special and superior.

“Imagination is the limit. What we are trying to build is an ultimate voice conversation AI platform so you can model any kind of voice interaction between two or more human beings.”

Google did demo its own stuttering voice AI — Duplex — last year, when it also took flak for a public demo in which it appeared not to have told restaurant staff up front they were going to be talking to a robot.

Chernyshov isn’t worried about Duplex, though, saying it’s a product, not a platform.

“Google recently tried to headhunt one of our developers,” he adds, pausing for effect. “But they failed.”

He says Dasha’s engineering staff make up more than half (28) its total headcount (48), and include two doctorates of science; three PhDs; five PhD students; and ten masters of science in computer science.

It has an R&D office in Russian which Chernyshov says helps makes the funding go further.

“More than 16 people, including myself, are ACM ICPC finalists or semi finalists,” he adds — likening the competition to “an Olympic game but for programmers”. A recent hire — chief research scientist, Dr Alexander Dyakonov — is both a doctor of science professor and former Kaggle No.1 GrandMaster in machine learning. So with in-house AI talent like that you can see why Google, uh, came calling…

Dasha

 

But why not have Dasha ID itself as a robot by default? On that Chernyshov says the platform is flexible — which means disclosure can be added. But in markets where it isn’t a legal requirement the door is being left open for ‘John’ to slip cheerily by. Bladerunner here we come.

The team’s driving conviction is that emphasis on modelling human-like speech will, down the line, allow their AI to deliver universally fluid and natural machine-human speech interactions which in turn open up all sorts of expansive and powerful possibilities for embeddable next-gen voice interfaces. Ones that are much more interesting than the current crop of gadget talkies.

This is where you could raid sci-fi/pop culture for inspiration. Such as Kitt, the dryly witty talking car from the 1980s TV series Knight Rider. Or, to throw in a British TV reference, Holly the self-depreciating yet sardonic human-faced computer in Red Dwarf. (Or indeed Kryten the guilt-ridden android butler.) Chernyshov’s suggestion is to imagine Dasha embedded in a Boston Dynamics robot. But surely no one wants to hear those crawling nightmares scream…

Dasha’s five-year+ roadmap includes the eyebrow-raising ambition to evolve the technology to achieve “a general conversational AI”. “This is a science fiction at this point. It’s a general conversational AI, and only at this point you will be able to pass the whole Turing Test,” he says of that aim.

“Because we have a human level speech recognition, we have human level speech synthesis, we have generative non-rule based behavior, and this is all the parts of this general conversational AI. And I think that we can we can — and scientific society — we can achieve this together in like 2024 or something like that.

“Then the next step, in 2025, this is like autonomous AI — embeddable in any device or a robot. And hopefully by 2025 these devices will be available on the market.”

Of course the team is still dreaming distance away from that AI wonderland/dystopia (depending on your perspective) — even if it’s date-stamped on the roadmap.

But if a conversational engine ends up in command of the full range of human speech — quirks, quibbles and all — then designing a voice AI may come to be thought of as akin to designing a TV character or cartoon personality. So very far from what we currently associate with the word ‘robotic’. (And wouldn’t it be funny if the term ‘robotic’ came to mean ‘hyper entertaining’ or even ‘especially empathetic’ thanks to advances in AI.)

Let’s not get carried away though.

In the meanwhile, there are ‘uncanny valley’ pitfalls of speech disconnect to navigate if the tone being (artificially) struck hits a false note. (And, on that front, if you didn’t know ‘John from Acme Dental’ was a robot you’d be forgiven for misreading his chipper sign off to a total time waster as pure sarcasm. But an AI can’t appreciate irony. Not yet anyway.)

Nor can robots appreciate the difference between ethical and unethical verbal communication they’re being instructed to carry out. Sales calls can easily cross the line into spam. And what about even more dystopic uses for a conversation engine that’s so slick it can convince the vast majority of people it’s human — like fraud, identity theft, even election interference… the potential misuses could be terrible and scale endlessly.

Although if you straight out ask Dasha whether it’s a robot Chernyshov says it has been programmed to confess to being artificial. So it won’t tell you a barefaced lie.

Dasha

How will the team prevent problematic uses of such a powerful technology?

“We have an ethics framework and when we will be releasing the platform we will implement a real-time monitoring system that will monitor potential abuse or scams, and also it will ensure people are not being called too often,” he says. “This is very important. That we understand that this kind of technology can be potentially probably dangerous.”

“At the first stage we are not going to release it to all the public. We are going to release it in a closed alpha or beta. And we will be curating the companies that are going in to explore all the possible problems and prevent them from being massive problems,” he adds. “Our machine learning team are developing those algorithms for detecting abuse, spam and other use cases that we would like to prevent.”

There’s also the issue of verbal ‘deepfakes’ to consider. Especially as Chernyshov suggests the platform will, in time, support cloning a voiceprint for use in the conversation — opening the door to making fake calls in someone else’s voice. Which sounds like a dream come true for scammers of all stripes. Or a way to really supercharge your top performing salesperson.

Safe to say, the counter technologies — and thoughtful regulation — are going to be very important.

There’s little doubt that AI will be regulated. In Europe policymakers have tasked themselves with coming up with a framework for ethical AI. And in the coming years policymakers in many countries will be trying to figure out how to put guardrails on a technology class that, in the consumer sphere, has already demonstrated its wrecking-ball potential — with the automated acceleration of spam, misinformation and political disinformation on social media platforms.

“We have to understand that at some point this kind of technologies will be definitely regulated by the state all over the world. And we as a platform we must comply with all of these requirements,” agrees Chernyshov, suggesting machine learning will also be able to identify whether a speaker is human or not — and that an official caller status could be baked into a telephony protocol so people aren’t left in the dark on the ‘bot or not’ question. 

“It should be human-friendly. Don’t be evil, right?”

Asked whether he considers what will happen to the people working in call centers whose jobs will be disrupted by AI, Chernyshov is quick with the stock answer — that new technologies create jobs too, saying that’s been true right throughout human history. Though he concedes there may be a lag — while the old world catches up to the new.

Time and tide wait for no human, even when the change sounds increasingly like we do.


By Natasha Lomas

Why AWS gains big storage efficiencies with E8 acquisition

AWS is already the clear market leader in the cloud infrastructure market, but it’s never been an organization that rests on its past successes. Whether it’s a flurry of new product announcements and enhancements every year, or making strategic acquisitions.

When it bought Israeli storage startup E8 yesterday, it might have felt like a minor move on its face, but AWS was looking, as it always does, to find an edge and reduce the costs of operations in its data centers. It was also very likely looking forward to the next phase of cloud computing. Reports have pegged the deal at between $50 and $60 million.

What E8 gives AWS for relatively cheap money is highly advanced storage capabilities, says Steve McDowell, senior storage analyst at Moor Research and Strategy. “E8 built a system that delivers extremely high-performance/low-latency flash (and Optane) in a shared-storage environment,” McDowell told TechCrunch.


By Ron Miller

The Exit: The acquisition charting Salesforce’s future

Before Tableau was the $15.7 billion key to Salesforce’s problems, it was a couple of founders arguing with a couple of venture capitalists over lunch about why its Series A valuation should be higher than $12 million pre-money.

Salesforce has generally been one to signify corporate strategy shifts through their acquisitions, so you can understand why the entire tech industry took notice when the cloud CRM giant announced its priciest acquisition ever last month.

The deal to acquire the Seattle-based data visualization powerhouse Tableau was substantial enough that Salesforce CEO Marc Benioff publicly announced it was turning Seattle into its second HQ. Tableau’s acquisition doesn’t just mean big things for Salesforce. With the deal taking place just days after Google announced it was paying $2.6 billion for Looker, the acquisition showcases just how intense the cloud wars are getting for the enterprise tech companies out to win it all.

The Exit is a new series at TechCrunch. It’s an exit interview of sorts with a VC who was in the right place at the right time but made the right call on an investment that paid off. [Have feedback? Shoot me an email at [email protected]]

Scott Sandell, a general partner at NEA (New Enterprise Associates) who has now been at the firm for 25 years, was one of those investors arguing with two of Tableau’s co-founders, Chris Stolte and Christian Chabot. Desperate to close the 2004 deal over their lunch meeting, he went on to agree to the Tableau founders’ demands of a higher $20 million valuation, though Sandell tells me it still feels like he got a pretty good deal.

NEA went on to invest further in subsequent rounds and went on to hold over 38% of the company at the time of its IPO in 2013 according to public financial docs.

I had a long chat with Sandell, who also invested in Salesforce, about the importance of the Tableau deal, his rise from associate to general partner at NEA, who he sees as the biggest challenger to Salesforce, and why he thinks scooter companies are “the worst business in the known universe.”

The interview has been edited for length and clarity. 


Lucas Matney: You’ve been at this investing thing for quite a while, but taking a trip down memory lane, how did you get into VC in the first place? 

Scott Sandell: The way I got into venture capital is a little bit of a circuitous route. I had an opportunity to get into venture capital coming out of Stanford Business School in 1992, but it wasn’t quite the right fit. And so I had an interest, but I didn’t have the right opportunity.


By Lucas Matney

Analytics startup Heap raises $55M

Since co-founding Heap, CEO Matin Movassate has been saying that he wants to take on the analytics incumbents. Today, he’s got more money to fund that challenge, with the announcement that Heap has raised $55 million in Series C funding.

Movassate (pictured above) previously worked as a product manager at Facebook, and I interviewed him after the startup’s Series B, he recalled the circuitous process normally required to collect and analyze user data. In contrast, Heap automatically collects data on user activity — the goal is to capture literally everything — and makes it available in a self-serve way, with no additional code required to answer new queries.

The company says it now has more than 6,000 customers, including Twilio, AppNexus, Harry’s, WeWork and Microsoft.

With this new funding, Heap has raised a total of $95.2 million. The plan is to fund international growth, as well to expand the product, engineering and go-to-market teams.

The Series C was led by NewView Capital, with participation from new DTCP, Maverick Ventures, Triangle Peak Partners, Alliance Bernstein Private Credit Investors and Sharespost) and existing investors (NEA, Menlo Ventures, Initialized Capital, and Pear VC). NewView founder and managing partner Ravi Viswanathan is joining the startup’s board of directors.

“Heap offers an innovative approach to automating a company’s analytics, enabling a variety of teams within an organization to obtain the data they need to make educated and, ultimately, smarter decisions,” Viswanathan said in a statement. “We are excited to team up with Heap, as they continue to develop their cutting edge software, expand their analytics automation offerings and help serve their growing numbers of customers.”


By Anthony Ha

VComply raises $2.5 million seed round led by Accel to simplify risk and compliance management

Risk and compliance management platform VComply announced today that it has picked up a $2.5 million seed round led by Accel Partners for its international growth plan. The funding will be used to acquire more customers in the United States, open a new office in the United Kingdom to support customers in Europe and expand its presence in New Zealand and Australia.

The company was founded in 2016 by CEO Harshvardhan Kariwala and has customers in a wide range of industries, including Acreage Holdings, Ace Energy Solutions, CHD, the United Kingdom’s Department of International Trade and Burger King. It currently claims about 4,000 users in more than 100 countries. VComply is meant to be used by all departments in a company, with compliance information organized into a central dashboard.

While there are already a roster of governance, risk and compliance management solutions on the market (including ones from Oracle, HPE, Thomson Reuters, IBM and other established enterprise software companies), VComply’s competitive edge may be its flexibility, simple user interface and easy deployment (the company claims customers can on-board and start using the solution for compliance tasks in about 30 minutes). It also seeks out smaller companies whose needs have not been met by compliance solutions meant for large enterprises.

Kariwala told TechCrunch in an email that he began thinking of creating a new risk and compliance solution while working at his first startup LIME Learning Systems, an education management platform, after being hit with a $4,000 penalty due to a non-compliance issue.

“Believe me, $4,000 really hurts when you’re bootstrapped and trying to save every single cent you can. In this case, I had asked our outsourced accounting partners to manage this compliance and they forgot!” he said. After talking to other entrepreneurs, he realized compliance posed a challenge for most of them. LIME’s team built an internal compliance tracking tool for their own use, but also shared it with other people. After getting good feedback, Kariwala realized that despite the many governance, risk and compliance management solutions already on the market, there was still a gap in the market, especially for smaller businesses.

VComply is designed so organizations can customize it for their industry’s regulations and standards, as well as their own workflow and data needs, with competitive pricing for small to medium-sized organizations (a subscription starts at $3,999 a year).

“Most of the traditional GRC solutions that exist today are expensive, have a steep learning curve and entail a prolonged deployment. Not only are they expensive, they are also rigid, which means that organizations have little to no control or flexibility,” Kariwala said. “A GRC tool is often looked at as an expense, while it should really be treated as an investment. It is particularly the SMB sector that suffers the most. With the current solutions costing thousands of dollars (and sometimes millions), it becomes the least of their priorities to invest in a GRC platform, and as a result they fall prey to heightened risks and hefty penalties for non-compliance.”

In a press statement, Accel partner Dinesh Katiyar said “The first generation of GRC solutions primarily allowed companies to comply with industry-mandated regulations. However, the modern enterprise needs to govern its operations to maintain integrity and trust, and monitor internal and external risks to stay successful. That is where VComply shines, and we’re delighted to be partnering with a company that can redefine the future of enterprise risk management.”


By Catherine Shu

Southeast Asian cloud communications platform Wavecell acquired by 8×8 in deal worth $125 million

Wavecell, a cloud-communications platform for companies in Southeast Asia, announced today that it has been acquired by 8×8 in a deal worth about $125 million. The acquisition will help San Jose, California-based 8×8 expand in Asia, where Wavecell already has offices in Singapore, Indonesia, the Philippines, Thailand and Hong Kong.

Wavecell’s cloud API platform, which includes SMS, chat, video and voice messaging, is used by companies such as Paidy, Lalamove and Tokopedia. It has relationships with 192 network operators and partners like WhatsApp and claims its infrastructure is used to share more than two billion messages each year.

The terms of the deal includes $69 million in cash and about $56 million in 8×8 common shares. Founded in 2010, Wavecell’s investors included Qualgro VC, Wavemaker Partners and MDI Ventures.

In a prepared statement, 8×8 CEO Vik Verma said “8×8 is now the only cloud provider that owns the full, global-scale, cloud-native, technology stack offering voice, video, messaging, and contact center delivered both as pre-packaged applications and as enterprise-class APIs. We’re excited to welcome the Wavecell employees to the 8×8 family. We now have a significant market presence in Asia and expect to continue to expand in the region and globally in order to meet evolving customer requirements.”


By Catherine Shu