SmartDrive snaps up $90M for in-truck video telematics solutions for safety and fuel efficiency

Trucks and other large commercial vehicles and the biggest whales on the road today — are they also, by virtue of that size, some of the most dangerous and inefficient if they are driven badly. Today, a startup that has built a platform aimed at improving both of those areas has raised a large round of funding to continue fuelling (so to speak) its own growth: SmartDrive, a San Diego-based provider of video-based telematics and transportation insights, has snapped up a round of $90 million.

The company is not disclosing its valuation but according to PitchBook, it was last valued (in 2017) at $290 million, which would put the valuation now around $380 million. But given that the company has been growing well — it says that in the first half of this year, its contracted units were up 48%, while sales were up by 44% — that figure may well be higher. (We are asking.)

The funding comes at an interesting time for fleet management and the trucking industry. A lot of the big stories about automotive technology at the moment seem to be focused on autonomous vehicles for private usage, but that leaves a large — and largely legacy — market in the form of fleet management and commercial vehicles. That’s not to say it’s been completely ignored, however. Bigger companies like Uber, Telsa and Volvo, and startups like Nikola and more are all building smarter vehicles, and just yesterday Samsara, which makes an industrial IoT platform that works, in part, to provide fleet management to the trucking industry, raised $300 million on a $6.3 billion valuation.

The telematics market was estimated to be worth $25.5 billion in 2018 and is forecast to grow to some $98 billion by 2026.

The round was led by TPG Sixth Street Partners, a division of investment giant TPG (which backs the likes of Spotify and many others), which earlier this year was raising a $2 billion fund for growth-stage investments. Unnamed existing investors also participated. The company prior to this had raised $230 million, with other backers including Founders Fund, NewView Capital, Oak Investment Partners, Michelin and more. (NEA had also been an investor but has more recently sold its stake.)

SmartDrive has been around since 2005 and focuses on a couple of key areas. Tapping data from the many sensors that you have today in commercial vehicles, it builds up a picture of how specific truckers are handling their vehicles, from their control on tricky roads to what gears and speed they are using as they go up inclines, and how long they idle their engines. The resulting data is used both to provide a better picture to fleet managers of that performance, and to highlight specific areas where the trucker can improve his performance, and how.

Analytics and data provided to customers include multi-camera 360-degree views, extended recording and U-turn triggering, along with diagnostics on specific driver performance. The company claims that the information has led to more satisfaction among drivers and customers, with driver retention rates of 70% or higher and improvements to 9 miles per gallon (mpg) on trips, versus industry averages of 20% driver retention and 6 mpg.

“This is an exciting time at SmartDrive and in the transportation sector overall as adoption of video-based telematics continues to accelerate,” stated Steve Mitgang, SmartDrive CEO, in a statement. “Building on our pioneering video-based safety program, our vision of an open platform powering best-of-breed video, compliance and telematics applications is garnering significant traction across a diverse range of fleets given the benefits of choice, flexibility and a lower total cost of ownership. The investment from TPG Sixth Street Partners and our existing investors will fuel continued innovation in areas such as computer vision and AI, while also enhancing sales and marketing initiatives and further international expansion.”

The focus for SmartDrive seems to be on how drivers are doing in specific circumstances: it doesn’t seem to focus on whether there could have been better routes, or if better fleet management could have resulted in improved performance.

“SmartDrive is a market leader in the large and expanding transportation safety and intelligence sector and we are pleased to be investing in a growing company led by such a talented team,” noted Bo Stanley, partner and co-head of the Capital Solutions business at TPG Sixth Street Partners, in a statement. “SmartDrive’s proprietary data analytics platform and strong subscriber base put it in a great position to continue to capitalize on its track record of innovation and the broader secular trend of higher demand for safer and smarter transportation.”


By Ingrid Lunden

Snyk grabs $70M more to detect security vulnerabilities in open source code and containers

A growing number of IT breaches has led to security becoming a critical and central aspect of how computing systems are run and maintained. Today, a startup that focuses on one specific area — developing security tools aimed at developers and the work they do — has closed a major funding round that underscores the growth of that area.

Snyk — a London and Boston-based company that got its start identifying and developing security solutions for developers working on open source code — is today announcing that it has raised $70 million, funding that it will be using to continue expanding its capabilities and overall business. For example, the company has more recently expanded to building security solutions to help developers identify and fix vulnerabilities around containers, an increasingly standard unit of software used to package up and run code across different computing environments.

Open source — Snyk works as an integration into existing developer workflows, compatible with the likes of GitHub, Bitbucket and GitLab, as well as CI/CD pipelines — was an easy target to hit. It’s used in 95% of all enterprises, with up to 77% of open source components liable to have vulnerabilities, by Snyk’s estimates. Containers are a different issue.

“The security concerns around containers are almost more about ownership than technology,” Guy Podjarny, the president who co-founded the company with Assaf Hefetz and Danny Grander, explained in an interview. “They are in a twilight zone between infrastructure and code. They look like virtual machines and suffer many of same concerns such as being unpatched or having permissions that are too permissive.”

While containers are present in fewer than 30% of computing environments today, their growth is on the rise, according to Gartner, which forecasts that by 2022, over 75% of global organizations will run containerized applications. Snyk estimates that a full 44% of Docker image scans (Docker being one of the major container vendors) have known vulnerabilities.

This latest round is being led by Accel with participation from existing investors GV and Boldstart Ventures. These three, along with a fourth investor (Heavybit) also put $22 million into the company as recently as September 2018. That round was made at a valuation of $100 million, and from what we understand from a source close to the startup, it’s now in the “range” of $500 million.

“Accel has a long history in the security market and we believe Snyk is bringing a truly unique, developer-first approach to security in the enterprise,” said Matt Weigand of Accel said in a statement. “The strength of Snyk’s customer base, rapidly growing free user community, leadership team and innovative product development prove the company is ready for this next exciting phase of growth and execution.”

Indeed, the company has hit some big milestones in the last year that could explain that hike. It now has some 300,000 developers using it around the globe, with its customer base growing some 200 percent this year and including the likes of Google, Microsoft, Salesforce and ASOS (sidenote: you know that if developers at developer-centric places themselves working at the vanguard of computing, like Google and Microsoft, are using your product, that is a good sign). Notably, that has largely come by word of mouth — inbound interest.

The company in July of this year took on a new CEO, Peter McKay, who replaced Podjarny. McKay was the company’s first investor and has a track record in helping to grow large enterprise security businesses, a sign of the trajectory that Snyk is hoping to follow.

“Today, every business, from manufacturing to retail and finance, is becoming a software business,” said McKay. “There is an immediate and fast growing need for software security solutions that scale at the same pace as software development. This investment helps us continue to bring Snyk’s product-led and developer-focused solutions to more companies across the globe, helping them stay secure as they embrace digital innovation – without slowing down.”

 


By Ingrid Lunden

Q-CTRL raises $15M for software that reduces error and noise in quantum computing hardware

As hardware makers continue to work on ways of making wide-scale quantum computing a reality, a startup out of Australia that is building software to help reduce noise and errors on quantum computing machines has raised a round of funding to fuel its U.S. expansion.

Q-CTRL is designing firmware for computers and other machines (such as quantum sensors) that perform quantum calculations to identify the potential for errors, making them more resistant and able to stay working for longer (the Q in its name is a reference to qubits, the basic building block of quantum computing). The startup is today announcing that it has raised $15 million, money that it plans to use to double its team (currently numbering 25) and set up shop on the West Coast, specifically Los Angeles.

This Series A is coming from a list of backers that speaks to the startup’s success to date in courting quantum hardware companies as customers. Led by Square Peg Capital — a prolific Australian VC that has backed homegrown startups like Bugcrowd and Canva, but also those further afield such as Stripe — it also includes new investor Sierra Ventures as well as Sequoia Capital, Main Sequence Ventures, and Horizons Ventures.

Q-CTRL’s customers are some of the bigger names in quantum computing and IT such as Rigetti, Bleximo and Accenture, among others. IBM — which earlier this year unveiled its first commercial quantum computer — singled it out last year for its work in advancing quantum technology.

The problem that Q-CTRL is aiming to address is basic but arguably critical to solving if quantum computing ever hopes to make the leap out of the lab and into wider use in the real world.

Quantum computers and other machines like quantum sensors, which are built on quantum physics architecture, are able to perform computations that go well beyond what can be done by normal computers today, with the applications for such technology including cryptography, biosciences, advanced geological exploration and much more. But quantum computing machines are known to be unstable, in part because of the fragility of the quantum state, which introduces a lot of noise and subsequent errors.

As Frederic pointed out recently, scientists are confident that this is ultimately a solvable issue. Q-CTRL is one of the hopefuls working on that, by providing a set of tools that runs on quantum machines, visualises noise and decoherence, and then deploys controls to “defeat” those errors.

Q-CTRL currently has four products it offers to the market, Black Opal, Boulder Opal, Open Controls and Devkit — aimed respectively at students/those exploring quantum computing, hardware makers, the research community, and end users/algorithm developers.

Q-CTRL was founded in 2017 by Michael Biercuk, a Professor of Quantum Physics & Quantum Technology at the University of Sydney and a Chief Investigator in the Australian Research Council Centre of Excellence for Engineered Quantum Systems, who studied in the U.S., with a PhD in physics from Harvard.

“Being at the vanguard of the birth of a new industry is extraordinary,” he said in a statement. “We’re also thrilled to be assembling one of the most impressive investor syndicates in quantum technology. Finding investors who understand and embrace both the promise and the challenge of building quantum computers is almost magical.”

Why choose Los Angeles for building out a U.S. presence, you might ask? Southern California, it turns out, has shaped up to be a key area for quantum research and development, with several of the universities in the region building out labs dedicated to the area, and companies like Lockheed Martin and Google also contributing to the ecosystem. This means a strong pipeline of talent and conversation in what is still a nascent area.

Given that it is still early days for quantum computing technology, that gives a lot of potential options to a company  like Q-CTRL longer-term: the company might continue to build a business as it does today, selling its technology to a plethora of hardware makers and researchers in the field; or it might get snapped up by a specific hardware company to integrate Q-CTRL’s solutions more closely onto its machines (and keep them away from competitors). Or, it could make like a quantum particle and follow both of those paths at the same time.

“Q-CTRL impressed us with their strategy; by providing infrastructure software to improve quantum computers for R&D teams and end-users, they’re able to be a central player in bringing this technology to reality,” said Tushar Roy, a partner at Square Peg. “Their technology also has applications beyond quantum computing, including in quantum-based sensing, which is a rapidly-growing market. In Q-CTRL we found a rare combination of world-leading technical expertise with an understanding of customers, products and what it takes to build an impactful business.”


By Ingrid Lunden

Newly renamed Superside raises $3.5M for its outsourced design platform

Superside, a startup aiming to create a premium alternative to the existing crowdsourced design platforms, is announcing that it has raised $3.5 million in new funding.

It’s also adding new features like the ability to work on user interfaces, interaction design and motion graphics. Co-founder and CEO Fredrik Thomassen said this allows the company to offer “a full-service design solution.”

You may have heard about Superside under its old name Konsus . In a blog post, Thomassen explained the recent change in name and branding, writing, “We changed our name and look to align with what we had become: The world’s top team of international designers and creatives.”

He told me Superside was created to address his own frustrations after trying to use marketplaces like 99designs and Fiverr. He argued that there’s a problem with “adverse selection on those platforms.” In other words, “The best people … don’t remain, because they don’t have a career path — they’re fighting with other freelancers to get the jobs.”

Superside, on the other hand, is picky about the designers it works with — it claims to select 100 designers from the more than 50,000 applications it receives each year. But if they are accepted, they’re guaranteed full-time work.

superside step1 orderwizard

Thomassen said the platform is built for large enterprises that have their own design and marketing teams but still need additional support. Customers include Amazon, BBDO, Publicis and Clear Channel.

In addition to choosing good designers, Superside also built a broader project management platform.

“We’re basically automating everything: Finding people, screening people, on-boarding, on-the-job learning, invoicing of customers, project management, all of the nitty gritty,” Thomassen said. “The only thing not automated is design — that’s where the human element and the creativity come in.”

Plus, Thomassen said Superside can turn around a standard piece of artwork in 12 hours: “Nobody else can do what we’re doing in terms of speed.”

The new funding comes from Freestyle Capital, with participation from High Alpha Ventures, Y Combinator and Alliance Ventures.

“We’re very much a mission-driven company,” Thomassen added. “For me, the reason to go to work in the morning is to help build an online labor market and create equal economic opportunity for everyone in the world.”


By Anthony Ha

OpenGov raises $51M to boost its cloud-based IT services for government and civic organizations

OpenGov, the firm co-founded by Panaltir’s Joe Lonsdale that helps government and other civic organizations organise, analyse and present financial and other data using cloud-based architecture, has raised another big round of funding to continue expanding its business. The startup has picked up an additional $51 million in a Series D round led by Weatherford Capital and 8VC (Lonsdale’s investment firm), with participation from existing investor Andreessen Horowitz.

The funding brings the total raised by the company to $140 million, with previous investors in the firm including JC2 Ventures, Emerson Collective, Founders Fund and a number of others. The company is not disclosing its valuation — although we are asking — but for some context, PitchBook noted it was around $190 million in its last disclosed round — although that was in 2017 and has likely increased in the interim, not least because of the startup’s links in high places, and its growth.

On the first of these, the company says that its board of directors includes, in addition to Lonsdale (who is now the chairman of the company); Katherine August-deWilde, Co-Founder and Vice-Chair of First Republic Bank; John Chambers, Founder and CEO of JC2 Ventures and Former Chairman and CEO of Cisco Systems; Marc Andreessen, Co-Founder and General Partner of Andreessen Horowitz; and Zac Bookman, Co-Founder and CEO of OpenGov .

And in terms of its growth, OpenGov says today it counts more than 2,000 governments as customers, with recent additions to the list including the State of West Virginia, the State of Oklahoma, the Idaho State Controller’s Office, the City of Minneapolis MN, and Suffolk County NY. For comparison, when we wrote in 2017 about the boost the company had seen since Trump’s election (which has apparently seen a push for more transparency and security of data), the company noted 1,400 government customers.

Government data is generally associated with legacy systems and cripplingly slow bureaucratic processes, and that has spelled opportunity to some startups, who are leveraging the growth of cloud services to present solutions tailored to the needs of civic organizations and the people who work in them, from city planners to finance specialists. In the case of OpenGov, it packages its services in a platform it calls the OpenGov Cloud.

“OpenGov’s mission to power more effective and accountable government is driving innovation and transformation for the public sector at high speed,” said OpenGov CEO Zac Bookman in a statement. “This new investment validates OpenGov’s position as the leader in enterprise cloud solutions for government, and it fuels our ability to build, sell, and deploy new mission-critical technology that is the safe and trusted choice for government executives.”

City Manager Dashboard Screen

It’s also, it seems, a trusted choice for government executives who have left public service and moved into investing, leveraging some of the links they still have into those who manage procurement for public services. Weatherford Capital, one of the lead investors, is led in part by managing partner Will Weatherford, who is the former Speaker of the House for the State of Florida.

“OpenGov’s innovative technology, accomplished personnel, market leadership, and mission-first approach precisely address the growing challenges inherent in public administration,” he said in a statement. “We are thrilled at the opportunity to partner with OpenGov to accelerate its growth and continue modernizing how this important sector operates.”

It will be interesting to see how and if the company uses the funding to consolidate in its particular area of enterprise technology. There are other firms like LiveStories that have also been building services to help better present civic data to the public that you could see as complementary to what OpenGov is doing. OpenGov has made acquisitions in the past, such as Ontodia to bring more open-source data and technology into its platform.


By Ingrid Lunden

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

Clumio raises $51M to bring enterprise backup into the 21st century

Creating backups for massive enterprise deployments may feel like a solved problem, but for the most part, we’re still talking about complex hardware and software setups. Clumio, which is coming out of stealth today, wants to modernize enterprise data protection by eliminating the on-premise hardware in favor of a flexible, SaaS-style cloud-based backup solution.

For the first time, Clumio also today announced that it has raised a total of $51 million in a Series A and B round since it was founded in 2017. The $11 million Series A round closed in October 2017 and the Series B round in November 2018, Clumio founder and CEO Poojan Kumar told me. Kumar’s previous company, storage startup PernixData, was acquired by Nutanix in 2016. It doesn’t look like the investors made their money back, though.

Clumio is backed by investors like Sutter Hill Ventures, which led the Series A, and Index Ventures, which drove the Series B together with Sutter Hill. Other individual investors include Mark Leslie, founder of Veritas Technologies, and John Thompson, chairman of the board at Microsoft .

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“Enterprise workloads are being ‘SaaS-ified’ because IT can no longer afford the time, complexity and expense of building and managing heavy on-prem hardware and software solutions if they are to successfully deliver against their digital transformation initiatives,” said Kumar. “Unlike legacy backup vendors, Clumio SaaS is born in the cloud. We have leveraged the most secure and innovative cloud services available, now and in the future, within our service to ensure that we can meet customer requirements for backup, regardless of where the data is.”

In its current iteration, Clumio can be used to secure data from on-premise, VMware Cloud for AWS and native AWS service workloads. Given this list, it doesn’t come as a surprise that Clumio’s backend, too, makes extensive use of public cloud services.

The company says that it already has several customers, though it didn’t disclose any in today’s announcement.


By Frederic Lardinois

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 been doubling revenues each year for the last three and counts companies like Reddit, Red Hat, REI, the US Census among some 400 others among 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 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 RedHat or Reddit — and half comes from knowledge worker applications inside organizations.

The plan will be to continue that proportion, while also adding in 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.”


By Ingrid Lunden

Cybereason raises $200 million for its enterprise security platform

Cybereason, which uses machine learning to increase the number of endpoints a single analyst can manage across a network of distributed resources, has raised $200 million in new financing from SoftBank Group and its affiliates. 

It’s a sign of the belief that SoftBank has in the technology, since the Japanese investment firm is basically doubling down on commitments it made to the Boston-based company four years ago.

The company first came to our attention five years ago when it raised a $25 million financing from investors, including CRV, Spark Capital and Lockheed Martin.

Cybereason’s technology processes and analyzes data in real time across an organization’s daily operations and relationships. It looks for anomalies in behavior across nodes on networks and uses those anomalies to flag suspicious activity.

The company also provides reporting tools to inform customers of the root cause, the timeline, the person involved in the breach or breaches, which tools they use and what information was being disseminated within and outside of the organization.

For co-founder Lior Div, Cybereason’s work is the continuation of the six years of training and service he spent working with the Israeli army’s 8200 Unit, the military incubator for half of the security startups pitching their wares today. After his time in the military, Div worked for the Israeli government as a private contractor reverse-engineering hacking operations.

Over the last two years, Cybereason has expanded the scope of its service to a network that spans 6 million endpoints tracked by 500 employees, with offices in Boston, Tel Aviv, Tokyo and London.

“Cybereason’s big data analytics approach to mitigating cyber risk has fueled explosive expansion at the leading edge of the EDR domain, disrupting the EPP market. We are leading the wave, becoming the world’s most reliable and effective endpoint prevention and detection solution because of our technology, our people and our partners,” said Div, in a statement. “We help all security teams prevent more attacks, sooner, in ways that enable understanding and taking decisive action faster.”

The company said it will use the new funding to accelerate its sales and marketing efforts across all geographies and push further ahead with research and development to make more of its security operations autonomous.

“Today, there is a shortage of more than three million level 1-3 analysts,” said Yonatan Striem-Amit, chief technology officer and co-founder, Cybereason, in a statement. “The new autonomous SOC enables SOC teams of the future to harness technology where manual work is being relied on today and it will elevate  L1 analysts to spend time on higher value tasks and accelerate the advanced analysis L3 analysts do.”

Most recently the company was behind the discovery of Operation SoftCell, the largest nation-state cyber espionage attack on telecommunications companies. 

That attack, which was either conducted by Chinese-backed actors or made to look like it was conducted by Chinese-backed actors, according to Cybereason, targeted a select group of users in an effort to acquire cell phone records.

As we wrote at the time:

… hackers have systematically broken in to more than 10 cell networks around the world to date over the past seven years to obtain massive amounts of call records — including times and dates of calls, and their cell-based locations — on at least 20 individuals.

Researchers at Boston-based Cybereason, who discovered the operation and shared their findings with TechCrunch, said the hackers could track the physical location of any customer of the hacked telcos — including spies and politicians — using the call records.

Lior Div, Cybereason’s co-founder and chief executive, told TechCrunch it’s “massive-scale” espionage.

Call detail records — or CDRs — are the crown jewels of any intelligence agency’s collection efforts. These call records are highly detailed metadata logs generated by a phone provider to connect calls and messages from one person to another. Although they don’t include the recordings of calls or the contents of messages, they can offer detailed insight into a person’s life. The National Security Agency  has for years controversially collected the call records of Americans from cell providers like AT&T and Verizon (which owns TechCrunch), despite the questionable legality.

It’s not the first time that Cybereason has uncovered major security threats.

Back when it had just raised capital from CRV and Spark, Cybereason’s chief executive was touting its work with a defense contractor who’d been hacked. Again, the suspected culprit was the Chinese government.

As we reported, during one of the early product demos for a private defense contractor, Cybereason identified a full-blown attack by the Chinese — 10,000 thousand usernames and passwords were leaked, and the attackers had access to nearly half of the organization on a daily basis.

The security breach was too sensitive to be shared with the press, but Div says that the FBI was involved and that the company had no indication that they were being hacked until Cybereason detected it.


By Jonathan Shieber

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

TrustRadius, a customer-generated B2B software review platform, raises $12.5M

Customer reviews play a key role in helping people decide what to buy on consumer-focused marketplaces like Amazon or app stores, and the same tendency exists in the B2B world, where nearly half a trillion dollars is spent annually on software and IT purchases. TrustRadius, one of the startups capitalising on the latter trend with total feedback sessions today standing at close to 190,000 reviews, has now picked up a Series C of $12.5 million led by Next Coast Ventures with existing investors Mayfield Fund and LiveOak Ventures also participating.

The funding, which brings the total raised by TrustRadius to $25 million (modest compared to some of its competitors) will be used to build more partnerships and use cases for its reviews, as well as continue expanding that total number of users providing feedback.

In addition to its main site — which goes up against a huge number of other online software comparison services like TrustPilot, G2 Crowd, Owler, and many others — TrustRadius is already working with vendors like LogMeIn, Tibco and more (including a number of huge IT companies that have asked not to be named).

TrustRadius mainly works with them on two tracks: to source a wider range of reviews from their existing customer bases to improve their profiles on the site; and then to help them use those reviews in their own marketing materials. Partnerships like these form the core of TrustRadius’s business model: people posting reviews or using the site to read them access it for free.

Vinay Bhagat, founder and CEO of TrustRadius, believes that his company’s mission — to help IT decision makers vet software by tapping into feedback from other IT buyers — has found particular relevance in the current market.

“I think that gravity is on our side,” he said in an interview. “If you think about how the tech industry is evolving and getting things done, IT decisions are getting decentralized and moving out of the CIO’s office. Millennials are ageing into positions of authority, and it means that the way people had previously bought software — by way of salespeople or on the basis of analyst reports — are changing. There is pent-up demand to hear the roar of peers and that’s where we come in.”

User-generated reviews have come under a lot of criticism in recent times. Regulators have been going after companies for not being vigilant enough about policing their platforms for “fake” reviews, either planted to big up a product, or by rivals to knock it down, or coming from people who are being paid to put in a good word. The argument has been that the marketplaces hosting those reviews are still bringing in eyeballs and product conversions based on that feedback, so they are less concerned with the corruption even if it longer term can likely sour consumers on the trustworthiness of the whole platform.

That belief is not wholly true, of course: Amazon for one has recently been making a huge effort to improve trust, by going after dodgy reviewers and setting up systems to halt the trafficking of counterfeit goods.

And Bhagat argued to me that it doesn’t hold for TrustRadius, either. The company has a focused enough mandate — B2B software purchasing — within a crowded enough field, that losing trust by posting blindly positive reviews would get it nowhere fast.

At the same time, he noted that the company has held a firm line with its customers on making sure that the “truth” about a product is made clear even if it’s not completely rosy, in the hopes that they can use that to work on improvements, and also provide more balanced feed back at the least from existing customers in order to give a more complete picture. (It also, like other reviews sites, makes people who provide feedback do so using professional credentials like work emails and LinkedIn profiles.)

That line has so far carried it into relationships with a number of software companies, which are using reviews as a complement to their own sales teams, and the papers and analysis published by analysts like Gartner and Ovum and Forester, to reach people who are weighing up different options for their IT solutions.

“TrustRadius has become an integral part of today’s economic cycle”, said Bill Wagner, CEO of LogMeIn, in a statement. “Software buyers today need detailed reviews to make sure that the product works for a business professional like themselves. TrustRadius provides that in a transparent way, so buyers can make confident decisions, even about enterprise-grade software.”

The recent swing in the digital world towards data protection and people getting increasingly aware of how their own personal details are used in ways they never intended, has presented an interesting challenge for the world of online services. Most of us don’t like getting marketing and will generally opt out of any “yes, I consent to getting updates from XYZ and its partners!” boxes — if we happen to spot them amid the dark patterning of the net.

TrustRadius and companies like it have an opportunity through that, though: by targeting IT buyers who have to make complicated purchasing decisions and most likely more than one, and in a way that ensures each purchase works with the rest of an existing tech stack, they represent one of the rare cases of where a user might actually want to hear more.

Indeed, one of the company’s plans longer term is to continue developing how it can work with its users through that IT lifecycle by providing suggestions of software based on previous software purchases and also what that user’s feedback has been around a past purchase.

“From day one we have been deal with complex purchasing decisions,” Bhagat said. “Buying technology that will be used to run your business is not the same as buying an app that you use casually. It can be make or break for your company.”


By Ingrid Lunden

AlphaSense, a search engine for analysis and business intel, raises $50M led by Innovation Endeavors

Google and its flagship search portal opened the door to the possibilities of how to build a business empire on the back of organising and navigating the world’s information, as found on the internet. Now, a startup that’s built a search engine tailored to the needs of enterprises and their own quests for information has raised a round of funding to see if it can do the same for the B2B world.

AlphaSense, which provides a way for companies to quickly amass market intelligence around specific trends, industries and more to help them make business decisions, has closed a $50 million round of funding, a Series B that it’s planning to use to continue enhancing its product and expanding to more verticals.

Today, the company today counts some 1,000 clients on its books, with a heavy emphasis on investment banks and related financial services companies. That’s in part because of how the company got its start: Finnish co-founder and CEO Jaakko (Jack) Kokko he had been an analyst at Morgan Stanley in a past life and understood the labor and time pain points of doing market research, and decided to build a platform to help shorted a good part of the information gathering process.

“My experience as an analyst on Wall Street showed me just how fragmented information really was,” he said in an interview, citing as one example how complex sites like those of the FDA are not easy to navigate to look for new information an updates — the kind of thing that a computer would be much more adept at monitoring and flagging. “Even with the best tools and services, it still was really hard to manually get the work done, in part because of market volatility and the many factors that cause it. We can now do that with orders of magnitude more efficiency. Firms can now gather information in minutes that would have taken an hour. AlphaSense does the work of the best single analyst, or even a team of them.”

(Indeed, the “alpha” of AlphaSense appears to be a reference to finance: it’s a term that refers to the ability of a trader or portfolio manager to beat the typical market return.)

The lead investor in this round is very notable and says something about the company’s ambitions. It’s Innovation Endeavors, the VC firm backed by Eric Schmidt, who had been the CEO of none other than Google (the pace-setter and pioneer of the search-as-business model) for a decade, and then stayed on as chairman and ultimately board member of Google and then Alphabet (its later holding company) until just last June.

Schmidt presided over Google at what you could argue was its most important time, gaining speed and scale and transitioning from an academic idea into full-fledged, huge public business whose flagship product has now entered the lexicon as a verb and (through search and other services like Android and YouTube) is a mainstay of how the vast majority of the world uses the web today. As such he is good at spotting opportunities and gaps in the market, and while enterprise-based needs will never be as prominent as those of mass-market consumers, they can be just as lucrative.

“Information is the currency of business today, but data is overwhelming and fragmented, making it difficult for business professionals to find the right insights to drive key business decisions,” he said in a statement. “We were impressed by the way AlphaSense solves this with its AI and search technology, allowing businesses to proceed with the confidence that they have the right information driving their strategy.”

This brings the total raised by AlphaSense to $90 million, with other investors in this round including Soros Fund Management LLC and other unnamed existing investors. Previous backers had included Tom Glocer (the former Reuters CEO who himself is working on his own fintech startup, a security firm called BlueVoyant), the MassChallenge incubator, Tribeca Venture Partners and others. Kokko said AlphaSense is not disclosing its valuation at this point. (I’m guessing though that it’s definitely on the up.)

There have been others that have worked to try to tackle the idea of providing more targeted, and business focused search portals, from the likes of Wolfram Alpha (another alpha!) through to Lexis Nexis and others like Bloomberg’s terminals, FactSet, Business Quant and many more.

One interesting aspect of AlphaSense is how it’s both focused on pulling in requests as well as set up to push information to its users based on previous search parameters. Currently these are set up to only provide information, but over time, there is a clear opportunity to build services to let the engines take on some of the actions based on that information, such as adjusting asking prices for sales and other transactions.

“There are all kinds of things we could do,” said Kokko. “This is a massive untapped opportunity. But we’re not taking the human out of the loop, ever. Humans are the right ones to be making final decisions, and we’re just about helping them make those faster.”


By Ingrid Lunden

OneTrust raises $200M at a $1.3B valuation to help organizations navigate online privacy rules

GDPR, and the newer California Consumer Privacy Act, have given a legal bite to ongoing developments in online privacy and data protection: it’s always good practice for companies with an online presence to take measures to safeguard people’s data, but now failing to do so can land them in some serious hot water.

Now — to underscore the urgency and demand in the market — one of the bigger companies helping organizations navigate those rules is announcing a huge round of funding. OneTrust, which builds tools to help companies navigate data protection and privacy policies both internally and with its customers, has raised $200 million in a Series A led by Insight that values the company at $1.3 billion.

It’s an outsized round for a Series A, being made at an equally outsized valuation — especially considering that the company is only three years old — but that’s because, according to CEO Kabir Barday, of the wide-ranging nature of the issue, and OneTrust’s early moves and subsequent pole position in tackling it.

“We’re talking about an operational overhaul in a company’s practices,” Barday said in an interview. “That requires the right technology and reach to be able to deliver that at a low cost.” Notably, he said that OneTrust wasn’t actually in search of funding — it’s already generating revenue and could have grown off its own balance sheet — although he noted that having the capitalization and backing sends a signal to the market and in particular to larger organizations of its stability and staying power.

Currently, OneTrust has around 3,000 customers across 100 countries (and 1,000 employees), and the plan will be to continue to expand its reach geographically and to more businesses. Funding will also go towards the company’s technology: it already has 50 patents filed and another 50 applications in progress, securing its own IP in the area of privacy protection.

OneTrust offers technology and services covering three different aspects of data protection and privacy management.

Its Privacy Management Software helps an organization manage how it collects data, and it generates compliance reports in line with how a site is working relative to different jurisdictions. Then there is the famous (or infamous) service that lets internet users set their preferences for how they want their data to be handled on different sites. The third is a larger database and risk management platform that assesses how various third-party services (for example advertising providers) work on a site and where they might pose data protection risks.

These are all provided either as a cloud-based software as a service, or an on-premises solution, depending on the customer in question.

The startup also has an interesting backstory that sheds some light on how it was founded and how it identified the gap in the market relatively early.

Alan Dabbiere, who is the co-chairman of OneTrust, had been the chairman of Airwatch — the mobile device management company acquired by VMware in 2014 (Airwatch’s CEO and founder, John Marshall, is OneTrust’s other co-chairman). In an interview, he told me that it was when they were at Airwatch — where Barday had worked across consulting, integration, engineering and product management — that they began to see just how a smartphone “could be a quagmire of information.”

“We could capture apps that an employee was using so that we could show them to IT to mitigate security risks,” he said, “but that actually presented a big privacy issue. If [the employee] has dyslexia [and uses a special app for it] or if the employee used a dating app, you’ve now shown things to IT that you shouldn’t have.”

He admitted that in the first version of the software, “we weren’t even thinking about whether that was inappropriate, but then we quickly realised that we needed to be thinking about privacy.”

Dabbiere said that it was Barday who first brought that sensibility to light, and “that is something that we have evolved from.” After that, and after the VMware sale, it seemed a no-brainer that he and Marshall would come on to help the new startup grow.

Airwatch made a relatively quick exit, I pointed out. His response: the plan is to stay the course at OneTrust, with a lot more room for expansion in this market. He describes the issues of data protection and privacy as “death by 1,000 cuts.” I guess when you think about it from an enterprising point of view, that essentially presents 1,000 business opportunities.

Indeed, there is obvious growth potential to expand not just its funnel of customers, but to add in more services, such as proactive detection of malware that might leak customers’ data (which calls to mind the recently-fined breach at British Airways), as well as tools to help stop that once identified.

While there are a million other companies also looking to fix those problems today, what’s interesting is the point from which OneTrust is starting: by providing tools to organizations simply to help them operate in the current regulatory climate as good citizens of the online world.

This is what caught Insight’s eye with this investment.

“OneTrust has truly established themselves as leaders in this space in a very short timeframe, and are quickly becoming for privacy professionals what Salesforce became for salespeople,” said Richard Wells of Insight. “They offer such a vast range of modules and tools to help customers keep their businesses compliant with varying regulatory laws, and the tailwinds around GDPR and the upcoming CCPA make this an opportune time for growth. Their leadership team is unparalleled in their ambition and has proven their ability to convert those ambitions into reality.”

Wells added that while this is a big round for a Series A it’s because it is something of an outlier — not a mark of how Series A rounds will go soon.

“Investors will always be interested in and keen to partner with companies that are providing real solutions, are already established and are led by a strong group of entrepreneurs,” he said in an interview. “This is a company that has the expertise to help solve for what could be one of the greatest challenges of the next decade. That’s the company investors want to partner with and grow, regardless of fund timing.”


By Ingrid Lunden

Signavio raises $177M at a $400M valuation for its business process automation solutions

Robotic Process Automation has been the name of the game in enterprise software lately — with organizations using advances in machine learning algorithms and other kinds of AI, alongside big-data analytics to speed up everything from performing mundane tasks to more complex business decisions.

To underscore the opportunity and growth in the market, today a startup in the wider segment of process automation is announcing a significant fundraise. Signavio, a company founded out of Berlin that provides tools for business process management — “providing the ‘P’ in RPA,” as the company describes it — has picked up an investment of $177 million at what we understand is a valuation of $400 million.

This round is large on its own, but even more so considering that before this the company — founded in 2009 — had only raised around $50 million before now, according to data from PitchBook. This latest capital injection is being led by Apax Digital (the growth equity team of Apax Partners), with DTCP. It notes that existing investor Summit Partners is also keeping a stake in the business with this deal.

The company was founded by a team of alums from the Hasso Plattner Institute in Potsdam, Germany, who used research they did there for creating the world’s first web modeller for business process management and analytics as the template for Signavio’s own Process Manager. (The name “Signavio” seems to be a portmanteau of “navigating through signals”, which essentially explains the basics of what BPM aims to do to help a business with its decision-making.)

Partly because it’s raised so little money, Signavio has been somewhat under the radar, but it has seen a huge amount of growth. It says that revenues in the last 12 months have grown by more than 70%, and its software  is used by more than one million users across 1,300 customers — with clients including SAP, DHL, Liberty Mutual, Deloitte, Comcast and Puma. It counts Silicon Valley as its second HQ these days, that trajectory will be followed further with this latest funding: Signavio says the funding in part will be going to international expansion of the business.

“10 years ago, we set out on a journey to tackle the time-consuming practices that limit business productivity,” said Dr. Gero Decker, CEO and co-founder of Signavio, in a statement. “This significant new investment further validates our approach to solve business problems faster and more efficiently, unleashing the power of process through our unique Business Transformation Suite. We are thrilled to welcome Apax Digital as our new lead partner, and look forward to building upon our success to date by leveraging our partners’ operating capabilities and global platforms for our international expansion.”

The other area of investment will be the company’s technology suite. While BPM has been around for years as a concept — and indeed there are a number of other companies that provide tools that are compared sometimes to Signavio’s such from biggies like IBM and Microsoft through to Kissflow and others — what’s interesting is how it’s had a surge of interest more recently as organizations increasingly start to add more automation into their IT infrastructure, in part to reduce the human labor needed for more mundane back-office tasks, and in part to reduce costs and speed up processes.

Robotic process automation companies like UiPath and Blue Prism bring some of the same processing tools to the table as Signavio, although the argument is that the latter — which says it helps to “mine, model, monitor, manage and maintain” customers’ data — provides a more sophisticated level of data crunching that can be used for RPA, or for other ends. (It also works with several of the big RPA players, mainly Blue Prism but also UiPath and Automation Anywhere.)

“As businesses have become more global, and workforces more distributed, business processes have proliferated, and become more complex,” noted Daniel O’Keefe, Managing Partner, and Mark Beith, Managing Director, of Apax Digital, in a joint statement. “Signavio’s cloud-native suite allows employees across an enterprise to collaborate and transform their businesses by digitizing, optimizing and ultimately automating their processes. We are tremendously excited to partner with the Signavio team and to support their vision.” The two will also be joining Signavio’s board with this round.


By Ingrid Lunden

Anvyl, looking to help D2C brands manage their supply chain, raises $9.3M

Growing D2C brands face an interesting challenge. While they’ve eliminated much of the hassle of a physical storefront, they must still deal with all the complications involved in managing inventory and manufacturing and shipping a physical product to suppliers.

Anvyl, with a fresh $9.3 million in Series A funding, is looking to jump in and make a difference for those brands. The company, co-founded by chief executive Rodney Manzo, is today announcing the raise, led by Redpoint Ventures, with participation from existing investors First Round Capital and Company Ventures. Angel investors Kevin Ryan (MongoDB and DoubleClick), Ben Kaufman (Quirky and Camp) and Dan Rose (Facebook) also participated in the round.

Manzo hails from Apple, where with $300 million in spend to manage logistics and supply chain he was still operating in an Excel spreadsheet. He then went to Harry’s, where he shaved $10 million in cash burn in his first month. He says himself that sourcing, procurement and logistics are in his DNA.

Which brings us to Anvyl. Anvyl looks at every step in the logistics process, from manufacture to arrival at the supplier, and visualizes that migration in an easy-to-understand UI.

The difference between Anvyl and other supply chain logistics companies, such as Flexport, is that Anvyl goes all the way to the very beginning of the supply chain: the factories. The company partners with factories to set up cameras and sensors that let brands see their product actually being built.

“When I was at Apple, I traveled for two years at least once a month to China and Japan just to oversee production,” said Manzo. “To oversee production, you essentially have to be boots on the ground and eyes in the factory. None of our brands have traveled to a factory.”

On the other end of the supply chain, Anvyl lets brands manage suppliers, find new suppliers, submit RFQs, see cost breakdowns and accept quotes.

The company also looks at each step in between, including trucks, trains, boats and planes so that brands can see, in real time, their products go from being manufactured to delivery.

Anvyl charges brands a monthly fee using a typical SaaS model. On the other end, Anvyl takes a “tiny percentage” of goods being produced within the Anvyl marketplace. The company declined to share actual numbers around pricing.

This latest round brings Anvyl’s total funding to $11.8 million. The company plans to use the funding toward hiring in engineering and marketing, and grow its consumer goods customer base.


By Jordan Crook