Apr
16
2019
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Leapwork raises $10M for its easy process automation platform, plans US expansion

Most work involving computers is highly repetitive, which is why companies regularly have developers write code to automate repetitive tasks. But that process is not very scalable. Ideally, individuals across an entire business would be able to create automated tasks, not just developers. This problem has created a new category called process automation. Startups in this space are all about making companies more efficient.
Most of the existing tools on the market are code-based and complicated, which tends to make it tough for non-technical people to automate anything. Ideally, you would allow them to train software robots to handle repetitive and mundane tasks.

This is the aim of Leapwork, which today announces a Series A investment of $10 million, from London’s DN Capital and e.ventures out of Berlin. The company already has many clients, from tier-one banks and global healthcare firms to aerospace and software companies, and now plans to expand in the U.S. Its customers typically already have a lot of experience with tools such as Tricentis, MicroFocus, UiPath and BluePrism, but employ Leapwork when code-based tools prove limiting.

Founded in 2015 and launched in April 2017, Leapwork has an entirely visual system, backed by a modern tech stack. Instead of using developer time, staff automate tasks themselves, without writing any code, with a simple user interface that is likened to learning PowerPoint or Excel. Leapwork estimates it can save 75 percent of an employee’s time.

Christian Brink Frederiksen, Leapwork’s CEO and co-founder said: “About half of our business comes from the U.S. and this investment will enable us to serve those customers better, as well as reaching new ones.”

Leapwork has found traction in the areas of software testing, data migration and robotic process automation in finance and healthcare. Based in Copenhagen, Denmark, Leapwork has offices in London, U.K., San Francisco, USA, Minsk, Belarus, and Gurugram, India.

Thomas Rubens, of DN Capital, said: “From the outset we were impressed by Leapwork’s product, which we believe will change the automation landscape. Every company has repetitive tasks that could be automated and few have the developer resource to make it happen.”

The founders began in June 2015 in Copenhagen, Denmark, after having worked for almost two decades in enterprise software and business-critical IT. They launched their first pilot in July 2016 and, after working with Global2000 pilot customers in the U.S. and Europe, went live with the Leapwork automation platform in March 2017.

Prior to this funding the company was bootstrapped by the founders, as both had previous successful exits.

Apr
11
2019
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Rasa raises $13M led by Accel for its developer-friendly open-source approach to chatbots

Conversational AI and the use of chatbots have been through multiple cycles of hype and disillusionment in the tech world. You know the story: first you get a launch from the likes of Apple, Facebook, Microsoft, Amazon, Google or any number of other companies, and then you get the many examples of how their services don’t work as intended at the slightest challenge. But time brings improvements and more focused expectations, and today a startup that has been harnessing all those learnings is announcing funding to take to the next level its own approach to conversational AI.

Rasa, which has built an open-source platform for third parties to design and manage their own conversational (text or voice) AI chatbots, is today announcing that it has raised $13 million in a Series A round of funding led by Accel, with participation from Basis Set Ventures, Greg Brockman (co-founder & CTO OpenAI), Daniel Dines (founder & CEO UiPath) and Mitchell Hashimoto (co-founder & CTO Hashicorp).

Rasa was founded in Berlin, but with this round, it will be moving its headquarters to San Francisco, with a plan to hire more people there in sales, marketing and business development; and to continue its tech development with its roadmap including plans to expand the platform to cover images, too.

The company was founded 2.5 years ago, by co-founder/CEO Alex Weidauer’s own admission “when chatbot hype was at its peak.”

Rasa itself was not immune to it, too: “Everyone wanted to automate conversations, and so we set out to build something, too,” he said. “But we quickly realised it was extremely hard to do and that the developer tools were just not there yet.”

Rather than posing an insurmountable roadblock, the shortcomings of chatbots became the problem that Rasa set out to fix.

Alan Nichols, the co-founder who is now the CTO, is an AI PhD, not in natural language as you might expect, but in machine learning.

“What we do is more is address this as a mathematical, machine learning problem rather than one of language,” Weidauer said. Specifically, that means building a model that can be used by any company to tap its own resources to train their bots, in particular with unstructured information, which has been one of the trickier problems to solve in conversational AI.

At a time when many have raised concerns about who might “own” the progress of artificial intelligence, and specifically the data that goes into building these systems, Rasa’s approach is a refreshing one.

Typically, when an organization wants to build an AI chatbot either to interact with customers or to run something in the back end of their business, their developers most commonly opt for third-party cloud APIs that have restrictions on how they can be customized, or they build their own from scratch — but if the organization is not already a large tech company, it will be challenged to have the human or other resources to execute this.

Rasa underscores an emerging trend for a strong third contender. The company has built a stack of tools that it has open-sourced, meaning that anyone can (and thousands of developers do) use it for free, with a paid enterprise version that includes extra tools, including customer support, testing and training tools, and production container deployment. (It’s priced depending on size of organization and usage.)

Importantly, whichever package is used, the tools run on a company’s own training data; and the company can ultimately host their bots wherever they choose, which have been some of the unique selling points for those using Rasa’s platform, when they are less interested in working with organizations that might also be competitors.

Adobe’s new AI assistant for searching on Adobe Stock, which has some 100 million images, was built on Rasa.

“We wanted to give our users an AI assistant that lets them search with natural language commands,” said Brett Butterfield, director of software development at Adobe, in a statement. “We looked at several online services, and, in the end, Rasa was the clear choice because we were able to host our own servers and protect our user’s data privacy. Being able to automate full conversations and the fact it is open source were key elements for us.”

Other customers include Parallon and TalkSpace, Zurich and Allianz, Telekom and UBS.

Open source has become big business in the last several years, and so a startup that’s built an AI platform that has a very direct application in the enterprise built on it presents an obvious attraction for VCs.

“Automation is the next battleground for the enterprise, and while this is a very difficult space to win, especially for unstructured information like text and voice, we are confident Rasa has what it takes given their impressive adoption by developers,” said Andrei Brasoveanu, partner at Accel, in a statement.

“Existing solutions don’t let in-house developer teams control their own automation destiny. Rasa is applying commercial open source software solutions for AI environments similarly to what open source leaders such as Cloudera, Mulesoft, and Hashicorp have done for others.”

Apr
05
2019
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Peter Kraus dishes on the market

During my recent conversation with Peter Kraus, which was supposed to be focused on Aperture and its launch of the Aperture New World Opportunities Fund, I couldn’t help veering off into tangents about the market in general. Below is Kraus’ take on the availability of alpha generation, the Fed, inflation versus Amazon, housing, the cross-ownership of U.S. equities by a few huge funds and high-frequency trading.

Gregg Schoenberg: Will alpha be more available over the next five years than it has been over the last five?

To think that at some point equities won’t become more volatile and decline 20% to 30%… I think it’s crazy.

Peter Kraus: Do I think it’s more available in the next five years than it was in the last five years? No. Do I think people will pay more attention to it? Yes, because when markets are up to 30 percent, if you get another five, it doesn’t matter. When markets are down 30 percent and I save you five by being 25 percent down, you care.

GS: Is the Fed’s next move up or down?

PK: I think the Fed does zero, nothing. In terms of its next interest rate move, in my judgment, there’s a higher probability that it’s down versus up.

Apr
03
2019
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Onfido, which verifies IDs using AI, nabs $50M from SoftBank, Salesforce, Microsoft and more

Security breaches, where malicious hackers obtain snippets of information that then get used to impersonate individuals in order to gain access to individuals’ and businesses’ sensitive financial and other private information, have become par for the course in the world of digital services. More than 2.7 billion records were  breached in a single incident this year in the US, and overall the damage from incidents like these potentially runs into the trillions of dollars globally.

Today, a startup called Onfido, which uses AI techniques combined with human verifiers to efficiently verify people are who they say they are when using digital services — is today announcing $50 million in funding to help address that ongoing — and growing — problem.

The funding comes on the heels of some very strong growth for the startup, which was founded in London but now operates most of its business out of San Francisco. In an interview, co-founder and CEO Husayn Kassai said that more than half of its customers, and most of its new growth, is coming out of the US.

Onfido uses computer vision and a number of other AI-based technologies to verify against some 4,500 different types of identity documents, using techniques like “facial liveness testing,” to see patterns invisible to the human eye, now has 1,500 businesses as customers, primarily in categories like marketplaces and communities, gaming and financial services, including companies like Remitly, Zipcar and Europcar; and in the last year, it had sales growth of 342 percent. Kassai said that it has to date verified “tens of millions” of IDs.

The money — a Series C2, technically — is coming from a group that includes top strategic tech investors. The round is being co-led by SoftBank Investment (SBI) and Salesforce Ventures, with M12 (the new name for Microsoft Ventures), FinVC and other unnamed new and previous investors are also participating. That’s a signal not just of how the biggest companies in that sector today are grappling with this problem, but also what approach they are using to solve it.

For SoftBank, the investment is separate from the Vision fund, founder and CEO Husayn Kassai noted, but it’s notable that a lot of the businesses that have been backed out of that fund — companies like Didi, Uber, Oyo, Lemonade, and others — fundamentally rely on people trusting that they are handling personal details securely while also carefully vetting suppliers on the platform (meaning, they need and use services like Onfido’s).

Meanwhile, both Microsoft and Salesforce have extensive enterprise businesses that could see multiple benefits from working with an identity verification provider, not just for their own purposes, but as a service that is sold on to its customers as part of a larger identity management and security offering.

The company is not revealing its valuation but has raised around $100 million to date and Kassai confirmed that it was an upround, with “a lot of happy investors.”

“We have strong metrics, and we have a long way to go in our growth,” he added.

There are a lot of companies today offering services to help offer secure services to authenticate users, for example, to help them log on to their work accounts or to access their online banking services. Onfido’s business focuses on the first step in all of this — customer onboarding — specifically around services geared towards consumers.

The opportunity that has opened up for it has been the result of more than just a rise in breaches. There’s also been a growing realization that a lot of the existing services that had been used for verification are simply not fit for purpose: either they too have been breached — as in the case of some of the bigger credit agencies like Equifax — or are not realistically efficient enough for how many online services run today, such as in the case of in-person verifications. (Onfido claims that its system can make a verification in as little as 15 seconds.)

Or, they are part of the new guard that has shifted its approach to the business of ID verificiation, either by choice or force. One would-be competitor from the past, Checkr, is now a partner of Onfido’s, Kassai noted. Others like Jumio — which is still grappling with the fallout from major illegal missteps from previous management — seem to still be trying to find their feet as standalone businesses.

“Fraud is rising and not going anywhere,” Kassai — who co-founded the company with Ruhul Amin and Eamon Jubbawy — said. “And the problem is that there are a dozen other companies that have not done a good enough job to detect it so far.” While no service is perfect — Onfido says that its “risk exposure” is 0.0195 percent — he says that the advantage of building its service on top of AI means that the algorithms use every experience to continue honing its accuracy. “What we learn from one client gets applied everywhere,” he notes.

“There has never been a more important time for companies to build trust with their customers by showing they are one step ahead of fraudsters,” said Frank van Veenendaal, the ex-vice chairman of Salesforce, who is joining the board with this round. “I believe Onfido has the unique opportunity to transform the digital identity market and deliver robust and scalable authentication-as-a-service, similar to how Salesforce transformed customer relationship management.”

Apr
02
2019
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Microsoft teams up with BMW for the IoT-focused Open Manufacturing Platform

Car companies are making big investments in technology to help ensure that they are not cut out of the next generation of transportation and automotive manufacturing, and today came the latest development in that trend.

The BMW Group and Microsoft announced they would team up in a new effort called the Open Manufacturing Platform, aimed at developing and encouraging more collaborative IoT development in the manufacturing sector, focusing on smart factory solutions and building standards to develop them in areas like machine connectivity and on-premises systems integration.

The two companies have not disclosed how much they intend to invest in the project — we have sent a message to ask. The plan will be to bring in more manufacturers and suppliers — the goal, they say, is to have between four and six others with them, working on 15 use cases by the end of this year — working with open source components, open industrial standards and open data to develop both hardware and software that runs on it.

The two say that future partners do not have to be from within the automotive industry.

The OMP will be built on Microsoft’s industrial IoT platform — part of its Azure cloud business. But this is a natural progression of how Microsoft and BMW were already working together. BMW already has 3,000 machines running on Azure cloud, IoT and AI services in its existing robots and in-factory autonomous transport systems, and it said it will be contributing some of the technology that it had already built — for example around its self-driving systems — into the group as part of the effort.

“Microsoft is joining forces with the BMW Group to transform digital production efficiency across the industry,” Scott Guthrie, executive vice president, Microsoft Cloud + AI Group, said in a presentation in Germany today. “Our commitment to building an open community will create new opportunities for collaboration across the entire manufacturing value chain.”

“Mastering the complex task of producing individualized premium products requires innovative IT and software solutions,” added Oliver Zipse, member of the Board of Management of BMW AG, Production, a statement. “The interconnection of production sites and systems as well as the secure integration of partners and suppliers are particularly important. We have been relying on the cloud since 2016 and are consistently developing new approaches. With the Open Manufacturing Platform as the next step, we want to make our solutions available to other companies and jointly leverage potential in order to secure our strong position in the market in the long term.”

The problem that Microsoft and BMW are going after here is a longstanding one. Much of the computing in the world of IT has been built around open standards, or in any event on very widely-used proprietary platforms that can interface with each other. The same does not go in the world of manufacturing, where proprietary systems are specific to each manufacturer, making them difficult to modify and often impossible to use in conjunction with other proprietary systems.

That ultimately slows down how things have been able to evolve, and will mean that implementing new generations of technology becomes expensive or even in some cases impossible. And given the speed with which things are moving, and the increasing sophistication of the machines that are being built (cars as “hardware”), something had to change.

That is what BMW and Microsoft are addressing. For BMW it will give it a hand in helping shape how standards develop, and for Microsoft it will give it a potential window into expanding its business in this enterprise sector.

The collaborative approach has been a big one for tech companies hoping to find a common way forward in the future of computing. Microsoft may own a lot of proprietary platforms that are not open source, but it’s making efforts to collaborate more in a number of other ways. It works with SAP, Adobe, WPP and others on the Open Data Initiative; with Intel, Google and others it’s working on an open standard for connecting data centers; it’s part of an open standard initiative for software licensing; and it’s part of a new cross-licensing patent database.

Apr
01
2019
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German LinkedIn rival Xing is rebranding as ‘New Work,’ acquires recruitment platform Honeypot for up to $64M

Xing, the business networking platform that has been described as Germany’s answer to LinkedIn, has made an acquisition to beef up its recruitment business ahead of a rebrand of the business as “New Work.” The company has acquired Honeypot, a German startup that has built a job-hunting platform for tech people, for up to €57 million ($64 million). Xing tells us that Honeypot is its biggest acquisition to date.

The figure includes the acquisition (€22 million) plus a potential earn-out of up to €35 million if certain targets are met in the next three years.

Xing said that it plans to rebrand as New Work in the second half of 2019, bringing together a number of other assets it has acquired and built over the years.

“This acquisition is an excellent addition to our New Work portfolio,” Thomas Vollmoeller, CEO at Xing, said in a statement. “Honeypot focuses on candidates by helping them to find a job matching their individual preferences… With subsidiaries and brands such as kununu and HalloFreelancer, Xing is far more than just a single network. New Work is the umbrella spanning all our business activities.” Xing said that all the smaller companies will keep their branding.

Xing already offered job listings as part of its platform, with 20,000 businesses as customers; but Honeypot will add a few different things to the mix.

First, it will give Xing more traction specifically in the tech vertical, since Honeypot first started out in 2015 targeting developers although it later expanded to other tech jobs.

Second, Honeypot’s structure is a natural fit for a social recuitment platform: as with a lot of social recruiting, Honeypot lets recruiters use platforms, profile pages and social graphics to find and approach candidates, rather than candidates reaching out in response to specific opportunities.

Honeypot adds additional features to help make this process more accurate and less of a waste of time on both sides. Those doing the recruiting have to provide specific details around salary and, say, programming languages required, as part of their outreach. On the other side, individuals go through a “brief expertise check” to vet them, and they too have to be a bit more specific on what they can and what they want to do, and what they want to earn, to help weed out opportunities that might not be suitable.

Third, the acquisition will help Xing make a bigger push into building its profile outside of Germany into more of Europe, as New Work.

This is no small thing. Xing years ago was considered a would-be rival to LinkedIn. But — and this was perhaps even more true in the past, and Xing was founded in 2003 — scaling startups to be global players out of Europe can be a challenge, even more so when there is a formidable direct competitor growing quickly as well.

In the end, Xing developed as a much more modest operation, relatively speaking. While LinkedIn today has some 600 million users and was acquired by Microsoft in 2016 for $26.2 billion, Xing is publicly traded and currently valued at around $2 billion (€1.81 billion), with some 15 million members.

Xing says that today Honeypot’s current emphasis is German-speaking countries and the Netherlands, which together cover some of the biggest startup hubs in Europe, including Berlin and Amsterdam.

The company is still relatively small but growing, adding 1,000 IT specialists to its books each week, with some 100,000 individuals and 1,500 businesses currently registered. Xing said that it will be investing in the company to expand to more markets in Europe, as well as to grow its business by tapping Xing’s own customer base.

Although there have been some notable exceptions like payments startup Adyen from the Netherlands, Farfetch from the UK and Spotify (originally from Stockholm, grown in London and now increasingly a US company), scaling startups in Europe has proven to be challenging.

One of the big reasons why has to do with a shortage of talent to build these companies: in Germany alone — home to the buzzy startup city of Berlin — there are 82,000 unfilled tech jobs. In other words, there is an opportunity for more user-friendly platforms to help connect those dots.

XING and Honeypot both have the vision of helping people to further their career. We want Honeypot to offer the world’s largest work-life community for IT specialists by giving candidates the power to decide on their next career step,” said Kaya Taner, CEO who founded Honeypot with Emma Tracey. “We will continue to pursue this vision with XING. Going forward, around 100,000 IT specialists from all over the world who are registered on Honeypot will be able to connect with the many first-rate employers in German-speaking countries. This will enable Honeypot to continue developing its domestic market, while also further expanding its international community.”

Mar
28
2019
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Kong raises $43M Series C for its API platform

Kong, the open core API management and life cycle management company previously known as Mashape, today announced that it has raised a $43 million Series C round led by Index Ventures. Previous investors Andreessen Horowitz and Charles River Ventures (CRV), as well as new investors GGV Capital and World Innovation Lab, also participated. With this round, Kong has now raised a total of $71 million.

The company’s CEO and co-founder Augusto Marietti tells me the company plans to use the funds to build out its service control platform. He likened this service to the “nervous system for an organization’s software architecture.”

Right now, Kong is just offering the first pieces of this, though. One area the company plans to especially focus on is security, in addition to its existing management tools, where Kong plans to add more machine learning capabilities over time, too. “It’s obviously a 10-year journey, but those two things — immunity with security and machine learning with [Kong] Brain — are really a 10-year journey of building an intelligent platform that can manage all the traffic in and out of an organization,” he said.

In addition, the company also plans to invest heavily in its expansion in both Europe and the Asia Pacific market. This also explains the addition of World Innovation Lab as an investor. The firm, after all, focuses heavily on connecting companies in the U.S. with partners in Asia — and especially Japan. As Marietti told me, the company is seeing a lot of demand in Japan and China right now, so it makes sense to capitalize on this, especially as the Chinese market is about to become more easily accessible for foreign companies.

Kong notes that it doubled its headcount in 2018 and now has more than 100 enterprise customers, including Yahoo! Japan, Ferrari, SoulCycle and WeWork.

It’s worth noting that while this is officially a Series C investment, Marietti is thinking of it more like a Series B round, given that the company went through a major pivot when it moved from being Mashape to its focus on Kong, which was already its most popular open-source tool.

“Modern software is now built in the cloud, with applications consuming other applications, service to service,” said Martin Casado, general partner at Andreessen Horowitz . “We’re at the tipping point of enterprise adoption of microservices architectures, and companies are turning to new open-source-based developer tools and platforms to fuel their next wave of innovation. Kong is uniquely suited to help enterprises as they make this shift by supporting an organization’s entire service architecture, from centralized or decentralized, monolith or microservices.”

Mar
13
2019
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Email app Spark adds delegation feature for teams

Email app Spark added collaboration features back in May 2018. And Readdle, the company behind the app, is going one step further with a new feature specifically designed to delegate an email to one of your colleagues.

While you can already collaborate with your team by sharing emails in Spark, the app is still not as powerful as a dedicated shared email client, such as Front. But delegation brings Spark one step closer to its competitor.

You can now treat emails as tasks with a deadline. If you’re a manager, you’re working with a personal assistant or you’re in charge of everyone’s workload, you can now assign a conversation to a person in particular and send a message to add some context.

On the other end, your colleague receives the conversation in their Spark account, in the “Assigned to Me” tab. They can then start working on that email together with other team members.

As a reminder, Spark lets you discuss email threads with your colleagues in a comment area, @-mention your colleague and add attachments and links. When you know what to say, you can create a draft, ask for feedback and collaborate like in Google Docs.

Delegation is a bit more powerful than simply sharing an email with a colleague. For instance, you can set a due date and mute the conversation. This way, you can hand-off some work and focus on something else.

Spark for Teams uses a software-as-a-service approach. It’s free for small teams and you have to pay $6.39 to $7.99 per user per month to unlock advanced features, such as unlimited email templates and unlimited delegations. Free teams are limited to 10 active delegations at any time.

Mar
12
2019
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Time is Ltd. uses data from Slack and other cloud software to help companies improve productivity

Time is Ltd., a Prague-based startup offering “productivity software analytics” to help companies gain insights from employees’ use of Slack, Office 365, G Suite and other enterprise software, has raised €3 million in funding.

Leading the round is Mike Chalfen — who previously co-founded London venture capital firm Mosaic Ventures but has since decided to operate as a solo investor — with participation from Accel. The investment will be used by Time is Ltd. to continue building the platform for large enterprises that want to better understand the patterns of behaviour hidden inside the various cloud software on which they run.

“Time is Ltd. was founded… to help large corporations and companies get a view into insights and productivity of teams,” co-founder and CEO Jan Rezab tells me. “Visualising insights around calendars, time and communication will help companies to understand real data behind their productivity.”

Powered by machine learning, the productivity software analytics platform plugs into the cloud software tools that enterprises typically use to collaborate across various departments. It then analyses various metadata pulled from these software tools, such as who is communicating with whom and time spent on Slack, or which teams are meeting, where and for how long as per various calendars. The idea is to enable managers to gain a better understanding of where productivity is lost or could be improved and to tie to business goals changes in these patterns.

Rezab cites the example of a large company undergoing “agile” transformation. “If you want to steer a massive company of 5,000 plus people, you really should understand the impact of your actions a bit more much earlier, not after the fact,” he says. “One of the hypothesis of an agile transformation is, for example, that managers really get involved a bit less and things work a bit more streamlined. You see from our data that this is or is not happening, and you can take corrective action.”

Or it could be something as simple as a large company with multiple offices that is conducting too many meetings. Time is Ltd. is able to show how the number of meetings held is increasing and which departments or teams are instigating them. “You can also show the inter-departmental video meeting efficiency, and if the people, for example, often need to travel to these meetings, how long does that takes versus digital meetings — so you can generally help and recommend the company take specific actions,” explains Rezab.

Sales is another area that could benefit from productivity analytics, with Time is Ltd. revealing that most sales teams actually spend the majority of their meeting time inside the company, not outside as you would think. “The structure of these internal meetings varies; planning for these events or just on-boarding and education,” says the Time is Ltd. CEO. “You can, so to speak, follow the time from revenue to different teams… and then see over time how it changes, and how it impacts sales productivity.”

Meanwhile, investor Mike Chalfen describes the young startup as a new breed of data-driven services that use “significant but under-utilised datasets.” “Productivity is one of the largest software markets globally, but lacks deep enterprise analytics to drive intelligent operational management for large businesses,” he says in a statement.

That’s not to say Time is Ltd. isn’t without competition, which includes Microsoft itself. “Our biggest competitor is Microsoft Workplace Analytics,” says Rezab. “However, Microsoft does not integrate other than MS products. Our advantage is that we are a productivity platform to integrate all of the cloud tools. Starting with Slack, SAP Success Factors, Zoom and countless others.”

Feb
19
2019
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Senseon raises $6.4M to tackle cybersecurity threats with an AI ‘triangulation’ approach

Darktrace helped pave the way for using artificial intelligence to combat malicious hacking and enterprise security breaches. Now a new U.K. startup founded by an ex-Darktrace executive has raised some funding to take the use of AI in cybersecurity to the next level.

Senseon, which has pioneered a new model that it calls “AI triangulation” — simultaneously applying artificial intelligence algorithms to oversee, monitor and defend an organization’s network appliances, endpoints and “investigator bots” covering multiple microservices — has raised $6.4 million in seed funding.

David Atkinson — the startup’s CEO and founder who had previously been the commercial director for Darktrace and before that helped pioneer new cybersecurity techniques as an operative at the U.K.’s Ministry of Defense — said that Senseon will use the funding to continue to expand its business both in Europe and the U.S. 

The deal was co-led by MMC Ventures and Mark Weatherford, who is chief cybersecurity strategist at vArmour (which itself raised money in recent weeks) and previously Deputy Under Secretary for Cybersecurity, U.S. Department of Homeland Security. Others in the round included Amadeus Capital Partners, Crane Venture Partners and CyLon, a security startup incubator in London.

As Atkinson describes it, triangulation was an analytics concept first introduced by the CIA in the U.S., a method of bringing together multiple vectors of information to unearth inconsistencies in a data set (you can read more on triangulation in this CIA publication). He saw an opportunity to build a platform that took the same kind of approach to enterprise security.

There are a number of companies that are using AI-based techniques to help defend against breaches — in addition to Darktrace, there is Hexadite (a remediation specialist acquired by Microsoft), Amazon is working in the field and many others. In fact I think you’d be hard-pressed to find any IT security company today that doesn’t claim to or actually use AI in its approach.

Atkinson claims, however, that many AI-based solutions — and many other IT security products — take siloed, single-point approaches to defending a network. That is to say, you have network appliance security products, endpoint security, perhaps security for individual microservices and so on.

But while many of these work well, you don’t always get those different services speaking to each other. And that doesn’t reflect the shape that the most sophisticated security breaches are taking today.

As cybersecurity breaches and identified vulnerabilities continue to grow in frequency and scope — with hundreds of millions of individuals’ and organizations’ data potentially exposed in the process, systems disabled, and more — we’re seeing an increasing amount of sophistication on the part of the attackers.

Yes, those malicious actors employ artificial intelligence. But — as described in this 2019 paper on the state of cybersecurity from Symantec — they are also taking advantage of bigger “surface areas” with growing networks of connected objects all up for grabs; and they are tackling new frontiers like infiltrating data in transport and cloud-based systems. (In terms of examples of new frontiers, mobile networks, biometric data, gaming networks, public clouds and new card-skimming techniques are some of the specific areas that Experian calls out.)

Senseon’s antidote has been to build a new platform that “emulates how analysts think,” said Atkinson. Looking at an enterprise’s network appliance, an endpoint and microservices in the cloud, the Senseon platform “has an autonomous conversation” using the source data, before it presents a conclusion, threat, warning or even breach alert to the organization’s security team.

“We have an ability to take observations and compare that to hypothetical scenarios. When we tell you something, it has a rich context,” he said. Single-point alternatives essentially can create “blind spots that hackers manoeuvre around. Relying on single-source intelligence is like tying one hand behind your back.”

After Senseon compiles its data, it sends out alerts to security teams in a remediation service. Interestingly, while the platform’s aim is to identify malicious activity in a network, another consequence of what it’s doing is to help organizations identify “false positives” that are not actually threats, to cut down on time and money that get wasted on investigating those.

“Organisations of all sizes need to get better at keeping pace with emerging threats, but more importantly, identifying the attacks that require intervention,” said Mina Samaan of MMC Ventures in a statement. “Senseon’s technology directly addresses this challenge by using reinforcement learning AI techniques to help over-burdened security teams better understand anomalous behaviour through a single holistic platform.”

Although Senseon is only announcing seed funding today, the company has actually been around since 2017 and already has customers, primarily in the finance and legal industries (it would only give out one customer reference, the law firm of Harbottle & Lewis).

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