Espressive lands $30M Series B to build better help chatbots

Espressive, a four-year-old startup from former ServiceNow employees, is working to build a better chatbot to reduce calls to company help desks. Today, the company announced a $30 million Series B investment.

Insight Partners led the round with help from Series A lead investor General Catalyst along with Wing Venture Capital. Under the terms of today’s agreement, Insight founder and managing director Jeff Horing will be joining the Espressive Board. Today’s investment brings the total raised to $53 million, according to the company.

Company founder and CEO Pat Calhoun says that when he was at ServiceNow he observed that, in many companies, employees often got frustrated looking for answers to basic questions. That resulted in a call to a Help Desk requiring human intervention to answer the question.

He believed that there was a way to automate this with AI-driven chatbots, and he founded Espressive to develop a solution. “Our job is to help employees get immediate answers to their questions or solutions or resolutions to their issues, so that they can get back to work,” he said.

They do that by providing a very narrowly focused natural language processing (NLP) engine to understand the question and find answers quickly, while using machine learning to improve on those answers over time.

“We’re not trying to solve every problem that NLP can address. We’re going after a very specific set of use cases which is really around employee language, and as a result, we’ve really tuned our engine to have the highest accuracy possible in the industry,” Calhoun told TechCrunch.

He says what they’ve done to increase accuracy is combine the NLP with image recognition technology. “What we’ve done is we’ve built our NLP engine on top of some image recognition architecture that’s really designed for a high degree of accuracy and essentially breaks down the phrase to understand the true meaning behind the phrase,” he said.

The solution is designed to provide a single immediate answer. If, for some reason, it can’t understand a request, it will open a help ticket automatically and route it to a human to resolve, but they try to keep that to a minimum. He says that when they deploy their solution, they tune it to the individual customers’ buzzwords and terminology.

So far they have been able to reduce help desk calls by 40% to 60% across customers with around 85% employee participation, which shows that they are using the tool and it’s providing the answers they need. In fact, the product understands 750 million employee phrases out of the box.

The company was founded in 2016. It currently has 65 employees and 35 customers, but with the new funding, both of those numbers should increase.


By Ron Miller

Nvidia acquires data storage and management platform SwiftStack

Nvidia today announced that it has acquired SwiftStack, a software-centric data storage and management platform that supports public cloud, on-premises and edge deployments.

The company’s recent launches focused on improving its support for AI, high-performance computing and accelerated computing workloads, which is surely what Nvidia is most interested in here.

“Building AI supercomputers is exciting to the entire SwiftStack team,” says the company’s co-founder and CPO Joe Arnold in today’s announcement. “We couldn’t be more thrilled to work with the talented folks at NVIDIA and look forward to contributing to its world-leading accelerated computing solutions.”

The two companies did not disclose the price of the acquisition, but SwiftStack had previously raised about $23.6 million in Series A and B rounds led by Mayfield Fund and OpenView Venture Partners. Other investors include Storm Ventures and UMC Capital.

SwiftStack, which was founded in 2011, placed an early bet on OpenStack, the massive open-source project that aimed to give enterprises an AWS-like management experience in their own data centers. The company was one of the largest contributors to OpenStack’s Swift object storage platform and offered a number of services around this, though it seems like in recent years, it has downplayed the OpenStack relationship as that platform’s popularity has fizzled in many verticals.

SwiftStack lists the likes of PayPal, Rogers, data center provider DC Blox, Snapfish and Verizon (TechCrunch’s parent company) on its customer page. Nvidia, too, is a customer.

SwiftStack notes that it team will continue to maintain existing set of open source tools like Swift, ProxyFS, 1space and Controller.

“SwiftStack’s technology is already a key part of NVIDIA’s GPU-powered AI infrastructure, and this acquisition will strengthen what we do for you,” says Arnold.


By Frederic Lardinois

YC-backed Turing uses AI to help speed up the formulation of new consumer packaged goods

One of the more interesting and useful applications of artificial intelligence technology has been in the world of biotechnology and medicine, where now more than 220 startups (not to mention universities and bigger pharma companies) are using AI to accelerate drug discovery by using it to play out the many permutations resulting from drug and chemical combinations, DNA and other factors.

Now, a startup called Turing — which is part of the current cohort at Y Combinator due to present in the next Demo Day on March 22 — is taking a similar principle but applying it to the world of building (and ‘discovering’) new consumer packaged goods products.

Using machine learning to simulate different combinations of ingredients plus desired outcomes to figure out optimal formulations for different goods (hence the “Turing” name, a reference to Alan Turing’s mathematical model, referred to as the Turing machine), Turing is initially addressing the creation of products in home care (eg detergents), beauty, and food and beverage.

Turing’s founders claim that it is able to save companies millions of dollars by reducing the average time it takes to formulate and test new products, from an average of 12 to 24 months down to a matter of weeks.

Specifically, the aim is to reduce all the time that it takes to test combinations, giving R&D teams more time to be creative.

“Right now, they are spending more time managing experiments than they are innovating,” Manmit Shrimali, Turing’s co-founder and CEO, said.

Turing is in theory coming out of stealth today, but in fact it has already amassed an impressive customer list. It is already generating revenues by working with 8 brands owned by one of the world’s biggest CPG companies, and it is also being trialled by another major CPG behemoth (Turing is disclosing their names publicly, but suffice it to say, they and their brands are household names).

Turing is co-founded by Shrimali and Ajith Govind, two specialists in data science that had worked together on a previous startup called Dextro Analytics. Dextro had set out to help businesses use AI and other kinds of business analytics to help with identifying trends and decision making around marketing, business strategy and other operational areas.

While there, they identified a very specific use case for the same principles that was perhaps even more acute: the research and development divisions of CPG companies, which have (ironically, given their focus on the future) often been behind the curve when it comes to the “digital transformation” that has swept up a lot of other corporate departments.

“We were consulting for product companies and realised that they were struggling,” Shirmali said. Add to that the fact that CPG is precisely the kind of legacy industry that is not natively a tech company but can most definitely benefit from implementing better technology, and that spells out an interesting opportunity for how (and where) to introduce artificial intelligence into the mix.

R&D labs play a specific and critical role in the world of CPG.

Before eventually being shipped into production, this is where products are discovered; tested; tweaked in response to input from customers, marketing, budgetary and manufacturing departments and others; then tested again; then tweaked again; and so on. One of the big clients that Turing works with spends close to $400 million in testing alone.

But R&D is under a lot of pressure these days. While these departments are seeing their budgets getting cut, they continue to have a lot of demands. They are still being expected to meet timelines in producing new products (or often more likely, extensions of products) to keep consumers interested. There are a new host of environmental and health concerns around goods with huge lists of unintelligible ingredients, meaning they have to figure out how to simplify and improve the composition of mass-market products. And smaller direct-to-consumer brands are undercutting their larger competitors by getting to market faster with competitive offerings that have met new consumer tastes and preferences.

“In the CPG world, everyone was focused on marketing, and R&D was a blind spot,” Shrimali said, referring to the extensive investments that CPG have made into figuring out how to use digital to track and connect with users, and also how better to distribute their products. “To address how to use technology better in R&D, people need strong domain knowledge, and we are the first in the market to do that.”

Turing’s focus is to speed up the formulation and testing aspects that go into product creation to cut down on some of the extensive overhead that goes into putting new products into the market.

Part of the reason why it can take upwards of years to create a new product is because of all of the permutations that go into building something and making sure it works consistently as a consumer would expect it to (which still being consistent in production and coming in within budget).

“If just one ingredient is changed in a formulation, it can change everything,” Shirmali noted. And so in the case of something like a laundry detergent, this means running hundreds of tests on hundreds of loads of laundry to make sure that it works as it should.

The Turing platform brings in historical data from across a number of past permutations and tests to essentially virtualise all of this: it suggests optimal mixes and outcomes from them without the need to run the costly physical tests, and in turn this teaches the Turing platform to address future tests and formulations. Shrimali said that the Turing platform has already saved one of the brands some $7 million in testing costs.

Turing’s place in working with R&D gives the company some interesting insights into some of the shifts that the wider industry is undergoing. Currently, Shrimali said one of the biggest priorities for CPG giants include addressing the demand for more traceable, natural and organic formulations.

While no single DTC brand will ever fully eat into the market share of any CPG brand, collectively their presence and resonance with consumers is clearly causing a shift. Sometimes that will lead into acquisitions of the smaller brands, but more generally it reflects a change in consumer demands that the CPG companies are trying to meet. 

Longer term, the plan is for Turing to apply its platform to other aspects that are touched by R&D beyond the formulations of products. The thinking is that changing consumer preferences will also lead into a demand for better “formulations” for the wider product, including more sustainable production and packaging. And that, in turn, represents two areas into which Turing can expand, introducing potentially other kinds of AI technology (such as computer vision) into the mix to help optimise how companies build their next generation of consumer goods.


By Ingrid Lunden

Google Cloud announces four new regions as it expands its global footprint

Google Cloud today announced its plans to open four new data center regions. These regions will be in Delhi (India), Doha (Qatar), Melbourne (Australia) and Toronto (Canada) and bring Google Cloud’s total footprint to 26 regions. The company previously announced that it would open regions in Jakarta, Las Vegas, Salt Lake City, Seoul and Warsaw over the course of the next year. The announcement also comes only a few days after Google opened its Salt Lake City data center.

GCP already had a data center presence India, Australia and Canada before this announcement, but with these newly announced regions, it now offers two geographically separate regions for in-country disaster recovery, for example.

Google notes that the region in Doha marks the company’s first strategic collaboration agreement to launch a region in the Middle East with the Qatar Free Zones Authority. One of the launch customers there, is Bespin Global, a major manages services provider in Asia.

“We work with some of the largest Korean enterprises, helping to drive their digital transformation initiatives. One of the key requirements that we have is that we need to deliver the same quality of service to all of our customers around the globe,” said John Lee, CEO, Bespin Global. “Google Cloud’s continuous investments in expanding their own infrastructure to areas like the Middle East make it possible for us to meet our customers where they are.”


By Frederic Lardinois

Google cancels Cloud Next because of coronavirus, goes online-only

Google today announced that it is canceling the physical part of Cloud Next, its cloud-focused event and its largest annual conference by far with around 30,000 attendees, over concerns around the current spread of COVID-19.

Given all of the recent conference cancellations, this announcement doesn’t come as a huge surprise, especially after Facebook canceled its F8 developer conference only a few days ago.

Cloud Next was scheduled to run from Apri 6 to 8. Instead of the physical event, Google will now host an online event under the “Google Cloud Next ’20: Digital Connect” moniker. So there will still be keynotes and breakout sessions, as well as the ability to connect with experts.

“Innovation is in Google’s DNA and we are leveraging this strength to bring you an immersive and inspiring event this year without the risk of travel,” the company notes in today’s announcement.

The virtual event will be free and in an email to attendees, Google says that it will automatically refund all tickets to this year’s conference. It will also automatically cancel all hotel reservations made through its conference reservation system.

It now remains to be seen what happens to Google’s other major conference, I/O, which is slated to run from May 12 to 14 in Mountain View. The same holds true for Microsoft’s rival Build conference in Seattle, which is scheduled to start on May 19. These are the two premier annual news events for both companies, but given the current situation, nobody would be surprised if they got canceled, too.


By Frederic Lardinois

Microsoft’s Cortana drops consumer skills as it refocuses on business users

With the next version of Windows 10, coming this spring, Microsoft’s Cortana digital assistant will lose a number of consumer skills around music and connected homes, as well as some third-party skills. That’s very much in line with Microsoft’s new focus for Cortana, but it may still come as a surprise to the dozens of loyal Cortana fans.

Microsoft is also turning off Cortana support in its Microsoft Launcher on Android by the end of April and on older versions of Windows that have reached their end-of-service date, which usually comes about 36 months after the original release.

cortana

As the company explained last year, it now mostly thinks of Cortana as a service for business users. The new Cortana is all about productivity, with deep integrations into Microsoft’s suite of Office tools, for example. In this context, consumer services are only a distraction, and Microsoft is leaving that market to the likes of Amazon and Google .

Because the new Cortana experience is all about Microsoft 365, the subscription service that includes access to the Office tools, email, online storage and more, it doesn’t come as a surprise that the assistant’s new feature will give you access to data from these tools, including your calendar, Microsoft To Do notes and more.

And while some consumer features are going away, Microsoft stresses that Cortana will still be able to tell you a joke, set alarms and timers, and give you answers from Bing.

For now, all of this only applies to English-speaking users in the U.S. Outside of the U.S., most of the productivity features will launch in the future.


By Frederic Lardinois

DocuSign acquires Seal Software for $188M to enhance its AI chops

Contract management service DocuSign today announced that it is acquiring Seal Software for $188 million in cash. The acquisition is expected to close later this year. DocuSign, it’s worth noting, previously invested $15 million in Seal Software in 2019.

Seal Software was founded in 2010, and, while it may not be a mainstream brand, its customers include the likes of PayPal, Dell, Nokia and DocuSign itself. These companies use Seal for its contract management tools, but also for its analytics, discovery and data extraction services. And it’s these AI smarts the company developed over time to help businesses analyze their contracts that made DocuSign acquire the company. This can help them significantly reduce their time for legal reviews, for example.

“Seal was built to make finding, analyzing, and extracting data from contracts simpler and faster,” DocuSign CEO John O’Melia said in today’s announcement. “We have a natural synergy with DocuSign, and our team is excited to leverage our AI expertise to help make the Agreement Cloud even smarter. Also, given the company’s scale and expansive vision, becoming part of DocuSign will provide great opportunities for our customers and partners.”

DocuSign says it will continue to sell Seal’s analytics tools. What’s surely more important to DocuSign, though, is that it will also leverage the company’s AI tools to bolster its DocuSign CLM offering. CLM is DocuSign’s service for automating the full contract life cycle, with a graphical interface for creating workflows and collaboration tools for reviewing and tracking changes, among other things. And integration with Seal’s tools, DocuSign argues, will allow it to provide its customers with a “faster, more efficient agreement process,” while Seal’s customers will benefit from deeper integrations with the DocuSign Agreement Cloud.


By Frederic Lardinois

London-based Gyana raises $3.9M for a no-code approach to data science

Coding and other computer science expertise remain some of the more important skills that a person can have in the working world today, but in the last few years, we have also seen a big rise in a new generation of tools providing an alternative way of reaping the fruits of technology: “no-code” software, which lets anyone — technical or non-technical — build apps, games, AI-based chatbots, and other products that used to be the exclusive terrain of engineers and computer scientists.

Today, one of the newer startups in the category — London-based Gyana, which lets non-technical people run data science analytics on any structured dataset — is announcing a round of £3 million to fuel its next stage of growth.

Led by UK firm Fuel Ventures, other investors in this round include Biz Stone of Twitter, Green Shores Capital and U+I , and it brings the total raised by the startup to $6.8 million since being founded in 2015.

Gyana (Sanskrit for “knowledge”) was co-founded by Joyeeta Das and David Kell, who were both pursuing post-graduate degrees at Oxford: Das, a former engineer, was getting an MBA, and Kell was doing a PhD in physics.

Das said that the idea of building this tool came out of the fact that the pair could see a big disconnect emerging not just in their studies, but also in the world at large — not so much a digital divide, as a digital light year in terms of the distance between the groups of who and who doesn’t know how to work in the realm of data science.

“Everyone talks about using data to inform decision making, and the world becoming data-driven, but actually that proposition is available to less than one percent of the world,” she said.

Out of that, the pair decided to work on building a platform that Das describes as a way to empower “citizen data scientists”, by letting users upload any structured data set (for example, a .CSV file) and running a series of queries on it to be able to visualise trends and other insights more easily.

While the longer term goal may be for any person to be able to produce an analytical insight out of a long list of numbers, the more practical and immediate application has been in enterprise services and building tools for non-technical knowledge workers to make better, data-driven decisions.

To prove out its software, the startup first built an app based on the platform that it calls Neera (Sanskrit for “water”), which specifically parses footfall and other “human movement” metrics, useful for applications in retail, real estate and civic planning — for example to determine well certain retail locations are performing, footfall in popular locations, decisions on where to place or remove stores, or how to price a piece of property.

Starting out with the aim of mid-market and smaller companies — those most likely not to have in-house data scientists to meet their business needs — startup has already picked up a series of customers that are actually quite a lot bigger than that. They include Vodafone, Barclays, EY, Pret a Manger, Knight Frank and the UK Ministry of Defense. It says it has some £1 million in contracts with these firms currently.

That, in turn, has served as the trigger to raise this latest round of funding and to launch Vayu (Sanskrit for “air”) — a more general purpose app that covers a wider set of parameters that can be applied to a dataset. So far, it has been adopted by academic researchers, financial services employees, and others that use analysis in their work, Das said.

With both Vayu and Neera, the aim — refreshingly — is to make the whole experience as privacy-friendly as possible, Das noted. Currently, you download an app if you want to use Gyana, and you keep your data local as you work on it. Gyana has no “anonymization” and no retention of data in its processes, except things like analytics around where your cursor hovers, so that Gyana knows how it can improve its product.

“There are always ways to reverse engineer these things,” Das said of anonymization. “We just wanted to make sure that we are not accidentally creating a situation where, despite learning from anaonyised materials, you can’t reverse engineer what people are analysing. We are just not convinced.”

While there is something commendable about building and shipping a tool with a lot of potential to it, Gyana runs the risk of facing what I think of as the “water, water everywhere” problem. Sometimes if a person really has no experience or specific aim, it can be hard to think of how to get started when you can do anything. Das said they have also identified this, and so while currently Gyana already offers some tutorials and helper tools within the app to nudge the user along, the plan is to eventually bring in a large variety of datasets for people to get started with, and also to develop a more intuitive way to “read” the basics of the files in order to figure out what kinds of data inquiries a person is most likely to want to make.

The rise of “no-code” software has been a swift one in the world of tech spanning the proliferation of startups, big acquisitions, and large funding rounds. Companies like Airtable and DashDash are aimed at building analytics leaning on interfaces that follow the basic design of a spreadsheet; AppSheet, which is a no-code mobile app building platform, was recently acquired by Google; and Roblox (for building games without needing to code) and Uncorq (for app development) have both raised significant funding just this week. In the area of no-code data analytics and visualisation, there are biggies like Tableau, as well as Trifacta, RapidMiner and more.

Gartner predicts that by 2024, some 65% of all app development will be made on low- or no-code platforms, and Forrester estimates that the no- and low-code market will be worth some $10 billion this year, rising to $21.2 billion by 2024.

That represents a big business opportunity for the likes of Gyana, which has been unique in using the no-code approach specifically to tackle the area of data science.

However, in the spirit of citizen data scientists, the intention is to keep a consumer version of the apps free to use as it works on signing up enterprise users with more enhanced paid products, which will be priced on an annual license basis (currently clients are paying between $6,000 and $12,000 depending on usage, she said).

“We want to do free for as long as we can,” Das said, both in relation to the data tools and the datasets that it will offer to users. “The biggest value add is not about accessing premium data that is hard to get. We are not a data marketplace but we want to provide data that makes sense to access,” adding that even with business users, “we’d like you to do 90% of what you want to do without paying for anything.”


By Ingrid Lunden

Freshworks acquires AnsweriQ

Customer engagement platform Freshworks today announced that it has acquired AnsweriQ, a startup that provides AI tools for self-service solutions and agent-assisted use cases where the ultimate goal is to quickly provide customers with answers and make agents more efficient.

The companies did not disclose the acquisition price. AnsweriQ last raised a funding round in 2017, when it received $5 million in a Series A round from Madrona Venture Group.

Freshworks founder and CEO Girish Mathrubootham tells me that he was introduced to the company through a friend, but that he had also previously come across AnsweriQ as a player in the customer service automation space for large clients in high-volume call centers.

“We really liked the team and the product and their ability to go up-market and win larger deals,” Mathrubootham said. “In terms of using the AI/ML customer service, the technology that they’ve built was perfectly complementary to everything else that we were building.”

He also noted the client base, which doesn’t overlap with Freshworks’, and the talent at AnsweriQ, including the leadership team, made this a no-brainer.

AnsweriQ, which has customers that use Freshworks and competing products, will continue to operate its existing products for the time being. Over time, Freshworks, of course, hopes to convert many of these users into Freshworks users as well. The company also plans to integrate AnsweriQ’s technology into its Freddy AI engine. The exact branding for these new capabilities remains unclear, but Mathrubootham suggested FreshiQ as an option.

As for the AnsweriQ leadership team, CEO Pradeep Rathinam will be joining Freshworks as chief customer officer.

Rathinam told me that the company was at the point where he was looking to raise the next round of funding. “As we were going to raise the next round of funding, our choices were to go out and raise the next round and go down this path, or look for a complementary platform on which we can vet our products and then get faster customer acquisition and really scale this to hundreds or thousands of customers,” he said. Rathinam also noted that as a pure AI player, AnsweriQ had to deal with lots of complex data privacy and residency issues, so a more comprehensive platform like Freshworks made a lot of sense.

Freshworks has always been relatively acquisitive. Last year, the company acquired the customer success service Natero, for example. With the $150 million Series H round it announced last November, the company now also has the cash on hand to acquire even more customers. Freshworks is currently valued at about $3.5 billion and has 2,7000 employees in 13 offices. With the acquisition of AnsweriQ, it now also has a foothold in Seattle, which it plans to use to attract local talent to the company.


By Frederic Lardinois

Thomas Kurian on his first year as Google Cloud CEO

“Yes.”

That was Google Cloud CEO Thomas Kurian’s simple answer when I asked if he thought he’d achieved what he set out to do in his first year.

A year ago, he took the helm of Google’s cloud operations — which includes G Suite — and set about giving the organization a sharpened focus by expanding on a strategy his predecessor Diane Greene first set during her tenure.

It’s no secret that Kurian, with his background at Oracle, immediately put the entire Google Cloud operation on a course to focus on enterprise customers, with an emphasis on a number of key verticals.

So it’s no surprise, then, that the first highlight Kurian cited is that Google Cloud expanded its feature lineup with important capabilities that were previously missing. “When we look at what we’ve done this last year, first is maturing our products,” he said. “We’ve opened up many markets for our products because we’ve matured the core capabilities in the product. We’ve added things like compliance requirements. We’ve added support for many enterprise things like SAP and VMware and Oracle and a number of enterprise solutions.” Thanks to this, he stressed, analyst firms like Gartner and Forrester now rank Google Cloud “neck-and-neck with the other two players that everybody compares us to.”

If Google Cloud’s previous record made anything clear, though, it’s that technical know-how and great features aren’t enough. One of the first actions Kurian took was to expand the company’s sales team to resemble an organization that looked a bit more like that of a traditional enterprise company. “We were able to specialize our sales teams by industry — added talent into the sales organization and scaled up the sales force very, very significantly — and I think you’re starting to see those results. Not only did we increase the number of people, but our productivity improved as well as the sales organization, so all of that was good.”

He also cited Google’s partner business as a reason for its overall growth. Partner influence revenue increased by about 200% in 2019, and its partners brought in 13 times more new customers in 2019 when compared to the previous year.


By Frederic Lardinois

SentinelOne raises $200M at a $1.1B valuation to expand its AI-based endpoint security platform

As cybercrime continues to evolve and expand, a startup that is building a business focused on endpoint security has raised a big round of funding. SentinelOne — which provides a machine learning-based solution for monitoring and securing laptops, phones, containerised applications and the many other devices and services connected to a network — has picked up $200 million, a Series E round of funding that it says catapults its valuation to $1.1 billion.

The funding is notable not just for its size but for its velocity: it comes just eight months after SentinelOne announced a Series D of $120 million, which at the time valued the company around $500 million. In other words, the company has more than doubled its valuation in less than a year — a sign of the cybersecurity times.

This latest round is being led by Insight Partners, with Tiger Global Management, Qualcomm Ventures LLC, Vista Public Strategies of Vista Equity Partners, Third Point Ventures, and other undisclosed previous investors all participating.

Tomer Weingarten, CEO and co-founder of the company, said in an interview that while this round gives SentinelOne the flexibility to remain in “startup” mode (privately funded) for some time — especially since it came so quickly on the heels of the previous large round — an IPO “would be the next logical step” for the company. “But we’re not in any rush,” he added. “We have one to two years of growth left as a private company.”

While cybercrime is proving to be a very expensive business (or very lucrative, I guess, depending on which side of the equation you sit on), it has also meant that the market for cybersecurity has significantly expanded.

Endpoint security, the area where SentinelOne concentrates its efforts, last year was estimated to be around an $8 billion market, and analysts project that it could be worth as much as $18.4 billion by 2024.

Driving it is the single biggest trend that has changed the world of work in the last decade. Everyone — whether a road warrior or a desk-based administrator or strategist, a contractor or full-time employee, a front-line sales assistant or back-end engineer or executive — is now connected to the company network, often with more than one device. And that’s before you consider the various other “endpoints” that might be connected to a network, including machines, containers and more. The result is a spaghetti of a problem. One survey from LogMeIn, disconcertingly, even found that some 30% of IT managers couldn’t identify just how many endpoints they managed.

“The proliferation of devices and the expanding network are the biggest issues today,” said Weingarten. “The landscape is expanding and it is getting very hard to monitor not just what your network looks like but what your attackers are looking for.”

This is where an AI-based solution like SentinelOne’s comes into play. The company has roots in the Israeli cyberintelligence community but is based out of Mountain View, and its platform is built around the idea of working automatically not just to detect endpoints and their vulnerabilities, but to apply behavioral models, and various modes of protection, detection and response in one go — in a product that it calls its Singularity Platform that works across the entire edge of the network.

“We are seeing more automated and real-time attacks that themselves are using more machine learning,” Weingarten said. “That translates to the fact that you need defence that moves in real time as with as much automation as possible.”

SentinelOne is by no means the only company working in the space of endpoint protection. Others in the space include Microsoft, CrowdStrike, Kaspersky, McAfee, Symantec and many others.

But nonetheless, its product has seen strong uptake to date. It currently has some 3,500 customers, including three of the biggest companies in the world, and “hundreds” from the global 2,000 enterprises, with what it says has been 113% year-on-year new bookings growth, revenue growth of 104% year-on-year, and 150% growth year-on-year in transactions over $2 million. It has 500 employees today and plans to hire up to 700 by the end of this year.

One of the key differentiators is the focus on using AI, and using it at scale to help mitigate an increasingly complex threat landscape, to take endpoint security to the next level.

“Competition in the endpoint market has cleared with a select few exhibiting the necessary vision and technology to flourish in an increasingly volatile threat landscape,” said Teddie Wardi, MD of Insight Partners, in a statement. “As evidenced by our ongoing financial commitment to SentinelOne along with the resources of Insight Onsite, our business strategy and ScaleUp division, we are confident that SentinelOne has an enormous opportunity to be a market leader in the cybersecurity space.”

Weingarten said that SentinelOne “gets approached every year” to be acquired, although he didn’t name any names. Nevertheless, that also points to the bigger consolidation trend that will be interesting to watch as the company grows. SentinelOne has never made an acquisition to date, but it’s hard to ignore that, as the company to expand its products and features, that it might tap into the wider market to bring in other kinds of technology into its stack.

“There are definitely a lot of security companies out there,” Weingarten noted. “Those that serve a very specific market are the targets for consolidation.”


By Ingrid Lunden

Microsoft Dynamics 365 update is focused on harnessing data

Microsoft announced a major update to its Dynamics 365 product line today, which correlates to the growing amount of data in the enterprise, and how to collect and understand that data to produce better customer experiences.

This is, in fact, the goal of all vendors in this space including Salesforce and Adobe, who are also looking to help improve the customer experience. James Philips, who was promoted to president of Microsoft Business Applications just this week, says that Microsoft has also been keenly focused on harnessing the growing amount of data and helping make use of that inside the applications he is in charge of.

“To be frank every single thing that we’re doing at Microsoft, not just in business applications but across the entire Microsoft Cloud, is on the back of that vision that data is coming out of everything, and that those organizations that can collect that data, harmonize it and reason over it will be in a position to be proactive versus reactive,” Philips told TechCrunch.

New customer engagement tooling

For starters, the company is adding functionality to its customer data platform (CDP), a concept all major vendors (and a growing group of startups) have embraced. It pulls together all of the customer data from various systems into one place, making it easier to understand how the customer interacts with you with the goal of providing better experiences based on this knowledge. Microsoft’s CDP is called Customer Insights.

The company is adding some new connectors to help complete that picture of the customer. “We’re adding new first- and third-party data connections to Customer Insights that allow our customers to understand, for example audience memberships, brand affinities, demographic, psychographic and other characteristics of customers that are stored and then harnessed from Dynamics 365 Customer Insights,” Philips said.

All of this, might make you wonder how they can collect this level of data and maintain GDPR/CCPA kind of compliance. Philips says that the company has been working on this for some time. “We did work at the company level to build a system that allows us and our customers to search for and then delete information about customers in each product group within Microsoft including my organization,” he explained.

The company has also added new sales forecasting tools and Dynamics 365 Sales Engagement Center. The first allows companies to tap into all this data to better predict the customers who sales is engaged with that are most likely to turn into sales. The second gives inside sales teams tools like next best action. These are not revolutionary by any means in the CRM space, but do provide new capabilities for Microsoft customers.

New operations level tooling

The operations side is related to what happens after the sale when the company begins to collect money and report revenue. To that end, the company is introducing a new product called Dynamic 365 Finance Insights, which you can think of as Customer Insights, except for money.

“This product is designed to help our customers predict and accelerate their cash flow. It’s designed specifically to identify opportunities where to focus your energy, where you may have the best opportunity to either close accounts payables or receivables or the opportunity to understand where you may have cash shortfalls,” Philips said.

Finally the company is introducing Dynamics 365 Project Operations,which provides a way for project-based business like construction, consulting and law to track the needs of the business.

“Those organizations, who are trying to operate in a project-based way now have with Dynamics 365 Project Operations, what we believe is the most widely used project management capability in Microsoft Project being joined now with all of the back-end capabilities for selling, accounting and planning that Dynamic 365 offers, all built on the same Common Data Platform, so that you can marry your front-end operations and operational planning with your back-end resource planning, workforce planning and operational processes,” he explained.

All of these tools are designed to take advantage of the growing amount of data coming into organizations, and provide ways to run businesses in a more automated and intelligent fashion that removes some of the manual steps involved in running a company.

To be clear, Microsoft is not alone in offering this kind of intelligent functionality. It is part of a growing movement to bring intelligence to all aspects of enterprise software, regardless of vendor.


By Ron Miller

OpsRamp raises $37.5M for its hybrid IT operations platform

OpsRamp, a service that helps IT teams discover, monitor, manage and — maybe most importantly — automate their hybrid environments, today announced that it has closed a $37.5 million funding round led by Morgan Stanley Expansion Capital, with participation from existing investor Sapphire Ventures and new investor Hewlett Packard Enterprise.

OpsRamp last raised funding in 2017, when Sapphire led its $20 million Series A round.

At the core of OpsRamp’s services is its AIOps platform. Using machine learning and other techniques, this service aims to help IT teams manage increasingly complex infrastructure deployments, provide intelligent alerting, and eventually automate more of their tasks. The company’s overall product portfolio also includes tools for cloud monitoring and incident management.

The company says its annual recurrent revenue increased by 300 percent in 2019 (though we obviously don’t know what number it started 2019 with). In total, OpsRamp says it now has 1,400 customers on its platform and alliances with AWS, ServiceNow, Google Cloud Platform and Microsoft Azure.

OpsRamp co-founder and CEO Varma Kunaparaju

According to OpsRamp co-founder and CEO Varma Kunaparaju, most of the company’s customers are mid to large enterprises. “These IT teams have large, complex, hybrid IT environments and need help to simplify and consolidate an incredibly fragmented, distributed and overwhelming technology and infrastructure stack,” he said. “The company is also seeing success in the ability of our partners to help us reach global enterprises and Fortune 5000 customers.”

Kunaparaju told me that the company plans to use the new funding to expand its go-to-market efforts and product offerings. “The company will be using the money in a few different areas, including expanding our go-to-market motion and new pursuits in EMEA and APAC, in addition to expanding our North American presence,” he said. “We’ll also be doubling-down on product development on a variety of fronts.”

Given that hybrid clouds only increase the workload for IT organizations and introduce additional tools, it’s maybe no surprise that investors are now interested in companies that offer services that rein in this complexity. If anything, we’ll likely see more deals like this one in the coming months.

“As more of our customers transition to hybrid infrastructure, we find the OpsRamp platform to be a differentiated IT operations management offering that aligns well with the core strategies of HPE,” said Paul Glaser, Vice President and Head of Hewlett Packard Pathfinder. “With OpsRamp’s product vision and customer traction, we felt it was the right time to invest in the growth and scale of their business.”


By Frederic Lardinois

Persona raises $17.5M for an identify verification platform that goes beyond user IDs and passwords

The proliferation of data breaches based on leaked passwords, and the rising tide of regulation that puts a hard stop on just how much user information can be collected, stored and used by companies have laid bare the holes in simple password and memorable-information-based verification systems.

Today a startup called Persona, which has built a platform to make it easier for organisations to implement more watertight methods based on third-party documentation, real-time evaluation, and AI to verify users, is announcing a funding round, speaking to the shift in the market and subsequent demand for new alternatives to the old way of doing things.

The startup has raised $17.5 million in a Series A from a list of impressive investors that include Coatue and First Round Capital, money that it plans to use to double down on its core product: a platform that businesses and organisations can access by way of an API, which lets them use a variety of documents, from government-issued IDs through to biometrics, to verify that customers are who they say they are.

Current customers include Rippling, Petal, UrbanSitter, Branch, Brex, Postmates, Outdoorsy, Rently, SimpleHealth and Hipcamp, among others. Persona’s target user today is any company involved in any kind of online financial transaction to verify for regulatory compliance, fraud prevention and for trust and safety.

The startup is young and is not disclosing valuation. Previously, Persona had raised an undisclosed amount of funding from Kleiner Perkins and FirstRound, according to data from PitchBook. Angels in the company have included Zach Perret and William Hockey (co-founders of Plaid), Dylan Field (founded Figma), Scott Belsky (Behance) and Tony Xu (DoorDash).

Founded by Rick Song and Charles Yeh, respectively former engineers from Square and Dropbox (companies that have had their own concerns with identity verification and breaches), Persona’s main premise is that most companies are not security companies and therefore lack the people, skills, time and money to build strong authentication and verification services — much less to keep up with the latest developments on what is best practice.

And on top of that, there have been too many breaches that underscored the problem with companies holding too much information on users, collected for identification purposes but then sitting there waiting to be hacked.

The name of the game for Persona is to provide services that are easy to use for customers — for those who can’t or don’t access the code of their apps or websites for registration flows, they can even verify users by way of email-based links.

“Digital identity is one of the most important things to get right, but there is no silver bullet,” Song, who is the CEO, said in an interview. “I believe longer term we’ll see that it’s not a one-size-fits-all approach.” Not least because malicious hackers have an ever-increasing array of tools to get around every system that gets put into place. (The latest is the rise of deep-fakes to mimic people, putting into question how to get around that in, say, a video verification system.)

At Persona, the company currently gives customers the option to ask for social security numbers, biometric verification such as fingerprints or pictures, or government ID uploads and phone lookups, some of which (like biometrics) is built by Persona itself and some of which is accessed via third-party partnerships. Added to that are other tools like quizzes and video-based interactions. Song said the list is expanding, and the company is looking at ways of using the AI engine that it’s building — which actually performs the matching — to also potentially suggest the best tools for each and every transaction.

The key point is that in every case, information is accessed from other databases, not kept by the customer itself.

This is a moving target, and one that is becoming increasingly harder to focus on, given not just the rise in malicious hacking, but also regulation that limits how and when data can be accessed and used by online businesses. Persona notes a McKinsey forecast that the personal identify and verification market will be worth some $20 billion by 2022, which is not a surprising figure when you consider the nearly $9 billion that Google has been fined so far for GDPR violations, or the $700 million Equifax paid out, or the $50 million Yahoo (a sister company now) paid out for its own user-data breach.


By Ingrid Lunden

ServiceNow acquires Loom Systems to expand AIOps coverage

ServiceNow announced today that it has acquired Loom Systems, an Israeli startup that specializes in AIOps. The companies did not reveal the purchase price.

IT operations collects tons of data across a number of monitoring and logging tools, way too much for any team of humans to keep up with. That’s why there are startups like Loom turning to AI to help sort through it. It can find issues and patterns in the data that would be challenging or impossible for humans to find. Applying AI to operations data in this manner has become known as AIOps in industry parlance.

ServiceNow is first and foremost a company trying to digitize the service process, however that manifests itself. IT service operations is a big part of that. Companies can monitor their systems, wait until a problem happens and then try and track down the cause and fix it, or they can use the power of artificial intelligence to find potential dangers to the system health and neutralize them before they become major problems. That’s what an AIOps product like Loom’s can bring to the table.

Jeff Hausman, vice president and general manager of IT Operations Management at ServiceNow sees Loom’s strengths merging with ServiceNow’s existing tooling to help keep IT systems running. “We will leverage Loom Systems’ log analytics capabilities to help customers analyze data, automate remediation and reduce L1 incidents,” he told TechCrunch.

Loom co-founder and CEO Gabby Menachem not surprisingly sees a similar value proposition. “By joining forces, we have the unique opportunity to bring together our AI innovations and ServiceNow’s AIOps capabilities to help customers prevent and fix IT issues before they become problems,” he said in a statement.

Loom raised $16 million since it launched in 2015, according to PitchBook data. Its most recent round for $10 million was in November 2019. Today’s deal is expected to close by the end of this quarter.


By Ron Miller