Mar
25
2020
--

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.

Mar
05
2020
--

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.

Mar
05
2020
--

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 (e.g. 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 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 eight brands owned by one of the world’s biggest CPG companies, and it is also being trialed by another major CPG behemoth (Turing is not disclosing their names publicly, but suffice it to say, they and their brands are household names).

“Turing aims to become the industry norm for formulation development and we are here to play the long game,” Shrimali said. “This requires creating an ecosystem that can help at each stage of growing and scaling the company, and YC just does this exceptionally well.”

Turing is co-founded by Shrimali and Ajith Govind, two specialists in data science that 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,” Shrimali 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 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 companies 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 the permutations that go into building something and making sure it works as 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,” Shrimali 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 to 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 to 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.

Mar
04
2020
--

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 in 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 managed 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.”

Mar
02
2020
--

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 April 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 get canceled, too.

Feb
28
2020
--

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.

Feb
28
2020
--

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.

Feb
27
2020
--

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,” Seal Software 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.

Feb
27
2020
--

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,” Seal Software 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.

Feb
27
2020
--

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 U.K. 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 Ph. D. in physics.

Das said 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.”

Powered by WordPress | Theme: Aeros 2.0 by TheBuckmaker.com