Investor Jocelyn Goldfein to join us on AI panel at TechCrunch Sessions: Enterprise

Artificial intelligence is quickly becoming a foundational technology for enterprise software development and startups have begun addressing a variety of issues around using AI to make software and processes much more efficient.

To that end, we are delighted to announce that Jocelyn Goldfein, a Managing Director at Zetta Venture Partners will be joining on us a panel to discuss AI in the enterprise. It will take place at the TechCrunch Sessions: Enterprise show on September 5 at the Yerba Buena Center in San Francisco.

It’s not just startups that are involved in AI in the enterprise. Some of the biggest names in enterprise software including Salesforce Einstein, Adobe Sensei and IBM Watson have been addressing the need for AI to help solve the enterprise data glut.

Computers can process large amounts of information much more quickly than humans, and as enterprise companies generate increasing amounts of data, they need help understanding it all as the volume of information exceeds human capacity to sort through it.

Goldfein brings a deep engineering background to her investment work. She served as a VP of engineering at VMware and as an engineering director at Facebook, where she led the project that adopted machine learning for the News Feed ranker, launched major updates in photos and search, and helped spearhead Facebook’s pivot to mobile. Goldfein drove significant reforms in Facebook hiring practices and is a prominent evangelist for women in computer science. As an investor, she primarily is focused on startups using AI to take more efficient approaches to infrastructure, security, supply chains and worker productivity.

At TC Sessions: Enterprise, she’ll be joining Bindu Reddy from Reality Engines along with other panelists to discuss the growing role of AI in enterprise software with TechCrunch editors. You’ll learn why AI startups are attracting investor attention and how AI in general could fundamentally transform enterprise software.

Prior to joining Zetta, Goldfein had stints at Facebook and VMware, as well as startups Datify, MessageOne and Trilogy/pcOrder.

Early Bird tickets to see Joyce at TC Sessions: Enterprise are on sale for just $249 when you book here; but hurry, prices go up by $100 soon! Students, grab your discounted tickets for just $75 here.


By Ron Miller

Andrew Ng to talk about how AI will transform business at TC Sessions: Enterprise

When it comes to applying AI to the world around us, Andrew Ng has few if any peers. We are delighted to announce that the renowned founder, investor, AI expert and Stanford professor will join us on stage at the TechCrunch Sessions: Enterprise show on Sept. 5 at the Yerba Buena Center in San Francisco. 

AI promises to transform the $500 billion enterprise world like nothing since the cloud and SaaS.  Hundreds of startups are already seizing the AI moment in areas like recruiting, marketing and communications, and customer experience. The oceans of data required to power AI are becoming dramatically more valuable, which in turn is fueling the rise of new data platforms, another big topic of the show

Last year, Ng  launched the $175 million AI Fund, backed by big names like Sequoia, NEA, Greylock, and Softbank. The fund’s goal is to develop new AI businesses in a studio model and spin them out when they are ready for prime time. The first of that fund’s cohort is Landing AI, which also launched last year and aims to “empower companies to jumpstart AI and realize practical value.” It’s a wave businesses will want to catch if Ng is anywhere near right in his conviction that AI will generate $13 trillion in GDP growth globally in the next 20 years. You heard that right. 

At TC Sessions: Enterprise, TechCrunch’s editors will ask Ng to detail how he believes AI will unfold in the enterprise world and bring big productivity gains to business. 

As the former Chief Scientist at Baidu and the founding lead of Google Brain, Ng led the AI transformation of two of the world’s leading technology companies. Dr. Ng is the Co-founder of Coursera, an online learning platform, and founder of deeplearning.ai, an AI education platform. Dr. Ng is also an Adjunct Professor at Stanford University’s Computer Science Department and holds degrees from Carnegie Mellon University, MIT and the University of California, Berkeley.

Early Bird tickets to see Andrew at TC Sessions: Enterprise are on sale for just $249 when you book here, but hurry prices go up by $100 soon! Students, grab your discounted tickets for just $75 here.



By Frederic Lardinois

Demo your startup at TC Sessions: Enterprise 2019

Every year hundreds of startups launch with dreams of becoming the next enterprise software unicorn. And it’s no wonder, given the $500 billion market and the rate at which the enterprise giants snap up emerging players. If you’re the founder of an early-stage enterprise startup, join us for TC Sessions: Enterprise in San Francisco on September 5 at the Yerba Buena Center for the Arts.

Even better, grab the opportunity by the horns and buy a Startup Demo Package. There is limited space available. This is your chance to plant your company in front of some of the most influential enterprise movers and shakers — we’re talking more than 1,000 attendees. Demo tables are reserved for startups with less than $3 million in funding and are available for $2,000, which includes four tickets to the event.

This day-long intensive event features speakers, panel discussions, demos, workshops and world-class networking. Get ready for a head-on, hype-free exploration of the considerable challenges enterprise companies face — regardless of their size.

TechCrunch editors will interview founders and leaders from both established and up-and-coming companies on topics ranging from intelligent marketing automation and the cloud to machine learning and AI. And they’ll question enterprise-focused VCs about where they’re directing their early, middle and late-stage investments.

The full roster of speakers is still to be announced, but here’s a quick hit of who you can expect at TC Sessions: Enterprise.

You’ll hear from Scott Farquhar, co-founder and co-CEO of Atlassian, a company that’s changed the way developers work. Want to hear more about enterprise and the cloud? Snowflake’s co-founder and president of product, Benoit Dageville, will be on hand to talk about the company’s mission to bring the enterprise database to the cloud.

Have someone you want to hear from our stage? Submit your speaker suggestion here.

Pro Tip: For each TC Sessions: Enterprise ticket you buy, we’ll register you for a complimentary Expo Only pass to TechCrunch Disrupt SF on October 2-4.

TC Sessions: Enterprise takes place September 5 at San Francisco’s Yerba Buena Center for the Arts. Don’t miss this opportunity to showcase your early-stage enterprise startup in front of leading enterprise software founders, investors and technologists. Buy your Startup Demo Package today.

Looking for sponsorship opportunities? Contact our TechCrunch team to learn about the benefits associated with sponsoring TC Sessions: Enterprise 2019.


By Emma Comeau

Cathay Innovation leads Laiye’s $35M round to bet on Chinese enterprise IT

For many years, the boom and bust of China’s tech landscape have centered around consumer-facing products. As this space gets filled by Baidu, Alibaba, Tencent, and more recently Didi Chuxing, Meituan Dianping, and ByteDance, entrepreneurs and investors are shifting attention to business applications.

One startup making waves in China’s enterprise software market is four-year-old Laiye, which just raised a $35 million Series B round led by cross-border venture capital firm Cathay Innovation. Existing backers Wu Capital, a family fund, and Lightspeed China Partners, whose founding partner James Mi has been investing in every round of Laiye since Pre-A, also participated in this Series B.

The deal came on the heels of Laiye’s merger with Chinese company Awesome Technology, a team that’s spent the last 18 years developing Robotic Process Automation, a term for technology that lets organizations offload repetitive tasks like customer service onto machines. With this marriage, Laiye officially launched its RPA product UiBot to compete in the nascent and fast-growing market for streamlining workflow.

“There was a wave of B2C [business-to-consumer] in China, and now we believe enterprise software is about to grow rapidly,” Denis Barrier, co-founder and chief executive officer of Cathay Innovation, told TechCrunch over a phone interview.

Since launching in January, UiBot has collected some 300,000 downloads and 6,000 registered enterprise users. Its clients include major names such as Nike, Walmart, Wyeth, China Mobile, Ctrip and more.

Guanchun Wang, chairman and CEO of Laiye, believes there are synergies between AI-enabled chatbots and RPA solutions, as the combination allows business clients “to build bots with both brains and hands so as to significantly improve operational efficiency and reduce labor costs,” he said.

When it comes to market size, Barrier believes RPA in China will be a new area of growth. For one, Chinese enterprises, with a shorter history than those found in developed economies, are less hampered by legacy systems, which makes it “faster and easier to set up new corporate software,” the investor observed. There’s also a lot more data being produced in China given the population of organizations, which could give Chinese RPA a competitive advantage.

“You need data to train the machine. The more data you have, the better your algorithms become provided you also have the right data scientists as in China,” Barrier added.

However, the investor warned that the exact timing of RPA adoption by people and customers is always not certain, even though the product is ready.

Laiye said it will use the proceeds to recruit talents for research and development as well as sales of its RPA products. The startup will also work on growing its AI capabilities beyond natural language processing, deep learning, and reinforcement learning, in addition to accelerating commercialization of its robotic solutions across industries.


By Rita Liao

Bright Machines wants to put AI-driven automation in every factory

There’s a mythology around today’s factories that says everything is automated by robotics, and while there is some truth to that, it’s hard to bring that level of sophistication to every facility, especially those producing relatively small runs. Today, Bright Machines, a San Francisco startup announced its first product designed to put intelligence and automation in reach of every manufacturer, regardless of its size.

The startup, which emerged last fall with $179 million in Series A funding, has a mission to make every aspect of manufacturing run in a software-defined automated fashion. Company CEO Amar Hanspal understands it’s a challenging goal, and today’s announcement is about delivering version 1.0 of that vision.

“We have this ambitious idea to fundamentally change the way factories operate, and what we are all about is to get to autonomous programmable factories,” he said. To start on that journey, since getting its initial funding in October, the company has been building a team that includes manufacturing, software and artificial intelligence expertise. It brought in people from Autodesk, Amazon and Google and opened offices in Seattle and Tel Aviv.

The product it is releasing today is called the Software Defined Microfactory and it consists of hardware and software components that work in tandem. “What the Software Defined Microfactory does is package together robotics, computer vision, machine handling and converged systems in a modular way with hardware that you can plug and play, then the software comes in to instruct the factory on what to build and how to build it,” Hanspal explained.

Obviously, this is not an easy thing to do, and it’s taken a great deal of expertise to pull it together over the last months since the funding. It’s also required having testing partners. “We have about 20 product brands around the world and about 25 production lines in seven countries that have been iterating with us toward version one, what we are releasing today,” Hanspal said.

The company is concentrating on the assembly line for starters, especially when building smaller runs like say a specialized computer board or a network appliance where the manufacturer might produce just 50,000 in total, and could benefit from automation, but couldn’t justify the cost before.

“The idea here is going after the least automated part inside of factory, which is the assembly line, which is typically where people have to throw bodies at the problem and assembly lines have been hard to automate. The operations around assembly typically require human dexterity and judgment, trying to align things or plug things in,” Hanspal said.

The hope is to create a series of templates for different kinds of tooling, where they can get the majority of the way there with the software and robotics, and eventually just have to work on the more customized bits. It is an ambitious goal, and it’s not going to be easy to pull off, but today’s release is a first step.


By Ron Miller

Snowflake co-founder and president of product Benoit Dageville is coming to TC Sessions: Enterprise

When it comes to a cloud success story, Snowflake checks all the boxes. It’s a SaaS product going after industry giants. It has raised bushels of cash and grown extremely rapidly — and the story is continuing to develop for the cloud data lake company.

In September, Snowflake’s co-founder and president of product Benoit Dageville will join us at our inaugural TechCrunch Sessions: Enterprise event on September 5 in San Francisco.

Dageville founded the company in 2012 with Marcin Zukowski and Thierry Cruanes with a mission to bring the database, a market that had been dominated for decades by Oracle, to the cloud. Later, the company began focusing on data lakes or data warehouses, massive collections of data, which had been previously stored on premises. The idea of moving these elements to the cloud was a pretty radical notion in 2012.

It began by supporting its products on AWS, and more recently expanded to include support for Microsoft Azure and Google Cloud.

The company started raising money shortly after its founding, modestly at first, then much, much faster in huge chunks. Investors included a Silicon Valley who’s who such as Sutter Hill, Redpoint, Altimeter, Iconiq Capital and Sequoia Capital .

Snowflake fund raising by round. Chart: Crunchbase

Snowflake fund raising by round. Chart: Crunchbase

The most recent rounds came last year, starting with a massive $263 million investment in January. The company went back for more in October with an even larger $450 million round.

It brought on industry veteran Bob Muglia in 2014 to lead it through its initial growth spurt. Muglia left the company earlier this year and was replaced by former ServiceNow chairman and CEO Frank Slootman.

TC Sessions: Enterprise (September 5 at San Francisco’s Yerba Buena Center) will take on the big challenges and promise facing enterprise companies today. TechCrunch’s editors will bring to the stage founders and leaders from established and emerging companies to address rising questions, like the promised revolution from machine learning and AI, intelligent marketing automation and the inevitability of the cloud, as well as the outer reaches of technology, like quantum computing and blockchain.

Tickets are now available for purchase on our website at the early-bird rate of $395.

Student tickets are just $245 – grab them here.

We have a limited number of Startup Demo Packages available for $2,000, which includes four tickets to attend the event.

For each ticket purchased for TC Sessions: Enterprise, you will also be registered for a complimentary Expo Only pass to TechCrunch Disrupt SF on October 2-4.


By Ron Miller

Get your early-bird tickets to TC Sessions: Enterprise 2019

In a world where the enterprise market hovers around $500 billion in annual sales, is it any wonder that hundreds of enterprise startups launch into that fiercely competitive arena every year? It’s a thrilling, roller-coaster ride that’s seen it all: serious success, wild wealth and rapid failure.

That’s why we’re excited to host our inaugural TC Sessions Enterprise 2019 event on September 5 at the Yerba Buena Center for the Arts in San Francisco. Like TechCrunch’s other TC Sessions, this day-long intensive goes deep on one specific topic. Early-bird tickets are on sale now for $395 — and we have special pricing for MBA students and groups, too. Buy your tickets now and save.

Bonus ROI: For every ticket you buy to TC Sessions: Enterprise, we’ll register you for a free Expo Only pass to TechCrunch Disrupt SF on October 2-4. Sweet!

Expect a full day of programming featuring the people making it happen in enterprise today. We’re talking founders and leaders from established and emerging companies, plus proven enterprise-focused VCs. Discussions led by TechCrunch’s editors, including Connie Loizos, Frederic Lardinois and Ron Miller, will explore machine learning and AI, intelligent marketing automation and the inevitability of the cloud. We’ll even touch on topics like quantum computing and blockchain.

Tired of the hype and curious about what it really takes to build a successful enterprise company? We’ve got you. You’ll hear from proven serial entrepreneurs who’ve been there, done that and what they might like to build next.

We’re building the agenda of speakers, panelists and demos, and we have a limited number of speaking opportunities available. If you have someone in mind, submit your recommendation here.

This event is perfect for enterprise-minded founders, investors, MBA students, engineers, CTOs and CIOs. If you need four or more tickets, take advantage of our group rate and save 15% over the early-bird price when you buy in bulk. Are you an MBA student? Save your dough — buy a student ticket for $245.

TC Sessions: Enterprise 2019 takes place September 5 in San Francisco. Join us for actionable insights and world-class networking. Buy your early-bird tickets today.

Is your company interested in sponsoring or exhibiting at TC Sessions: Enterprise 2019? Contact our sponsorship sales team by filling out this form.


By Emma Comeau

TextIQ, a machine learning platform for parsing sensitive corporate data, raises $12.6M

TextIQ, a machine learning system that parses and understands sensitive corporate data, has raised $12.6 million in Series A funding led by FirstMark Capital, with participation from Sierra Ventures.

TextIQ started as cofounder Apoorv Agarwal’s Columbia thesis project titled “Social Network Extraction From Text.” The algorithm he built was able to read a novel, like Jane Austen’s Emma, for example, and understand the social hierarchy and interactions between characters.

This people-centric approach to parsing unstructured data eventually became the kernel of TextIQ, which helps corporations find what they’re looking for in a sea of unstructured, and highly sensitive, data.

The platform started out as a tool used by corporate legal teams. Lawyers often have to manually look through troves of documents and conversations (text messages, emails, Slack, etc.) to find specific evidence or information. Even using search, these teams spend loads of time and resources looking through the search results, which usually aren’t as accurate as they should be.

“The status quo for this is to use search terms and hire hundreds of humans, if not thousands, to look for things that match their search terms,” said Agarwal. “It’s super expensive, and it can take months to go through millions of documents. And it’s still risky, because they could be missing sensitive information. Compared to the status quo, TextIQ is not only cheaper and faster but, most interestingly, it’s much more accurate.”

Following success with legal teams, TextIQ expanded into HR/compliance, giving companies the ability to retrieve sensitive information about internal compliance issues without a manual search. Because TextIQ understands who a person is relative to the rest of the organization, and learns that organization’s ‘language’, it can more thoroughly extract what’s relevant to the inquiry from all that unstructured data in Slack, email, etc.

More recently, in the wake of GDPR, TextIQ has expanded its product suite to work in the privacy realm. When a company is asked by a customer to get access to all their data, or to be forgotten, the process can take an enormous amount of resources. Even then, bits of data might fall through the cracks.

For example, if a customer emailed Customer Service years ago, that might not come up in the company’s manual search efforts to find all of that customer’s data. But since TextIQ understands this unstructured data with a person-centric approach, that email wouldn’t slip by its system, according to Agarwal.

Given the sensitivity of the data, TextIQ functions behind a corporation’s firewall, meaning that TextIQ simply provides the software to parse the data rather than taking on any liability for the data itself. In other words, the technology comes to the data, and not the other way around.

TextIQ operates on a tiered subscription model, and offers the product for a fraction of the value they provide in savings when clients switch over from a manual search. The company declined to share any further details on pricing.

Former Apple and Oracle General Counsel Dan Cooperman, former Verizon General Counsel Randal Milch, former Baxter International Global General Counsel Marla Persky, and former Nationwide Insurance Chief Legal and Governance Officer Patricia Hatler are on the advisory board for TextIQ.

The company has plans to go on a hiring spree following the new funding, looking to fill positions in R&D, engineering, product development, finance, and sales. Cofounder and COO Omar Haroun added that the company achieved profitability in its first quarter entering the market and has been profitable for eight consecutive quarters.


By Jordan Crook

RealityEngines.AI raises $5.25M seed round to make ML easier for enterprises

RealityEngines.AI, a research startup that wants to help enterprises make better use of AI, even when they only have incomplete data, today announced that it has raised a $5.25 million seed funding round. The round was led by former Google CEO and Chairman Eric Schmidt and Google founding board member Ram Shriram. Khosla Ventures, Paul Buchheit, Deepchand Nishar, Elad Gil, Keval Desai, Don Burnette and others also participated in this round.

The fact that the service was able to raise from this rather prominent group of investors clearly shows that its overall thesis resonates. The company, which doesn’t have a product yet, tells me that it specifically wants to help enterprises make better use of the smaller and noisier datasets they have and provide them with state-of-the-art machine learning and AI systems that they can quickly take into production. It also aims to provide its customers with systems that can explain their predictions and are free of various forms of bias, something that’s hard to do when the system is essentially a black box.

As RealityEngines CEO Bindu Reddy, who was previously the head of products for Google Apps, told me the company plans to use the funding to build out its research and development team. The company, after all, is tackling some of the most fundamental and hardest problems in machine learning right now — and that costs money. Some, like working with smaller datasets, already have some available solutions like generative adversarial networks that can augment existing datasets and that RealityEngines expects to innovate on.

Reddy is also betting on reinforcement learning as one of the core machine learning techniques for the platform.

Once it has its product in place, the plan is to make it available as a pay-as-you-go managed service that will make machine learning more accessible to large enterprise, but also to small and medium businesses, which also increasingly need access to these tools to remain competitive.


By Frederic Lardinois

Alyce picks up $11.5 million Series A to help companies give better corporate gifts

Alyce, an AI-powered platform that helps sales people, marketers and event planners give better corporate gifts, has today announced the close of an $11.5 million Series A funding. The round was led by Manifest, with participation from General Catalyst, Boston Seed Capital, Golden Ventures, Morningside and Victress Capital.

According to Alyce, $120 billion is spent each year (just in the United States) on corporate gifts, swag, etc. Unfortunately, the impact of these gifts isn’t usually worth the hassle. No matter how thoughtful or clever a gift is, each recipient is a unique individual with their own preferences and style. It’s nearly impossible for marketers and event planners to find a one-size-fits-all gift for their recipients.

Alyce, however, has a solution. The company asks the admin to upload a list of recipients. The platform then scours the internet for any publicly available information on each individual recipient, combing through their Instagram, Twitter, Facebook, LinkedIn, videos and podcasts in which they appear, etc.

Alyce then matches each individual recipient with their own personalized gift, as chosen from one of the company’s merchant partners. The platform sends out an invitation to that recipient to either accept the gift, exchange the gift for something else on the platform, or donate the dollar value to the charity of their choice.

This allows Alyce to ensure marketers and sales people always give the right gift, even when they don’t. For charity donations, the donation is made in the name of the corporate entity who gave the gift, not the recipient, meaning that all donations act as a write-off for the gifting company.

The best marketers and sales people know how impactful a great gift, at the right time, can be. But the work involved in figuring out what a person actually wants to receive can be overwhelming. Hell, I struggle to find the right gifts for my close friends and loved ones.

Alyce takes all the heavy lifting out of the equation.

The company also has integrations with Salesforce, so users can send an Alyce gift from directly within Salesforce.

Alyce charges a subscription to businesses who use the software, and also takes a small cut of gifts accepted on the platform. The company also offers to send physical boxes with cards and information about the gift as another revenue channel.

Alyce founder and CEO Greg Segall says the company is growing 30 percent month-over-month and has clients such as InVision, Lenovo, Marketo and Verizon.


By Jordan Crook

Qubole launches Quantum, its serverless database engine

Qubole, the data platform founded by Apache Hive creator and former head of Facebook’s Data Infrastructure team Ashish Thusoo, today announced the launch of Quantum, its first serverless offering.

Qubole may not necessarily be a household name, but its customers include the likes of Autodesk, Comcast, Lyft, Nextdoor and Zillow . For these users, Qubole has long offered a self-service platform that allowed their data scientists and engineers to build their AI, machine learning and analytics workflows on the public cloud of their choice. The platform sits on top of open-source technologies like Apache Spark, Presto and Kafka, for example.

Typically, enterprises have to provision a considerable amount of resources to give these platforms the resources they need. These resources often go unused and the infrastructure can quickly become complex.

Qubole already abstracts most of this away and offering what is essentially a serverless platform. With Quantum, however, it is going a step further by launching a high-performance serverless SQP engine that allows users to query petabytes of data with nothing else by ANSI-SQL, given them the choice between using a Presto cluster or a serverless SQL engine to run their queries, for example.

The data can be stored on AWS, Azure, Google cloud or Oracle Cloud and users won’t have to set up a second data lake or move their data to another platform to use the SQL engine. Quantum automatically scales up or down as needed, of course, and users can still work with the same metastore for their data, no matter whether they choose the clustered or serverless option. Indeed, Quantum is essentially just another SQL engine without Qubole’s overall suite of engines.

Typically, Qubole charges enterprises by compute minutes. When using Quantum, the company uses the same metric, but enterprises pay for the execution time of the query. “So instead of the Qubole compute units being associated with the number of minutes the cluster was up and running, it is associated with the Qubole compute units consumed by that particular query or that particular workload, which is even more fine-grained ” Thusoo explained. “This works really well when you have to do interactive workloads.”

Thusoo notes that Quantum is targeted at analysts who often need to perform interactive queries on data stored in object stores. Qubole integrates with services like Tableau and Looker (which Google is now in the process of acquiring). “They suddenly get access to very elastic compute capacity, but they are able to come through a very familiar user interface,” Thusoo noted.

 


By Frederic Lardinois

Microsoft Power BI platform update aims to put AI in reach of business users

Low code and no code are the latest industry buzzwords, but if vendors can truly abstract away the complexity of difficult tasks like building machine learning models, it could help mainstream technologies that are currently out of reach of most business users. That’s precisely what Microsoft is aiming to do with its latest Power BI platform announcements today.

The company tried to bring that low code simplicity to building applications last year when it announced PowerApps. Now it believes by combining PowerApps with Microsoft Flow and its new AI Builder tool, it can allow folks building apps with PowerApps to add a layer of intelligence very quickly.

It starts with having access to data sources, and the Data Connector tool gives users access to over 250 data connectors. That includes Salesforce, Oracle and Adobe, as well as of course Microsoft services like Office 365 and Dynamics 365. Richard Riley, senior director for Power Platform marketing, says this is the foundation for pulling data into AI Builder.

“AI Builder is all about making it just as easy in a low code, no code way to go bring artificial intelligence and machine learning into your Power Apps, into Microsoft Flow, into the Common Data Service, into your data connectors, and so on,” Riley told TechCrunch.

Screenshot: Microsoft

Charles Lamanna, general manager at Microsoft says that Microsoft can do all the analysis and heavy lifting required to build a data model for you, removing a huge barrier to entry for business users. “The basic idea is that you can select any field in the Common Data Service and just say, ‘I want to predict this field.’  Then we’ll actually go look at historical records for that same table or entity to go predict [the results],” he explained. This could be used to predict if a customer will sign up for a credit card, if a customer is likely to churn, or if a loan would be approved, and so forth.

While Microsoft admits this won’t be something everyone uses, they do see a kind of power user who might have been previously unable to approach this level of sophistication on their own, building apps and adding layers of intelligence without a heck of a lot of coding. If it works as advertised it will bring a level of simplicity to tasks that were previously well out of reach of business users without requiring a data scientist.


By Ron Miller

Salesforce is buying data visualization company Tableau for $15.7B in all-stock deal

On the heels of Google buying analytics startup Looker last week for $2.6 billion, Salesforce today announced a huge piece of news in a bid to step up its own work in data visualization and (more generally) tools to help enterprises make sense of the sea of data that they use and amass: Salesforce is buying Tableau for $15.7 billion in an all-stock deal.

The latter is publicly traded and this deal will involve shares of Tableau Class A and Class B common stock getting exchanged for 1.103 shares of Salesforce common stock, the company said, and so the $15.7 billion figure is the enterprise value of the transaction, based on the average price of Salesforce’s shares as of June 7, 2019.

This is a huge jump on Tableau’s last market cap: it was valued at $10.79 billion at close of trading Friday, according to figures on Google Finance. (Also: trading has halted on its stock in light of this news.)

The two boards have already approved the deal, Salesforce notes. The two companies’ management teams will be hosting a conference call at 8am Eastern and I’ll listen in to that as well to get more details.

This is a huge deal for Salesforce as it continues to diversify beyond CRM software and into deeper layers of analytics.

The company reportedly worked hard to — but ultimately missed out on — buying LinkedIn (which Microsoft picked up instead), and while there isn’t a whole lot in common between LinkedIn and Tableau, this deal is also about extending engagement with the customers that Salesforce already has.

This also looks like a move designed to help bulk up against Google’s move to buy Looker, announced last week, although I’d argue that analytics is a big enough area that all major tech companies that are courting enterprises are getting their ducks in a row in terms of squaring up to stronger strategies (and products) in this area. It’s unclear whether (and if) the two deals were made in response to each other.

“We are bringing together the world’s #1 CRM with the #1 analytics platform. Tableau helps people see and understand data, and Salesforce helps people engage and understand customers. It’s truly the best of both worlds for our customers–bringing together two critical platforms that every customer needs to understand their world,” said Marc Benioff, Chairman and co-CEO, Salesforce, in a statement. “I’m thrilled to welcome Adam and his team to Salesforce.”

Tableau has about 86,000 business customers including Charles Schwab, Verizon (which owns TC), Schneider Electric, Southwest and Netflix. Salesforce said it will operate independently and under its own brand post-acquisition. It will also remain headquartered in Seattle, WA, headed by CEO Adam Selipsky along with others on the current leadership team.

That’s not to say, though, that the two will not be working together: on the contrary, Salesforce is already talking up the possibilities of expanding what the company is already doing with its Einstein platform (launched back in 2016, Einstein is the home of all of Salesforce’s AI-based initiatives); and with “Customer 360”, which is the company’s product and take on omnichannel sales and marketing. The latter is an obvious and complementary product home, given that one huge aspect of Tableau’s service is to provide “big picture” insights.

“Joining forces with Salesforce will enhance our ability to help people everywhere see and understand data,” said Selipsky. “As part of the world’s #1 CRM company, Tableau’s intuitive and powerful analytics will enable millions more people to discover actionable insights across their entire organizations. I’m delighted that our companies share very similar cultures and a relentless focus on customer success. I look forward to working together in support of our customers and communities.”

“Salesforce’s incredible success has always been based on anticipating the needs of our customers and providing them the solutions they need to grow their businesses,” said Keith Block, co-CEO, Salesforce. “Data is the foundation of every digital transformation, and the addition of Tableau will accelerate our ability to deliver customer success by enabling a truly unified and powerful view across all of a customer’s data.”

More to come as we learn it. Refresh for updates.

 


By Ingrid Lunden

Microsoft and Oracle link up their clouds

Microsoft and Oracle announced a new alliance today that will see the two companies directly connect their clouds over a direct network connection so that their users can then move workloads and data seamlessly between the two. This alliance goes a bit beyond just basic direct connectivity and also includes identity interoperability.

This kind of alliance is relatively unusual between what are essentially competing clouds, but while Oracle wants to be seen as a major player in this space, it also realizes that it isn’t likely to get to the size of an AWS, Azure or Google Cloud anytime soon. For Oracle, this alliance means that its users can run services like the Oracle E-Business Suite and Oracle JD Edwards on Azure while still using an Oracle database in the Oracle cloud, for example. With that, Microsoft still gets to run the workloads and Oracle gets to do what it does best (though Azure users will also continue be able to run their Oracle databases in the Azure cloud, too).

“The Oracle Cloud offers a complete suite of integrated applications for sales, service, marketing, human resources, finance, supply chain and manufacturing, plus highly automated and secure Generation 2 infrastructure featuring the Oracle Autonomous Database,” said Don Johnson, executive vice president, Oracle Cloud Infrastructure (OCI), in today’s announcement. “Oracle and Microsoft have served enterprise customer needs for decades. With this alliance, our joint customers can migrate their entire set of existing applications to the cloud without having to re-architect anything, preserving the large investments they have already made.”

For now, the direct interconnect between the two clouds is limited to Azure US East and Oracle’s Ashburn data center. The two companies plan to expand this alliance to other regions in the future, though they remain mum on the details. It’ll support applications like JD Edwards EnterpriseOne, E-Business Suite, PeopleSoft, Oracle Retail and Hyperion on Azure, in combination with Oracle databases like RAC, Exadata and the Oracle Autonomous Database running in the Oracle Cloud.

“As the cloud of choice for the enterprise, with over 95% of the Fortune 500 using Azure, we have always been first and foremost focused on helping our customers thrive on their digital transformation journeys,” said Scott Guthrie, executive vice president of Microsoft’s Cloud and AI division. “With Oracle’s enterprise expertise, this alliance is a natural choice for us as we help our joint customers accelerate the migration of enterprise applications and databases to the public cloud.”

Today’s announcement also fits within a wider trend at Microsoft, which has recently started building a number of alliances with other large enterprise players, including its open data alliance with SAP and Adobe, as well as a somewhat unorthodox gaming partnership with Sony.

 


By Frederic Lardinois

IDC: Asia-Pacific spending on AI systems will reach $5.5 billion this year, up 80 percent from 2018

Spending on artificial intelligence systems in the Asia-Pacific region is expected to reach $5.5 billion this year, an almost 80 percent increase over 2018, driven by businesses in China and the retail industry, according to IDC. In a new report, the research firm also said it expects AI spending to climb at a compound annual growth rate of 50 percent from 2018 to 2022, reaching a total of $15.06 billion in 2022.

This means AI spending growth in the Asia-Pacific region is expected to outpace the rest of the world over the next three years. In March, IDC forecast that worldwide spending on AI systems is expected to grow at a CAGR of 38 percent between 2018 to 2022.

Most of the growth will happen in China, which IDC says will account for nearly two-thirds of AI spending in the region, excluding Japan, in all forecast years. Spending on AI systems will be driven by retail, professional services and government industries.

Retail demand for AI-based tools will also lead growth in the rest of the region, as companies begin to rely on it more for merchandising, product recommendations, automated customer service and supply and logistics. While the banking industry’s AI spending trails behind retail, it will also begin adopting the tech for fraud analysis, program advisors, recommendations and customer service. IDC forecasts that this year, companies will invest almost $700 million in automated service agents. The next largest area for investment is sales process recommendations and automation, with $450 million expected, and intelligent process automation at more than $350 million.

The fastest-growing industries for AI spending are expected to be healthcare (growing at 60.2 percent CAGR) and process manufacturing (60.1 percent CAGR). In terms of infrastructure, IDC says spending on hardware, including servers and storage, will reach almost $7 billion in 2019, while spending on software is expected to grow at a five-year CAGR of 80 percent.


By Catherine Shu