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IBM acquires Taos to supplement its cloud expertise as workloads shift

January 15, 2021 Big Data

IBM announced that it’s acquiring Taos, a provider of managed and professional IT services with a strong focus on public cloud computing platforms. At the same time, Deloitte Consulting announced that it has completed its previously announced acquisition of HashedIn Technologies Private Limited, a software engineering and product development firm specializing in cloud native technologies.

Terms of both deals were undisclosed. However, they both come at a time when the number of workloads being shifted to public clouds has accelerated significantly during the COVID-19 pandemic. That shift is altering the center of data gravity in the enterprise in a way that requires IT services providers to add additional application and data management expertise that spans multiple clouds.

Most of the data organizations manage today still reside in on-premises environments. It’s not likely all data will reside on-premises or in the cloud, but rather organizations will find themselves managing data as it ebbs and flows across multiple centers of data gravity, said David Sun, director of corporate business development for IBM Services, in an interview with VentureBeat.

“All our clients are telling us their applications and data will reside in multiple clouds and hybrid cloud computing environments,” said Sun.

Taos, which will operate as an IBM company based in San Jose, California, will remain with IBM after the rest of IBM’s managed services business focused on infrastructure is spun out sometime next year. That relationship is similar to the one IBM is establishing with 7Summits, an IT services provider focused on the Salesforce platform that IBM acquired last week. This follow IBM’s announcement last month that it plans to acquire Nordcloud, a provider of cloud consulting leader in Europe. Overall, mergers and acquisitions among IT services providers is at an all time high.

The challenge enterprise IT teams face today is that there is a general shortage of cloud computing expertise. IBM and other IT service providers are counting on organizations to augment the limited IT expertise and resources they have with external cloud expertise. That expertise is even more sought after now because most enterprise IT organizations don’t have a lot of experience employing cloud native technologies such as containers, Kubernetes, and serverless computing frameworks.

A report published earlier this week by Information Services Group (ISG), a technology research and advisory firm, finds commercial outsourcing contracts with an annual contract value of $ 5 million or more involving as-a-service platform and managed services reached $ 16 billion in the fourth quarter of 2020. That’s up 13% over last year and 9% over the third quarter. Managed services specifically accounted for $ 7.2 billion for the quarter, which according to the report marks the first time managed service deal sizes have returned to their pre-pandemic levels.

A significant percentage of those managed services contracts revolve around cloud computing projects, said ISG president Steve Hall. Managed service providers (MSPs) are trying to strike a balance between a decline in demand for managing on-premises IT infrastructure against cloud computing opportunities that require more software expertise, said Hall. “Many MSPs have been focused on the data center,” he said.

The biggest challenge in the last year has been the simple fact that landing new business typically requires in-person meetings because of the level of trust that needs to be established between service providers and their end customers, noted Hall.

Less clear at the moment is to what degree organizations will ultimately rely more on outsourcing as IT environments become more complex. The overall percentage of IT consumed as a managed service has been relatively small compared to the trillions of dollars in applications and infrastructure that is managed internally by an IT staff. However, Gartner is forecasting that the market for cloud professional services will exceed $ 200 billion by 2024.

Internal IT staff, of course, are often resistant to relying on service providers that they often perceive to be a potential threat to their jobs. The challenge IT services providers face is either overcoming that bias or simply finding a way to bypass that internal IT altogether by establishing a relationship with a business executive or CIO who has come to believe external services providers simply have a level of expertise in one area or another that is needed much sooner than an internal IT team can acquire.

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IBM acquires 7Summits to deepen its salesforce consulting expertise

January 12, 2021 Big Data

IBM announced today it acquired 7Summits, a privately held consulting firm owned by Sverica Capital Management LP. For more than 10 years, 7Summits has specialized in projects based on software-as-a-service (SaaS) applications from Salesforce. Terms of the deal were not disclosed.

The acquisition comes at a time when the number of organizations that have transitioned to SaaS applications in the wake of the COVID-19 pandemic has significantly increased both to better enable employees to work from home and to accelerate nascent digital business transformation initiatives.

IBM launched its Salesforce consulting practice in earnest by acquiring Bluewolf in 2016. The acquisition of 7Summit is the first time since then that IBM has moved to expand that business by acquiring a complementary consulting organization.

Demand for Salesforce expertise has expanded during the pandemic because many organizations have replaced on-premises applications that were difficult to access remotely with a portfolio of SaaS applications from Salesforce that address sales, marketing, e-commerce, customer service, analytics, and application integration, said Paul Papas, global managing partner for IBM enterprise strategy and experience.

Rather than simply invoking a vanilla instance of these applications, Papas said most organizations are building customer workflows that span multiple SaaS applications. The IBM consulting practice is designed to help organizations achieve that goal by either standardizing on Salesforce SaaS applications or integrating them with other SaaS applications from Salesforce rivals such as SAP, Adobe, and ServiceNow.

In addition, IBM also works with customers to integrate the Einstein AI engine developed by Salesforce with the Watson AI platform developed by IBM. The Einstein engine from Salesforce is optimized for Salesforce applications, while Watson AI technologies are applied more broadly across the enterprise, noted Papas.

IBM decided to acquire 7Summits because the consulting firm has already developed some of its own applications for the Salesforce platform in addition to having developed expertise in segments that IBM views as being complementary to its existing practice, said Papas.

In the last year, many organizations have employed SaaS platforms to accelerate digital business transformation initiatives that, prior to the pandemic, were expected to be achieved over the course of several years, said Papas. Instead of building applications from the ground up, it quickly became apparent it was simpler to customize existing SaaS applications using low-code and no-code tools that are more accessible to a broad range of developers.

Now that a COVID-19 vaccine is becoming more widely available, organizations are now looking for help to determine to what degree some business processes will remain forever digital, while others shift back toward the way they were conducted prior to the pandemic, added Papas. “Organizations are now trying to determine what will stay changed forever,” he said.

Regardless of the path forward, it’s unlikely many organizations (with few exceptions) that have shifted toward SaaS applications will be rolling back toward legacy on-premises applications.

Of course, IBM is hardly the only provider of IT services focusing on SaaS application platforms. Competition among IT services providers is fierce. Papas declined to say whether IBM planned any further acquisitions among consulting firms that have Salesforce expertise, but he wouldn’t necessarily rule it out, either. In the last year, there has been a wave of mergers and acquisitions among IT services providers that continues unabated.

In the meantime, enterprise IT organizations will need to determine in the months ahead how much internal SaaS application expertise they will need versus relying on external service providers. At a time when an uncertain economy may make more organizations hesitant to hire additional full-time employees, IBM and other IT services providers are clearly betting more organizations will look outside their own four walls for SaaS application expertise.

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Kenshoo acquires Signals Analytics to supplement its AI-powered marketing platform

December 23, 2020 Big Data

Kenshoo, a provider of a platform for managing marketing campaigns, yesterday announced its intent to acquire Signals Analytics, which provides a service for collecting unstructured consumer data that allows marketers to model campaigns using AI technologies. Signals Analytics counts organizations including Procter & Gamble, Nestle, Johnson & Johnson, Bayer, Roche, and Mars as its customers. Terms of the acquisition were not disclosed.

The Signal Analytics service optimizes marketing campaign designs using consumer data from external sources such as social media feeds and normalizes it for customers. That capability allows marketers to employ machine learning algorithms to reach specific types of consumers without necessarily having to rely on a digital marketing agency, said Signals Analytics co-founder and CEO Gil Sadeh.

All the data loading and preparation activities are automated using AI tools the company provides for that purpose, he noted. He said that there’s no need for organizations to construct a massive data lake of their own to analyze consumer data.

Going forward, the combined entity will further enable the automated marketing campaign execution based on the models customers create using the Signals Analytics service. “Our outputs will become their inputs,” said Sadeh. “We’re going to create the first full lifecycle knowledge graph built for marketers.”

Other providers of market and customer intelligence platforms include Stravito and Precima. Marketing departments also employ an array of analytics applications that have been customized to analyze data stored in various types of data lakes that IT teams typically construct in the cloud on their behalf.

As organizations look to engage consumers online in the wake of the COVID-19 pandemic, they’re typically faced with a stark choice: Either invest dollars in building their own marketing platforms on top of a data lake or opt to employ a service that continuously collects and normalizes consumer data on their behalf. It would take most IT organizations several years to acquire, build, and deploy a platform that collects consumer data from multiple sources at a level of scale Signal Analytics has already achieved.

Once built, that data lake also needs to be maintained, otherwise it will potentially turn into a data swamp. Signals Analytics not only collects and normalizes massive amounts of data, it also classifies that data in a way that makes it possible to search and query it using natural language processing (NLP) tools.

What enterprise IT organizations are investing is customer data platforms (CDPs) that enable them to better engage their existing customers. SAP, for example, acquired Emarsys last fall to provide such a platform. At the beginning of the year, Salesforce acquired Evergage. Other providers of CDP platforms include Oracle, Adobe, Arm Treasure Data, and QuickPivot.

The level of investment being made in these classes of platforms tends to vary widely depending on the impact the pandemic has had on a vertical industry. However, with many organizations prioritizing digital customer engagements, the need for platforms that employ AI to sort and analyze massive amounts of data have become more profound.

Of course, collecting customer data is only the first step. Organizations will also need to invest time and resources integrating analytics tools with the marketing automation platforms they have deployed. The combined entity that Kenshoo will create once the deal is completed will provide organizations with a pre-integrated platform.

It’s not clear to what degree the convergence of marketing intelligence and automation platforms is imminent. However, give the urgency to launch market campaigns faster at a lower total cost to the organization, chances are good that more mergers among these platform providers is imminent.

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Cloudflare acquires Linc to automate web app deployment

December 22, 2020 Big Data

Cloudflare today acquired Linc, an automation platform to help front-end developers collaborate and build apps, for an undisclosed amount. Cloudflare says this will accelerate development of its front-end JAMStack hosting platform — Cloudflare Pages — to enable “richer” and “more powerful” full-stack applications.

A major challenge in front-end web development is moving from a static site — i.e., a directory of HTML, JS, and CSS files — to a fully featured app. While companies benefit from the flexibility of being able to render everything on-demand, their maintenance costs increase because they now have servers they need to keep running. Moreover, unless they’re already operating at a global scale, they’ll often see worse end-user performance as requests are served from one or a few locations worldwide.

Linc and Cloudflare’s solution is the Frontend Application Bundle (FAB), a deployment artefact that supports a range of server-side needs, including static sites, apps with API routes, cloud functions, and server-side streaming rendering. A compiler generates a ZIP file that has two components: a server file that acts as a server-side entry point and an assets directory that stores the HTML, CSS, JS, images, and fonts that are sent to the client. When a FAB is deployed, it’s often split into these component parts and deployed separately. Assets are sent to a low-cost object storage platform with a content delivery network in front of it, and the server component is sent to dedicated serverless hosting.

Pages, which launched earlier this month, works with JAMstack (short for “JavaScript, APIs, and Markup”) to separate front-end pages and UI from backend apps and databases. It integrates with GitHub repositories and competes directly with Netlify or Vercel, two cloud hosting companies that let companies build and deploy sites using JAMstack frameworks.

“Linc’s goal was to give front-end developers the best tooling to build and refine their apps, regardless of which hosting they were using,” Linc CTO Glen Maddern wrote in a blog post. “But we started to notice an important trend — if a team had a free choice for where to host their front-end, they inevitably chose [Cloudflare]. In some cases, for a period, teams even used Linc to deploy a FAB … alongside their existing hosting to demonstrate the performance improvement before migrating permanently.”

In the near future, Maddern, who has joined Cloudflare, says Linc’s team will focus on expanding Pages to cover “the full spectrum” of apps. Moreover, he says it will work toward the broader goals of enabling customers to “fully embrace” edge-rendering and making global serverless hosting “more powerful and accessible.”

The Linc acquisition comes after Cloudflare purchased S2 Systems, a Seattle-area startup developing a remote browser isolation solution. It’s Cloudflare’s first purchase of 2020 and its fifth since 2014.

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Facebook acquires messaging marketing automation startup Kustomer

November 30, 2020 Big Data

Facebook today announced it will acquire Kustomer, a New York-based customer relationship management startup, for an undisclosed amount. When the deal closes, Facebook says it will natively integrate Kustomer’s tools with its messaging platforms, including WhatsApp and Messenger, to allow businesses and partners to better manage their communications with users.

For most brands, guiding and tracking customers through every step of their journeys is of critical operational importance. According to a recent PricewaterhouseCoopers report, the number of companies investing in omnichannel experiences has jumped from 20% to 80%, and an Adobe study found that those with the strongest omnichannel customer engagement strategies enjoy 10% year-over-year growth on average and a 25% increase in close rates.

“We’ve witnessed this shift firsthand as every day more than 175 million people contact businesses via WhatsApp. This number is growing because messaging provides a better overall customer experience and drives sales for businesses,” Facebook VP of ads and business products Dan Levy and WhatsApp COO Matt Idema wrote in a blog post. “As businesses adjust to an evolving digital environment, they’re seeking solutions that place people at the center, especially when it comes to communication. Any business knows that when the phone rings, they need to answer it. Increasingly, texts and messages have become just as important as that phone call — and businesses need to adapt.”

AOL and Salesforce veterans Brad Birnbaum and Jeremy Suriel founded Kustomer in 2015, which went on to attract customers including Sweetgreen, Ring, Glossier, Rent the Runway, Away, and Glovo. The company’s platform let clients search, display, and report out-of-the-box on objects like “customers” and “companies,” with tweakable attributes such as orders, feedback scores, shipping, tracking, web events, and more. On the AI side of the equation, Kustomer offered a conversational assistant that collects customer information for human agents and auto-routes conversations.

Kustomer’s workflow and business logic engines supported the creation of conditional, multi-branch flows that enabled each step to use the output of any previous step and to trigger responses based on defined events from internal or third-party systems. From a dashboard, managers could view which agents are working in real time and launch customer satisfaction surveys (or view the results of recent surveys). The dashboard also exposed sentiment to provide a metric for overall customer service effectiveness, and it enabled admins to customize Kustomer’s self-service, customer-facing knowledge base with articles, tutorials, and rich media including videos, PDFs, and other formats.

Last year saw the launch of KustomerIQ, which allowed companies to train AI models to address their unique business needs. The models in question could automatically classify conversations and customer attributes, reading messages between customers and agents using natural language processing techniques.

Prior to the Facebook acquisition, Kustomer raised $ 173.5 million across six fundraising rounds. Earlier this morning, The Wall Street Journal reported that the deal announced today could value the startup at more than $ 1 billion.

Birnbaum, Suriel, and the rest of the Kustomer team will join Facebook once the transaction is approved. Facebook says that Kustomer businesses will continue to own the data that comes from interactions with their customers, but that it eventually expects to host Kustomer data on its infrastructure.

“Once the acquisition closes, we look forward to working closely with Facebook, where we will continue to serve our customers and work with our partners as part of the Facebook family,” Birnbaum wrote in a blog post. “With our complementary capabilities, we will be able to help more people benefit from customer service that is faster, richer and available whenever and however they need it — via phone, email, text, web chat or messaging. In particular, we look forward to enhancing the messaging experience which is one of the fastest growing ways for people and businesses to engage.”

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Via acquires delivery logistics startup Fleetonomy to bolster fulfillment with AI

October 1, 2020 Big Data

In a move to expand its business into the logistics and delivery segment, ride-hailing startup Via today announced that it acquired Fleetonomy for an undisclosed sum. Via, which says it plans to apply Fleetonomy’s expertise in demand prediction and fleet utilization to support fully integrated, digitally powered logistics solutions, says the pandemic has highlighted the growing need for essential services and goods delivery.

Tel Aviv-based Fleetonomy, which was founded in 2017 by CEO Israel Duanis and CTO Lior Gerenstein, taps AI to analyze data and deliver insights with the goal of maximizing inventory and promoting proactive maintenance. The company provides white label ride-sharing and on-demand car subscription services that can accommodate semiautonomous and autonomous fleets. With Fleetonomy’s cloud-based suite of tools, managers can simulate services before deploying cars on the road, adjusting for factors such as fleet size, parking, charging locations, demand, and more.

“As we continue to build the next generation of public transportation and delivery infrastructure, we are proud to partner with Fleetonomy to step into this new phase of growth,” Via cofounders Daniel Ramot and Oren Shoval said in a statement. “We have been consistently impressed by Israel, Lior, and the entire Fleetonomy team, and by the beautifully designed and exceptionally engineered products they have created. We share a vision for the future of mobility and look forward to realizing this vision together.”

Prior to the acquisition, Fleetonomy raised $ 3 million in a seed round led by Vertex Ventures, with participation from Kardan Ventures and VectoIQ.

“Today is a very exciting milestone for our company,” Duanis said. “When Lior and I founded Fleetonomy three years ago, we had a very big mission in mind — to provide a new way of managing fleet based services … In the past three years, with the incredible Fleetonomy team and partners along the way, we’ve been very lucky to see this mission turn to reality with customers such as Toyota, Jaguar Land Rover, Audi, and other top players in the mobility space. By joining Via, we will be able to expand and extend this mission and work together on Via’s great vision of changing the landscape of transportation.”

The logistics market is an increasingly attractive investment for companies like Via. Even pre-pandemic, last-mile delivery was fast becoming the most expensive part of the supply chain, with research firm Capgemini pegging the percentage of costs at 41%.

That no doubt factored into Via’s calculation, which faces an uphill battle as the pandemic rages on around the world. In March, Via suspended shared rides in areas like New York City, Chicago, and San Francisco, a blow to its shared-ride business consumer model. A report from Edison Trends found that spending on ridesharing plummeted around 21% in the seven-day period ending March 16; Via competitor Uber said gross bookings on rides were down 75% in the three months through June, and Lyft previously said that April ridership was down 75% from April 2019.

Via — which has raised $ 500 million in venture capital to date at a $ 2.25 billion valuation — first launched in New York City in 2013, but it’s now deployed globally in more than 70 cities in 20 countries, operating in Europe as ViaVan in partnership with Mercedes-Benz Vans. As of March, the company says it has provided over 70 million rides, up from 50 million as of July 2019. And Via works with more than 150 partners across municipalities, public transit agencies, transportation operators, corporations, schools, and universities to optimize their transport systems, such as the city of West Sacramento, the Los Angeles Metro, Transport for London, Sydney’s Transport for New South Wales, and the New York City Department of Education.

Via’s ride-sharing app and service tap AI to combine multiple passengers or packages headed in the same direction in real time, ostensibly reducing urban congestion and emissions while providing a lower-cost mobility service. Shared rides are usually from corner-to-corner, requiring passengers to walk to a nearby pickup point indicated on the app.

Last year, Via announced the debut of a driverless shuttle program in New South Wales, Australia, in partnership with the BusBot project, local bus operator Busways, local government agency Transport for New South Wales, and startup EasyMile. More recently, the company launched an on-demand transportation pilot in Sacramento, California, that let customers hail rides from apps and the city’s public transportation department. Just this month, Via unveiled in Edmonton what it claims will be Canada’s largest on-demand transit service, with over 60 shuttles that will connect commuters and residents to transit hubs across the city starting in mid-2021. And in the U.K., Via was awarded a multimillion-dollar grant by Innovate U.K., Britain’s innovation agency, to develop a platform that supports local partners as they optimize emergency and last-mile delivery efforts.

Ramot has said that the end goal for Via is an initial public offering. It’s unclear when that might happen.

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Amazon acquires autonomous vehicle startup Zoox

June 28, 2020 Big Data

Amazon today announced it is acquiring Zoox, a startup developing autonomous vehicle systems aimed at ride-hailing applications. Neither company disclosed terms of the deal, but according to the Information and the Financial Times, the purchase price is over $ 1.2 billion.

It’s Amazon’s biggest bet yet on autonomous technologies — whether vehicular, aeronautic, or industrial. Last February, Amazon contributed to driverless car and truck startup Aurora’s $ 530 million series B round. In March 2012, Amazon acquired warehouse robotics startup Kiva Systems for $ 775 million.

With Zoox, Amazon — which delivers more than 10 billion items worldwide each year — is looking to cut costs. Analysts at Morgan Stanley estimate self-driving technology could save the tech giant over $ 20 billion a year on shipping as it becomes a formidable competitor to companies like UPS, DHL, and FedEx. By 2023, Amazon is expected to spend $ 90 billion on logistics, expanding its truck trailer, ocean freighter, last-mile delivery van, and cargo jet networks.

“Zoox is working to imagine, invent, and design a world-class autonomous ride-hailing experience,” said Amazon global consumer CEO Jeff Wilke in a statement. “Like Amazon, Zoox is passionate about innovation and about its customers, and we’re excited to help the talented Zoox team to bring their vision to reality in the years ahead.”

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The story so far

Zoox was founded in 2014 by Australian artist-designer Tim Kentley Klay and Jesse Levinson, son of Apple chair Arthur D. Levinson, who was developing self-driving technology at Stanford. In December 2018, Zoox was first to gain approval to provide driverless transport services to the public in California. And in January 2019, the company appointed former Intel chief strategy officer Aicha Evans CEO, signaling a shift in priorities from conceptualization to commercialization.

Foster City, California-based Zoox had raised over $ 990 million in venture capital at a multibillion-dollar valuation, and it appeared to be making progress toward a commercial launch before live testing of its level 3 vehicles ground to a halt during the pandemic. The company recently announced it would begin deploying its autonomous Highlanders in Las Vegas. It has a permit from the Nevada Department of Motor Vehicles to transport passengers autonomously and has submitted documents to the California DMV showing its 58 vehicles drove 67,015 autonomous miles in 2019 in San Francisco.

Zoox had hoped to move beyond retrofitted Highlanders to fully custom cars that could be summoned by customers via a smartphone app. The roughly BMW i3-sized electric vehicles would have used cameras and four lidar sensors for perception, with each one covering 270 degrees. The vehicles were also designed with four-wheel steering, active four-wheel suspension, dual power trains, and dual batteries with a combined capacity larger than that of most single-car batteries today.

The idea was to reduce congestion through fleet management and to minimize trips back to base stations for charging overnight. Zoox’s shuttle-like car — which was fully driverless — was designed to operate in a shared fleet in order to maximize efficiency and cut down on ride trip times.

The focus on efficiency likely appealed to Amazon’s newfound conservationist sensibilities. In February 2019, Amazon led a $ 700 million funding round in Rivian, a Michigan-based startup developing electric pickup trucks, which Amazon claims will save an estimated 4 million metric tons of carbon per year by 2030. Amazon plans to have 10,000 of Rivian’s vehicles making on-the-road deliveries as early as 2022 and 100,000 vehicles on the road by 2040.

Plans

According to Amazon, Zoox founders Evans (CEO) and Levinson (CTO) will continue to lead Zoox as a standalone business, and Amazon will help “bring their vision of autonomous ride-hailing to reality.” Amazon gave little away in terms of how it will leverage the technology. It could convert Zoox’s planned robo-taxis into automated delivery vans further down the road, a task it certainly has the expertise to pull off. According to Reuters, Amazon holds more than 210 transportation-related patents, including a 2017 patent to provide on-demand transportation services through a network of autonomous vehicles.

Zoox previously said it was demonstrating its vehicle to partners and insiders behind closed doors, but the next phase of its deployment plans remain unclear. A few months ago, Zoox reportedly laid off 10% of its 1,000-person workforce days after letting go of 120 contract workers, moves it blamed on the economic fallout from the pandemic. It also said it would pay Tesla an undisclosed amount of monetary damages and undergo an audit to settle a trade secret theft lawsuit filed last year in which Tesla claimed some former employees brought proprietary information to Zoox.

According to the Information, a majority of Zoox investors — among them Lux Capital, DFJ, Primavera Capital, and Atlassian cofounder Michael Cannon-Brooks’ Grok Ventures — will see a return from the purchase. Still, the reported $ 1 billion price tag supports the notion that autonomous vehicle development remains expensive. Ford and Volkswagen partner Argo AI recently closed a $ 2.6 billion round at a $ 7.25 billion valuation. In May, Didi Chuxing’s self-driving unit nabbed $ 500 million, led by SoftBank’s Vision Fund 2. And in March, Waymo managed to secure a $ 750 million extension, bringing its first external round to $ 3 billion.

The race has taken on greater urgency as the pandemic roils the economy. While startups like Gatik, Optimus Ride, TuSimple, and Nuro have escaped the worst of it so far, well-financed ventures — including Cruise, Kodiak Robotics, and Ike — have shed hundreds of employees collectively.

Analysts predict the health crisis and its effects will result in consolidation, tabled or canceled launches, and shakeups across the autonomous transportation industry. In something of a case in point, Ford pushed the unveiling of its self-driving service from 2021 to 2022, and Waymo CEO John Krafcik told the New York Times the pandemic delayed work by at least two months.

According to Boston Consulting Group’s Brian Collie, broad commercialization of AVs won’t happen before 2025 or 2026 — at least three years later than originally anticipated.

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Microsoft acquires ADRM Software to beef up Azure with industry data models

June 18, 2020 Big Data

Microsoft today announced it has acquired ADRM Software, which provides large-scale industry data models companies use as “information blueprints.” The tech giant says it plans to combine these models with storage and compute from Azure to support the creation of data lakes where information from multiples lines of business is collated together at scale.

Industry data models enable companies to capture and define business concepts, refine and integrate processes, and build interoperability into their ecosystems. But despite the fact that they’re foundational for things like data quality, lineage, and governance, such models are often implemented on a fragmented and siloed basis.

That’s where ADRM comes in. It develops industry-specific enterprise, data warehouse, business area, and solution data models spanning 10 industry groups and 65 lines of business. For each organization, the company creates an enterprise data model containing a subset of entities from business area models for that organization’s industry. A slice of between 21 and 30 comprehensive business area models provides detail and expanded scope for each of the areas, offering a view of data for that business or specific subject area.

ADRM says its data models help customers in 18 firms around the world plan, architect, design, govern, report, and gather business intelligence and analytics. Complementing those models, the company provides industry best practices content and industry-specific naming and definitions.

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“Data and AI are the foundation of modern technological innovation, yet businesses today struggle to unlock the full value data has to offer as fragmented data estates hinder digital transformation,” Microsoft Azure CVP Ravi Krishnaswamy wrote in a press release. “Without a comprehensive and integrated view of their data, companies are at a competitive disadvantage, which hinders digital adoption and data-driven innovation … [Now] these capabilities will be delivered at scale, enabling our customers to accelerate digital progress and reduce risk in a variety of major initiatives.”

With the acquisition, ADRM’s team joined Microsoft’s Azure global engineering arm. Financial terms of the deal weren’t disclosed.

“As we worked closely with the Azure global engineering team during the past year, we became very enthusiastic about the tremendous additional value and acceleration we believe can be unlocked for large enterprises across many industries by combining ADRM’s comprehensive industry data models with the limitless storage and compute from Azure to power the next generation of intelligent data lakes — data lakes which aren’t just vast reservoirs of data but which are also metadata-rich foundations [that] can supercharge modern data warehouses, next-level analytics, and AI and ML,” ADRM wrote in a blog post.

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Intel acquires urban mobility startup Moovit for $900 million

May 4, 2020 Big Data

Intel has confirmed that it’s buying Israeli urban mobility startup Moovit, in a deal worth $ 900 million. Reports of the impending acquisition were first published by local Israeli publication Calcalist on Sunday, and in a press release today, Intel noted that it was buying Ness Ziona-based Moovit to help make Mobileye a “complete mobility provider,” which will eventually include driverless taxi services.

Chip giant Intel has a recent track record of acquiring Israeli startups. Just a few months back it paid around $ 2 billion for Habana Labs, which develops programmable AI and machine learning accelerators for datacenters. But back in 2017, Intel doled out an eye-popping $ 15.3 billion for Mobileye, a computer vision firm specializing in autonomous cars. Mobileye’s advanced driver-assistance systems (ADAS) are currently used in 60 million vehicles, and as the technology moves further toward full autonomy, Moovit’s arsenal of data will help Mobileye turn on “cost- and demand-optimized driverless” car services.

When the deal closes, Moovit will become part of the Mobileye business but will continue to operate under its own brand and run its existing partnerships. It’s also worth noting that Intel had previously invested in Moovit via its venture capital arm Intel Capital, meaning that the value of the acquisition is actually pegged at $ 840 million, net of Intel Capital equity gain.

The story so far

Founded in 2012, Moovit is best known for its consumer-facing app that’s used by more than 40 million active users globally to see the best ways to traverse a city using a combination of transport options, and even includes nifty augmented reality (AR) directions. However, the company has pivoted its core business to focus on licensing its back-end platform to third parties through a “mobility-as-a-service” (MaaS) offering. Through this, Moovit provides municipalities with data and analytics to improve city transport infrastructure, while corporations such as TomTom and Microsoft also leverage Moovit’s data to offer third-party developer access to real-time transport data to include in their own apps.

Intel acquires urban mobility startup Moovit for $900 million

Above: NYC: Moovit’s AR-powered “way finder” feature

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The value here for a company like Intel and its Mobileye subsidiary is data, which Moovit aggregates from myriad transit partners and corporations, as well as from its 40 million active users who generate more than 6 billion data points each day around traffic flow and user demand. Mobileye has made no secret of its plans for so-called “robotaxis,” and Moovit’s data will prove vital as it pushes into the driverless MaaS sphere.

Indeed, Intel and Mobileye intend to sell and lease self-driving vehicles for other companies and organizations to operate, while they also plan to deploy their own robotaxi services. But having the technology to operate fleets of driverless vehicles at scale is only part of the picture, and data and “customer-facing infrastructure” will also be required, according to Mobileye CEO Amnon Shashua.

In other words, Moovit gives Mobileye the knowledge it needs as it gears up to commercialize autonomous vehicle services in key markets around the world. Through the Moovit mobile app, Mobileye can push its robotaxi services as part of the broader trip planner offering, meaning that a commuter may see that the best way to get to their office is to take a driverless taxi from their home to the station two miles away, and then get a train the rest of the way.

The timing of Intel’s acquisition is notable, as it comes during a period of great uncertainty for companies such as Moovit — the global COVID-19 crisis has meant that public transport has been in low demand as people have stayed at home. Moovit itself publishes data regarding the impact of COVID-19 on public transit usage in key cities around the world, showing that it’s down by as much as 80% in some areas.

Above: Moovit data showing decline in public transit during COVID-19

As with other companies during the COVID-19 crisis, Moovit has sought new ways to keep business going. Last month it launched an emergency mobilization platform that makes it easier for transit organizations to redeploy their unused vehicle fleets to create new on-demand transport services for frontline workers. Corporations can also use the platform to arrange dedicated pickup services to get their essential employees safely to their place of work.

It’s not clear what role — if any — the COVID-19 crisis played in Moovit’s decision to sell now, but under the wings of a tech behemoth such as Intel, Moovit can worry just that little bit less about revenues in the coming months and years as society adjusts to what could become a “new normal” that leans heavily on remote working. The terms of the deal also seem like a decent exit for Moovit, which had raised around $ 131 million since its inception, including the $ 50 million series D cash injection led by Intel Capital in 2018.

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Big Data – VentureBeat

Rapid7 acquires cloud infrastructure automation platform DivvyCloud for $145 million

April 28, 2020 Big Data

Security data and analytics solutions provider Rapid7 today announced its intent to acquire DivvyCloud, a startup developing a cloud infrastructure automation platform, for approximately $ 145 million in cash and stock. The companies expect the deal to close during Q2 2020, subject to approval and closing conditions.

The acquisition — which comes two years after Rapid7’s initial public offering — is a spot of bright news in a startup ecosystem that’s seen hundreds of companies lay off workers since March, owing to coronavirus headwinds. And it points to the cybersecurity market’s strength at a time when enterprises are experiencing a spike in malware campaigns using coronavirus misinformation. Barracuda Networks reports that it saw a 667% increase in phishing emails linked to the coronavirus during the month of March.

DivvyCloud, which is headquartered in Arlington, Virginia, has its origins in the infrastructure teams at Electronic Arts and its subsidiary BioWare Mythics. There, DivvyCloud CEO Brian Johnson and CTO Chris DeRamus managed over 5,000 servers across five different countries with millions of paying subscribers. The two left EA in 2012 to develop a product that could provide a consolidated view and framework for the types of hybrid cloud environments they themselves oversaw.

DivvyCloud’s software-as-a-service (SaaS) platform offers real-time remediation with configurable bots and over 200 out-of-the-box guardrail policies. It works across public clouds such as Amazon Web Services, Google Cloud, and Azure and protects against things like insecure interfaces and APIs, misconfigurations, weak authentication, account hijacking, and data breaches with a robust user and permission management system, all while integrating with popular DevOps platforms like Splunk, ServiceNow, Jira, Slack, and PagerDuty.

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As for Boston-based Rapid7, the company offers a range of enterprise-focused cybersecurity services including vulnerability management, user behavior analytics, and phishing protection. It owns and maintains the Metasploit Project, a project that provides information about security vulnerabilities and tools for penetration testing, and it recently refreshed Insight — its platform that analyzes over 50 billion events and millions of assets daily — with new vulnerability management and app security testing products.

Insight — which Rapid7 says is built on nearly two decades of research, a constantly expanding vulnerability and exploit database, Metasploit, and learnings from thousands of penetration tests and an in-house threat-hunting team — combines with predictive analytics and operates on customer data from network scans, logs, and endpoints via agents and data connectors. In this way, it’s able to derive insights from the data, delivering guidance in the form of risk scores and alerts for incident detection, app security, and IT optimization.

Insight’s InsightIDR offering finds attackers in millions of events and gives IT team members the ability to search endpoints and data in real time. InsightUBA helps to detect, investigate, and stop threats with smart attack detection and incident response tools. Logentries centralizes logs and ingests data to provide answers to operations questions, while Nexpose accounts for vulnerabilities, controls, and configurations to spot sources of security risk. And AppSpider dynamically assesses custom web, mobile, and cloud apps for vulnerabilities across environments.

DivvyCloud raised $ 29 million to date prior to the acquisition from backers including Providence Strategic Growth, MissionOG, and RTP Ventures, with the most recent round — a $ 19 million series B — closing in April 2019. In May 2019, Johnson told VentureBeat that it had doubled its staff and client base from May 2018, bringing on customers like Discovery Communications, Sky, Mediacorp, Twilio, GE, Fannie Mae, Turner, Autodesk, Kroger, and Pizza Hut.

During its Q4 2019 earnings call, Rapid7 announced 16% year-over-year client growth and a 35% uptick in annualized recurring revenue (ARR) from 2018 to $ 338.7 million. At last count, it had more than 9,000 businesses using its product suite.

One thing’s for certain: There’s no shortage of competition in the cyberthreat detection and remediation space. Ironscales employs AI and machine learning to defeat organization-wide phishing attacks in real time, and France- and Boston-based Vade recently raised $ 79 million to further develop its filtering stack that protects against compromise, malware, and spam. There’s also Tessian, which uses machine learning for securing enterprise mail, and Valimail, which nabbed $ 45 million last year to thwart email phishing attacks. That’s not to mention ZeroFox — it novelly taps AI to surface threats of violence and identify deepfake videos, or videos that take a person in an existing image, audio recording, or video and replace them with someone else’s likeness using AI.

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Big Data – VentureBeat

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