VMware announces intent to buy Avi Networks, startup that raised $115M

VMware has been trying to reinvent itself from a company that helps you build and manage virtual machines in your data center to one that helps you manage your virtual machines wherever they live, whether that’s on prem or the public cloud. Today, the company announced it was buying Avi Networks, a six-year-old startup that helps companies balance application delivery in the cloud or on prem in an acquisition that sounds like a pretty good match. The companies did not reveal the purchase price.

Avi claims to be the modern alternative to load balancing appliances designed for another age when applications didn’t change much and lived on prem in the company data center. As companies move more workloads to public clouds like AWS, Azure and Google Cloud Platform, Avi is providing a more modern load-balancing tool, that not only balances software resource requirements based on location or need, but also tracks the data behind these requirements.

Diagram: Avi Networks

VMware has been trying to find ways to help companies manage their infrastructure, whether it is in the cloud or on prem, in a consistent way, and Avi is another step in helping them do that on the monitoring and load-balancing side of things, at least.

Tom Gillis, senior vice president and general manager for the networking and security business unit at VMware sees, this acquisition as fitting nicely into that vision. “This acquisition will further advance our Virtual Cloud Network vision, where a software-defined distributed network architecture spans all infrastructure and ties all pieces together with the automation and programmability found in the public cloud. Combining Avi Networks with VMware NSX will further enable organizations to respond to new opportunities and threats, create new business models, and deliver services to all applications and data, wherever they are located,” Gillis explained in a statement.

In a blog post,  Avi’s co-founders expressed a similar sentiment, seeing a company where it would fit well moving forward. “The decision to join forces with VMware represents a perfect alignment of vision, products, technology, go-to-market, and culture. We will continue to deliver on our mission to help our customers modernize application services by accelerating multi-cloud deployments with automation and self-service,” they wrote. Whether that’s the case, time will tell.

Among Avi’s customers, which will now become part of VMware, are Deutsche Bank, Telegraph Media Group, Hulu and Cisco. The company was founded in 2012 and raised $115 million, according to Crunchbase data. Investors included Greylock, Lightspeed Venture Partners and Menlo Ventures, among others.

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.

WhatsApp is finally going after outside firms that are abusing its platform

WhatsApp has so far relied on past dealings with bad players within its platform to ramp up its efforts to curtail spam and other automated behavior. The Facebook -owned giant has now announced an additional step it plans to take beginning later this year to improve the health of its messaging service: going after those whose mischievous activities can’t be traced within its platform.

The messaging platform, used by more than 1.5 billion users, confirmed on Tuesday that starting December 7 it will start considering signals off its platform to pursue legal actions against those who are abusing its system. The company will also go after individuals who — or firms that — falsely claim to have found ways to cause havoc on the service.

The move comes as WhatsApp grapples with challenges such as spam behavior to push agendas or spread false information on its messaging service in some markets. “This serves as notice that we will take legal action against companies for which we only have off-platform evidence of abuse if that abuse continues beyond December 7, 2019, or if those companies are linked to on-platform evidence of abuse before that date,” it said in an FAQ post on its site.

A WhatsApp spokesperson confirmed the change to TechCrunch, adding, “WhatsApp was designed for private messaging, so we’ve taken action globally to prevent bulk messaging and enforce limits on how WhatsApp accounts that misuse WhatsApp can be used. We’ve also stepped up our ability to identify abuse, which helps us ban 2 million accounts globally per month.”

Earlier this year, WhatsApp said (PDF) it had built a machine learning system to detect and weed out users who engage in inappropriate behavior, such as sending bulk messages or creating multiple accounts with intention to harm the service. The platform said it was able to assess the past dealings with problematic behaviors to ban 20% of bad accounts at the time of registration itself.

But the platform is still grappling to contain abusive behavior, a Reuters report claimed last month. The news agency reported about tools that were readily being sold in India for less than $15 that claimed to bypass some of the restrictions that WhatsApp introduced in recent months.

TechCrunch understands that with today’s changes, WhatsApp is going after those same set of bad players. It has already started to send cease and desist letters to marketing companies that claim to abuse WhatsApp in recent months, a person familiar with the matter said.

GitHub hires former Bitnami co-founder Erica Brescia as COO

It’s been just over a year since Microsoft bought GitHub for $7.5 billion, but the company has grown in that time, and today it announced that it has hired former Bitnami COO and cofounder, Erica Brescia to be its COO.

Brescia handled COO duties at Bitnami from its founding in 2011 until it was sold to VMware last month. In a case of good timing, GitHub was looking to fill its COO role and after speaking to CEO Nat Friedman, she believed it was going to be a good fit. The GitHub mission to provide a place for developers to contribute to various projects fits in well with what she was doing at Bitnami, which provided a way to deliver software to developers in the form of packages such as containers or Kubernetes Helm charts.

New GitHub COO Erica Brescia

She sees that experience of building a company, of digging in and taking on whatever roles the situation required, translating well as she takes over as COO at a company that is growing as quickly as GitHub. “I was really shocked to see how quickly GitHub is still growing, and I think bringing that kind of founder mentality, understanding where the challenges are and working with a team to come up with solutions, is something that’s going to translate really well and help the company to successfully scale,” Brescia told TechCrunch.

She admits that it’s going to be a different kind of challenge working with a company she didn’t help build, but she sees a lot of similarities that will help her as she moves into this new position. Right after selling a company, she obviously didn’t have to take a job right away, but this one was particularly compelling to her, too much so to leave on the table.

“I think there were a number of different directions that I could have gone coming out of Bitnami, and GitHub was really exciting to me because of the scale of the opportunity and the fact that it’s so focused on developers and helping developers around the world, both open source and enterprise, collaborate on the software that really powers the world moving forward,” she said.

She says as COO at a growing company, it will fall on her to find more efficient ways to run things as the company continues to scale. “When you have a company that’s growing that quickly, there are inevitably things that probably could be done more efficiently at the scale, and so one of the first things that I plan on spending time in on is just understanding from the team is where the pain points are, and what can we do to help the organization run like a more well oiled machine.”

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.

Crane, a new early-stage London VC focused on ‘intelligent’ enterprise startups, raises $90M fund

Crane Venture Partners, a newish London-based early-stage VC targeting what it calls “intelligent” enterprise startups, is officially outing today.

Founded by Scott Sage and Krishna Visvanathan, who were both previously at DFJ Esprit, “Crane I” has had a second closing totalling $90 million, money the firm is investing in enterprise companies that are data-driven. Sage and are Visvanathan are joined by Crane Partner Andy Leaver.

Specifically, Crane is seeking pre-Series A startups based in Europe, with a willingness to write the first institutional cheque. The firm is particularly bullish about London, noting that 90% of cloud and enterprise software companies that went public in the last 8-10 years opened their first international office in London. Investments already made from the fund include Aire, Avora, Stratio Automotive and Tessian.

Crane’s anchor LPs are MassMutual Ventures, the venture capital arm of MassMutual Life Insurance Corporation (MassMutual), and the U.K. taxpayer funded British Patient Capital (BPC), along with other institutions, founders and VCs spanning the U.S., Europe and Asia. In addition, Crane has formed a strategic partnership with MassMutual Ventures to give Crane and its portfolio companies “deep access” to new markets and networks as they expand internationally.

Below follows an email Q&A with Crane founders Scott Sage and Krishna Visvanathan, where we discuss the new fund’s remit, why Crane is so bullish on the enterprise, London after Brexit, and why the enterprise isn’t so boring after all!

TC: Why does London and/or the world need a new enterprise focused VC?

SS: Just to correct you Steve, we’re an enterprise only seed fund :) – which does make us somewhat unique. We back founders who have a differentiated product vision but who haven’t demonstrated the commercial metrics that our counterparts typically look for. We see opportunity and not just risk.

TC: It feels like years since I first heard you were both raising a fund together and of course I know that Crane has already made 20+ investments. So why did it take you so long to close and why are you only just officially announcing now?

KV: It was definitely a humbling experience and took us 12 months longer than we would have hoped! We held our first close for Crane I, our institutional fund, in July 2018, two and a half years from when we started raising. We had previously established a pre-cursor fund and started investing in Q1 2016, quietly building up our portfolio and presence. We had to hold off on discussing the fund until we concluded the final close a few weeks ago for regulatory and compliance reasons.

TC: You say that Crane is broadly targeting early-stage “intelligent” enterprise startups — as opposed to unintelligent ones! — but can you be more specific with regards to cheque size and stage and any particular verticals, themes or technologies you plan to invest in?

SS: Data is central to our thesis – the entire enterprise stack will need to be rebuilt to understand and learn from data, which is what we mean by intelligence. The majority of installed enterprise applications today are workflow tools and don’t do anything intelligent for the user or the organisation. We’re also excited about entirely new products for new markets that didn’t previously exist.

Our first cheques range from $750k to $3m, with sizeable follow on reserves to support our companies through Series B. We view our sweet spot as helping companies build their go-to market strategies and are happy to invest pre-revenue (approximately half of our portfolio at the time of investment), although we prefer to invest post-product.

TC: Given that you typically invest pre-Series A, where an enterprise startup may be pre-revenue and not yet have anything like definitive market fit, what are the standout qualities you look for in founding teams or the assumptions they are betting on?

KV: You mean apart from the obvious ones that every VC would say about passion, vision, hunger etc (mea culpa!)? We love highly technical teams who have a visceral understanding of the problem they are solving – usually because they lived through it previously. Many of the founders we’ve backed are reimagining the market segments they are addressing.

TC: Almost every new fund these days is talking about its operational support for portfolio companies. What does Crane do to actively support the very early-stage companies you back?

SS: Our sole focus is on supporting founders with their go-to-market strategy which encompasses everything from product positioning and generating marketing leads to building a high performing sales team, renewing and upselling customers. We have formal modules we run behind the scenes with a new company once we’ve invested and we’re also building out a stable of venture partners who are specialists in these areas. We believe that there is a multiplier effect in creating a community of similar staged businesses with parallels in their business models.

TC: Although Crane is pan-European, I know you are especially bullish on London as a leader in creating and adopting enterprise technology, why is that?

KV: We believe London has a great concentration of customers, data science and software talent, commercial and go-to-market talent. 90% of cloud and enterprise software companies that went public in the last 8-10 years opened their first international office in London. And, we’ve also seen a newfound boldness amongst young first-time founders who are not bound by the limits of their imaginations. Look at Onfido, Tessian and Senseon – all first-time founding teams we have backed who are building category-defining businesses.

TC: Which brings us to Brexit. How does Crane view the U.K. exiting the EU and the challenges this will undoubtedly create for tech and enterprise companies, in particular relating to hiring?

SS: We are believers in a global economy and the UK being a major contributor to it. The reason London is still the startup capital of Europe is because of its diversity and openness. The UK exiting the EU is counter to this which we believe will have a negative impact on our ability to attract talent and remain at the forefront of European tech.

TC: Lastly, enterprise tech is often viewed as “unsexy” and something many journalists (myself included) yawn at, even though it is a huge market and arguably the hidden software that the engine rooms of the world economy run on. Tell me something I might not already know about enterprise tech that I can repeat at a dinner party without sending everyone else to sleep?

KV: Imagine a world where you turn on your laptop and your day is pre-organised for you, your email self protects against catastrophic mistakes, your digital identity is portable, your physical workspace syncs with your calendar and auto reserves meeting rooms, and your creditworthiness is something you control, leaving you to focus on channelling your creativity as a journalist and not deal with pfaff. That’s the intelligent enterprise right there in the guise of Tessian, Onfido, OpenSensors and Aire, a selection of the companies in our portfolio. It may start with the enterprise, but ultimately, the products and businesses that are being built are all for people.

TC: Scott, Krishna, thanks for talking to TechCrunch!

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.

 

With Tableau and Mulesoft, Salesforce gains full view of enterprise data

Back in the 2010 timeframe, it was common to say that content was king, but after watching Google buy Looker for $2.6 billion last week and Salesforce nab Tableau for $15.7 billion this morning, it’s clear that data has ascended to the throne in a business context.

We have been hearing about Big Data for years, but we’ve probably reached a point in 2019 where the data onslaught is really having an impact on business. If you can find the key data nuggets in the big data pile, it can clearly be a competitive advantage, and companies like Google and Salesforce are pulling out their checkbooks to make sure they are in a position to help you out.

While Google, as a cloud infrastructure vendor, is trying to help companies on its platform and across the cloud understand and visualize all that data, Salesforce as a SaaS vendor might have a different reason — one that might surprise you — given that Salesforce was born in the cloud. But perhaps it recognizes something fundamental. If it truly wants to own the enterprise, it has to have a hybrid story, and with Mulesoft and Tableau, that’s precisely what it has — and why it was willing to spend around $23 billion to get it.

Making connections

Certainly, Salesforce chairman Marc Benioff has no trouble seeing the connections between his two big purchases over the last year. He sees the combination of Mulesoft connecting to the data sources and Tableau providing a way to visualize as a “beautiful thing.”

Vectra lands $100M Series E investment for AI-driven network security

Vectra, a seven-year old company that helps customers detect intrusions at the network level, whether in the cloud or on premises, announced a $100 million Series E funding round today led by TCV. Existing investors including Khosla Ventures and Accel also participated in the round, which brings the total raised to over $200 million, according to the company.

As company CEO Hitesh Sheth explained, there are two primary types of intrusion detection. The first is end point detection and the second is his company’s area of coverage, network detection and response or NDR.  He says that by adding a layer of artificial intelligence, it improves the overall results.

“One of the keys to our success has been applying AI to network traffic, the networking side of NDR, to look for the signal in the noise. And we can do this across the entire infrastructure, from the data center to the cloud all the way into end user traffic including IoT,” he explained.

He said that as companies move their data to the cloud, they are looking for ways to ensure the security of their most valuable data assets, and he says his company’s NDR solution can provide that. In fact, securing the cloud side of the equation is one of the primary investment focuses for this round.

Tim McAdam from lead investor TVC, says that the AI piece is a real differentiator for Vectra and one that attracted his firm to invest in the company. He said that while he realized that AI is an overused term these days, after talking to 30 customers he heard over and over again that Vectra’s AI-driven solution was a differentiator over competing products. “All of them have decided to standardize on the Vectra Cognito because to a person, they spoke of the efficacy and the reduction of their threat vectors as a result of standardizing on Vectra,” McAdam told TechCrunch.

The company was founded in 2012 and currently has 240. That is expected to double in the year to 18 months with this funding.

Google continues to preach multi-cloud approach with Looker acquisition

When Google announced it was buying Looker yesterday morning for $2.6 billion, you couldn’t blame some of the company’s 1,600 customers if they worried a bit if Looker would continue its multi-cloud approach. But Google Cloud chief Thomas Kurian made clear the company will continue to support an open approach to its latest purchase when it joins the fold later this year.

It’s consistent with the messaging from Google Next, the company’s cloud conference in April. It was looking to portray itself as the more open cloud. It was going to be friendlier to open-source projects, running them directly on Google Cloud. It was going to provide a way to manage your workloads wherever they live, with Anthos.

Ray Wang, founder and principal analyst at Constellation Research, says that in a multi-cloud world, Looker represented one of the best choices, and that could be why Google went after it. “Looker’s strengths include its centralized data-modeling and governance, which promotes consistency and reuse. It runs on top of modern cloud databases including Google BigQuery, AWS Redshift and Snowflake,” Wang told TechCrunch. He added, “They wanted to acquire a tool that is as easy to use as Microsoft Power BI and as deep as Tableau.”

Patrick Moorhead, founder and principal analyst at Moor Insights & Strategy, also sees this deal as part of a consistent multi-cloud message from Google. “I do think it is in alignment with its latest strategy outlined at Google Next. It has talked about rich analytics tools that could pull data from disparate sources,” he said.

Kurian pushing the multi-cloud message

Google Cloud CEO Thomas Kurian, who took over from Diane Greene at the end of last year, was careful to emphasize the company’s commitment to multi-cloud and multi-database support in comments to media and analysts yesterday. “We first want to reiterate, we’re very committed to maintaining local support for other clouds, as well as to serve data from multiple databases because customers want a single analytics foundation for their organization, and they want to be able to in the analytics foundation, look at data from multiple data sources. So we’re very committed to that,” Kurian said yesterday.

From a broader customer perspective, Kurian sees Looker providing customers with a single way to access and visualize data. “One of the things that is challenging for organizations in operationalizing business intelligence, that we feel that Looker has done really well, is it gives you a single place to model your data, define your data definitions — like what’s revenue, who’s a gold customer or how many servers tickets are open — and allows you then to blend data across individual data silos, so that as an organization, you’re working off a consistent set of metrics,” Kurian explained.

In a blog post announcing the deal, Looker CEO Frank Bien sought to ease concerns that the company might move away from the multi-cloud, multi-database support. “For customers and partners, it’s important to know that today’s announcement solidifies ours as well as Google Cloud’s commitment to multi-cloud. Looker customers can expect continuing support of all cloud databases like Amazon Redshift, Azure SQL, Snowflake, Oracle, Microsoft SQL Server, Teradata and more,” Bien wrote in the post.

No antitrust concerns

Kurian also emphasized that this deal shouldn’t attract the attention of antitrust regulators, who have been sniffing around the big tech companies like Google/Alphabet, Apple and Amazon as of late. “We’re not buying any data along with this transaction. So it does not introduce any concentration risk in terms of concentrating data. Secondly, there are a large number of analytic tools in the market. So by just acquiring Looker, we’re not further concentrating the market in any sense. And lastly, all the other cloud players also have their own analytic tools. So it represents a further strengthening of our competitive position relative to the other players in the market,” he explained. Not to mention its pledge to uphold the multi-cloud and multi-database support, which should show it is not doing this strictly to benefit Google or to draw customers specifically to GCP.

Just this week, the company announced a partnership with Snowflake, the cloud data warehouse startup that has raised almost a billion dollars, to run on Google Cloud Platform. It already runs AWS and Microsoft Azure. In fact, Wang suggested that Snowflake could be next on Google’s radar as it tries to build a multi-cloud soup-to-nuts analytics offering.

Regardless, with Looker the company has a data analytics tool to complement its data processing tools, and together the two companies should provide a fairly comprehensive data solution. If they truly keep it multi-cloud, that should keep current customers happy, especially those who work with tools outside of the Google Cloud ecosystem or simply want to maintain their flexibility.