Dec
06
2018
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Looker snags $103 million investment on $1.6 billion valuation

Looker has been helping customers visualize and understand their data for seven years, and today it got a big reward, a $103 million Series E investment on a $1.6 billion valuation.

The round was led by Premji Invest, with new investment from Cross Creek Advisors and participation from the company’s existing investors. With today’s investment, Looker has raised $280.5 million, according the company.

In spite of the large valuation, Looker CEO Frank Bien really wasn’t in the mood to focus on that particular number, which he said was arbitrary, based on the economic conditions at the time of the funding round. He said having an executive team old enough to remember the dot-com bubble from the late 1990s and the crash of 2008 keeps them grounded when it comes to those kinds of figures.

Instead, he preferred to concentrate on other numbers. He reported that the company has 1,600 customers now and just crossed the $100 million revenue run rate, a significant milestone for any enterprise SaaS company. What’s more, Bien reports revenue is still growing 70 percent year over year, so there’s plenty of room to keep this going.

He said he took such a large round because there was interest and he believed that it was prudent to take the investment as they move deeper into enterprise markets. “To grow effectively into enterprise customers, you have to build more product, and you have to hire sales teams that take longer to activate. So you look to grow into that, and that’s what we’re going to use this financing for,” Bien told TechCrunch.

He said it’s highly likely that this is the last private fundraising the company will undertake as it heads toward an IPO at some point in the future. “We would absolutely view this as our last round unless something drastic changed,” Bien said.

For now, he’s looking to build a mature company that is ready for the public markets whenever the time is right. That involves building internal processes of a public company even if they’re not there yet. “You create that maturity either way, and I think that’s what we’re doing. So when those markets look okay, you could look at that as another funding source,” he explained.

The company currently has around 600 employees. Bien indicated that they added 200 this year alone and expect to add additional headcount in 2019 as the business continues to grow and they can take advantage of this substantial cash infusion.

Dec
06
2018
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LeanIX, the SaaS that lets enterprises map out their software architecture, closes $30M Series C

LeanIX, the Software-as-a-Service for “Enterprise Architecture Management,” has closed $30 million in Series C funding.

The round is led by Insight Venture Partners, with participation from previous investors Deutsche Telekom Capital Partners (DTCP), Capnamic Ventures and Iris Capital. It brings LeanIX’s total funding to nearly $40 million since the German company was founded in 2012.

Operating in the enterprise architecture space, previously the domain of a company’s IT team only, LeanIX’s SaaS might well be described as a “Google Maps for IT architectures.”

The software lets enterprises map out all of the legacy software or modern SaaS that the organisation is run on, including creating meta data on things like what business process it is used for or capable of supporting, what tech (and version) powers it, what teams are using or have access to it, who is responsible for it, as well as how the different architecture fits together.

From this vantage point, enterprises can not only keep a better handle on all of the software from different vendors they are buying in, including how that differs or might be better utilised across distributed teams, but also act in a more nimble way in terms of how they adopt new solutions or decommission legacy ones.

In a call with André Christ, co-founder and CEO, he described LeanIX as providing a “single source of truth” for an enterprise’s architecture. He also explained that the SaaS takes a semi-automatic approach to how it maps out that data. A lot of the initial data entry will need to be done manually, but this is designed to be done collaboratively across an organisation and supported by an “easy-to-use UX,” while LeanIX also extracts some data automatically via integrations with ServiceNow (e.g. scanning software on servers) or Signavio (e.g. how IT Systems are used in Business Processes).

More broadly, Christ tells me that the need for a solution like LeanIX is only increasing, as enterprise architecture has shifted away from monolithic vendors and software to the use of a sprawling array of cloud or on-premise software where each typically does one job or business process really well, rather than many.

“With the rising adoption of SaaS, multi-cloud and microservices, an agile management of the Enterprise Architecture is harder to achieve but more important than ever before,” he says. “Any company in any industry using more than a hundred applications is facing this challenge. That’s why the opportunity is huge for LeanIX to define and own this category.”

To that end, LeanIX says the investment will be used to accelerate growth in the U.S. and for continued product innovation. Meanwhile, the company says that in 2018 it achieved several major milestones, including doubling its global customer base, launching operations in Boston and expanding its global headcount with the appointment of several senior-level executives. Enterprises using LeanIX include Adidas, DHL, Merck and Santander, with strategic partnerships with Deloitte, ServiceNow and PwC, among others.

“For businesses today, effective enterprise architecture management is critical for driving digital transformation, and requires robust tools that enable collaboration and agility,” said Teddie Wardi, principal at Insight Venture Partners, in a statement. “LeanIX is a pioneer in the space of next-generation EA tools, achieved staggering growth over the last year, and is the trusted partner for some of today’s largest and most complex organizations. We look forward to supporting its continued growth and success as one of the world’s leading software solutions for the modernization of IT architectures.”

Dec
05
2018
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Workato raises $25M for its integration platform

Workato, a startup that offers an integration and automation platform for businesses that competes with the likes of MuleSoft, SnapLogic and Microsoft’s Logic Apps, today announced that it has raised a $25 million Series B funding round from Battery Ventures, Storm Ventures, ServiceNow and Workday Ventures. Combined with its previous rounds, the company has now received investments from some of the largest SaaS players, including Salesforce, which participated in an earlier round.

At its core, Workato’s service isn’t that different from other integration services (you can think of them as IFTTT for the enterprise), in that it helps you to connect disparate systems and services, set up triggers to kick off certain actions (if somebody signs a contract on DocuSign, send a message to Slack and create an invoice). Like its competitors, it connects to virtually any SaaS tool that a company would use, no matter whether that’s Marketo and Salesforce, or Slack and Twitter. And like some of its competitors, all of this can be done with a drag-and-drop interface.

What’s different, Workato founder and CEO Vijay Tella tells me, is that the service was built for business users, not IT admins. “Other enterprise integration platforms require people who are technical to build and manage them,” he said. “With the explosion in SaaS with lines of business buying them — the IT team gets backlogged with the various integration needs. Further, they are not able to handle all the workflow automation needs that businesses require to streamline and innovate on the operations.”

Battery Ventures’ general partner Neeraj Agrawal also echoed this. “As we’ve all seen, the number of SaaS applications run by companies is growing at a very rapid clip,” he said. “This has created a huge need to engage team members with less technical skill-sets in integrating all these applications. These types of users are closer to the actual business workflows that are ripe for automation, and we found Workato’s ability to empower everyday business users super compelling.”

Tella also stressed that Workato makes extensive use of AI/ML to make building integrations and automations easier. The company calls this Recipe Q. “Leveraging the tens of billions of events processed, hundreds of millions of metadata elements inspected and hundreds of thousands of automations that people have built on our platform — we leverage ML to guide users to build the most effective integration/automation by recommending next steps as they build these automations,” he explained. “It recommends the next set of actions to take, fields to map, auto-validates mappings, etc. The great thing with this is that as people build more automations — it learns from them and continues to make the automation smarter.”

The AI/ML system also handles errors and offers features like sentiment analysis to analyze emails and detect their intent, with the ability to route them depending on the results of that analysis.

As part of today’s announcement, the company is also launching a new AI-enabled feature: Automation Editions for sales, marketing and HR (with editions for finance and support coming in the future). The idea here is to give those departments a kit with pre-built workflows that helps them to get started with the service without having to bring in IT.

Dec
05
2018
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Camunda hauls in $28M investment as workflow automation remains hot

Camunda, a Berlin-based company that builds open-source workflow automation software, announced a €25 million (approximately $28 million) investment from Highland Europe today.

This is the company’s first investment in its 10-year history. CEO and co-founder Jakob Freund says the company has been profitable since Day One, but decided to bring in outside capital now to take on a more aggressive international expansion.

The company launched in 2008 and for the first five years offered business process management consulting services, but they found traditional offerings from companies like Oracle, IBM and Pega weren’t encouraging software developers to really embrace BPM and build new applications.

In 2013 the company decided to solve that problem and began a shift from consulting to software. “We launched our own open-source project, Camunda BPM, in 2013. We also offered a commercial distribution, obviously, because that’s where the revenue came from,” Freund explained.

The project took off and they flipped their revenue sources from 80 percent consulting/20 percent software to 90 percent software/10 percent consulting in the five years since first creating the product. They boast 200 paying customers and have built out an entire stack of products since their initial product launch.

The company expanded from 13 employees in 2013 to 100 today, with offices in Berlin and San Francisco. Freund wants to open more offices and to expand the head count. To do that, he felt the time was right to go out and get some outside money. He said they continue to be profitable and more than doubled their ARR (annual recurring revenue) in the last 12 months, but knowing they wanted to expand quickly, they wanted the investment as a hedge in case revenue slowed down during the expansion.

“However, we also want to invest heavily right now and build up the team very quickly over the next couple of years. And we want to do that in such a quick way that we want to make sure that if the revenue growth doesn’t happen as quickly as the headcount building, we’re not getting any situation where we would then need to go look funding,” he explained. Instead, they struck while the company and the overall workflow automation space is hot.

He says they want to open more sales and support offices on the east coast of the U.S. and move into Asia, as well. Further, they want to keep investing in the open-source products, and the new money gives them room to do all of this.

Dec
05
2018
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Pindrop raises $90M to bring its voice-fraud prevention to IoT devices and Europe

When it comes to how humans communicate with each other or with machines, voice is a major interface, with growth in the latter fuelled by the rise of artificial intelligence, faster computing technology and an explosion of new devices — some of which only, or primarily, work with voice commands. But the supreme reign of voice has also opened a window of opportunity for malicious hackers — specifically, in the area of voice fraud.

Now, a security startup called Pindrop is announcing that it has raised $90 million to tackle this with a platform that it says can identify even the most sophisticated impersonations and hacking attempts, by analysing nearly 1,400 acoustic attributes to verify if a caller or a voice command is legit.

“We live in a brave new world where everything you thought you knew about security needs to be challenged,” said Vijay Balasubramaniyan, co-founder, CEO and CTO of Pindrop, who built the company (with co-founders Ahamad Mustaque and Paul Judge) originally out of his PhD thesis.

The funding is a growth round aimed specifically at two areas. First, taking US-based Pindrop into more international markets, starting with Europe — Vijay spoke to me in London — and coming soon to Asia. And second, to expand from customer service scenarios — the vast majority of its business today — into any applications that use voice interfaces, such as connected car platforms, home security devices, smart offices and smart home speakers.

To that end, this Series D includes a mix of strategic and financial investors: led by London’s Vitruvian Partners, it also includes Allegion Ventures (the corporate venture arm of the security giant), Cross Creek, systems integrator Dimension Data (“As you grow you want to be able to sell through partners,” Balasubramaniyan says), Singapore-based EDBI (to help with its push into Asia), and Goldman Sachs. Google’s CapitalG, IVP, Andreessen Horowitz, GV and Citi Ventures — all previous investors — were also in this round.

(The latter group of investors also has at least one strategic name in it: Pindrop is already working with Google, the CEO said.)

Valuation is not being disclosed, but in Pindrop’s Series C round in 2017, the company was valued at $600 million post-mioney, according to PitchBook, and the valuation now is “much higher,” Balasubramaniyan said with a laugh. The company’s raised $212 million to date.

The crux of what Pindrop has built is a platform that makes a voice “fingerprint” that identifies not just the specific tone you emit, but how you speak, where you are typically calling from and the sounds of that space, and even your regular device — something we can do now with the rise of smartphones that we typically don’t share with others — with each handset having a unique acoustic profile. Matching all these against what is determined to be your “normal” circumstances helps to start to build verification, Balasubramaniyan explained.

Founded in 2011 in Atlanta, GA, most of Pindrop’s business today has been built around helping to prevent voice fraud in customer service engagements. That business, Balasubramaniyan said, is on the path to profitability by the first quarter of 2019 and continues to grow well, with a voice fraud problem in the space that costs the industry $22 billion ($14 billion in fraud, $8 billion in time and systems wasted on security questions). (Pindrop claims it has stopped over $350 million in voice-based fraud and attacks so far  in 2018.)

Current customers include eight of the 10 largest banks and five largest insurance companies in the U.S., with more than 200 million consumer accounts protected at the moment. 

“There are 3.6 million agents in customer service jobs in the UK, with one in every 89 people in the US in this role,” he noted. “But last year, there there were 4.4 million new assistants added to the market,” referring to all the devices, apps and services that have hit us, “and that’s where we realised that it’s about expansion for us.”

In cases like connected home or office scenarios, some of the ways that these might get hacked are only starting to become apparent.

Balasubramaniyan noted that it can be something as innocent as a little girl ordering an expensive doll house while playing with Alexa (Pindrop is also now starting to work with Amazon, too, as it happens), or something more nefarious like a fraudster calling your answering machine to command your smart home hub to unlock your front door.

But we are unlikely to turn away from voice interfaces, and that is where a company like Pindrop (as well as competitors like Verint) come in.

“Voice-enabled interfaces are expanding how consumers interact with IoT devices in their everyday lives – as well as IoT manufacturers’ ability to offer smarter and stronger solutions,” said Allegion Ventures President Rob Martens, in a statement. “We’re excited about the future of voice technology and see Pindrop as a pioneer in the space. We look forward to working with Vijay and his team to accelerate the adoption of voice technology into new markets.”

More generally, as we see the rise of more voice services it’s only natural that we will start to see more ways of trying to hack them. Pindrop puts an interesting focus on the aural details of an experience as a way of helping to fight that. It’s detail that we often overlook in today’s very visual culture, but it’s also in a way a return to more analogue days.

Balasubramaniyan said one of his inspirations for the startup was a story he read as a child in 2600, the Hacker publication, that stuck with him, about Bell Labs. There, they had a team of blind engineers who could identify problems on a phone line by listening to the dial tone. “They had golden hearing,” he said.

 

Dec
05
2018
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Salesforce wants to deliver more automated field service using IoT data

Salesforce has been talking about the Internet of Things for some time as a way to empower field service workers. Today, the company announced Field Service Lightning, a new component designed to deliver automated IoT data to service technicians in the field on their mobile devices.

Once you connect sensors in the field to Service Cloud, you can make this information available in an automated fashion to human customer service agents and pull in other data about the customer from Salesforce’s CRM system to give the CSR a more complete picture of the customer.

“Drawing on IoT signals surfaced in the Service Cloud console, agents can gauge whether device failure is imminent, quickly determine the source of the problem (often before the customer is even aware a problem exists) and dispatch the right mobile worker with the right skill set,” Salesforce’s SVP and GM for Salesforce Field Service Lightning Paolo Bergamo wrote in a blog post introducing the new feature.

The field service industry has been talking for years about using IoT data from the field to deliver more proactive service and automate the customer service and repair process. That’s precisely what this new feature is designed to do. Let’s say you have a “smart home” with a heating and cooling system that can transmit data to the company that installed your equipment. With a system like this in place, the sensors could tell your HVAC dealer that a part is ready to break down and automatically start a repair process (that would presumably include calling the customer to tell them about it). When a CSR determines a repair visit is required, the repair technician would receive all the details on their smart phone.

Customer Service Console view. Gif: SalesforceIt also could provide a smoother experience because the repair technician can prepare before he or she leaves for the visit with the right equipment and parts for the job and a better understanding of what needs to be done before arriving at the customer location. This should theoretically lead to more efficient service calls.

All of this is in line with a vision the field service industry has been talking about for some time that you could sell a subscription to a device like an air conditioning system instead of the device itself. This would mean that the dealer would be responsible for keeping it up and running and having access to data like this could help that vision to become closer to reality.

In reality, most companies are probably not ready to implement a system like this and most equipment in the field has not been fit with sensors to deliver this information to the Service Cloud. Still, companies like Salesforce, ServiceNow and ServiceMax (owned by GE) want to release products like this for early adopters and to have something in place as more companies look to put smarter systems in place in the field.

Dec
04
2018
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Cove.Tool wants to solve climate change one efficient building at a time

As the fight against climate change heats up, Cove.Tool is looking to help tackle carbon emissions one building at a time.

The Atlanta-based startup provides an automated big-data platform that helps architects, engineers and contractors identify the most cost-effective ways to make buildings compliant with energy efficiency requirements. After raising an initial round earlier this year, the company completed the final close of a $750,000 seed round. Since the initial announcement of the round earlier this month, Urban Us, the early-stage fund focused on companies transforming city life, has joined the syndicate comprised of Tech Square Labs and Knoll Ventures.

Helping firms navigate a growing suite of energy standards and options

Cove.Tool software allows building designers and managers to plug in a variety of building conditions, energy options, and zoning specifications to get to the most cost-effective method of hitting building energy efficiency requirements (Cove.Tool Press Image / Cove.Tool / https://covetool.com).

In the US, the buildings we live and work in contribute more carbon emissions than any other sector. Governments across the country are now looking to improve energy consumption habits by implementing new building codes that set higher energy efficiency requirements for buildings. 

However, figuring out the best ways to meet changing energy standards has become an increasingly difficult task for designers. For one, buildings are subject to differing federal, state and city codes that are all frequently updated and overlaid on one another. Therefore, the specific efficiency requirements for a building can be hard to understand, geographically unique and immensely variable from project to project.

Architects, engineers and contractors also have more options for managing energy consumption than ever before – equipped with tools like connected devices, real-time energy-management software and more-affordable renewable energy resources. And the effectiveness and cost of each resource are also impacted by variables distinct to each project and each location, such as local conditions, resource placement, and factors as specific as the amount of shade a building sees.

With designers and contractors facing countless resource combinations and weightings, Cove.Tool looks to make it easier to identify and implement the most cost-effective and efficient resource bundles that can be used to hit a building’s energy efficiency requirements.

Cove.Tool users begin by specifying a variety of project-specific inputs, which can include a vast amount of extremely granular detail around a building’s use, location, dimensions or otherwise. The software runs the inputs through a set of parametric energy models before spitting out the optimal resource combination under the set parameters.

For example, if a project is located on a site with heavy wind flow in a cold city, the platform might tell you to increase window size and spend on energy efficient wall installations, while reducing spending on HVAC systems. Along with its recommendations, Cove.Tool provides in-depth but fairly easy-to-understand graphical analyses that illustrate various aspects of a building’s energy performance under different scenarios and sensitivities.

Cove.Tool users can input granular project-specifics, such as shading from particular beams and facades, to get precise analyses around a building’s energy performance under different scenarios and sensitivities.

Democratizing building energy modeling

Traditionally, the design process for a building’s energy system can be quite painful for architecture and engineering firms.

An architect would send initial building designs to engineers, who then test out a variety of energy system scenarios over the course a few weeks. By the time the engineers are able to come back with an analysis, the architects have often made significant design changes, which then gets sent back to the engineers, forcing the energy plan to constantly be 1-to-3 months behind the rest of the building. This process can not only lead to less-efficient and more-expensive energy infrastructure, but the hectic back-and-forth can lead to longer project timelines, unexpected construction issues, delays and budget overruns.

Cove.Tool effectively looks to automate the process of “energy modeling.” The energy modeling looks to ease the pains of energy design in the same ways Building Information Modeling (BIM) has transformed architectural design and construction. Just as BIM creates predictive digital simulations that test all the design attributes of a project, energy modeling uses building specs, environmental conditions, and various other parameters to simulate a building’s energy efficiency, costs and footprint.

By using energy modeling, developers can optimize the design of the building’s energy system, adjust plans in real-time, and more effectively manage the construction of a building’s energy infrastructure. However, the expertise needed for energy modeling falls outside the comfort zones of many firms, who often have to outsource the task to expensive consultants.

The frustrations of energy system design and the complexities of energy modeling are ones the Cove.Tool team knows well. Patrick Chopson and Sandeep Ajuha, two of the company’s three co-founders, are former architects that worked as energy modeling consultants when they first began building out the Cove.Tool software.

After seeing their clients’ initial excitement over the ability to quickly analyze millions of combinations and instantly identify the ones that produce cost and energy savings, Patrick and Sandeep teamed up with CTO Daniel Chopson and focused full-time on building out a comprehensive automated solution that would allow firms to run energy modeling analysis without costly consultants, more quickly, and through an interface that would be easy enough for an architectural intern to use.

So far there seems to be serious demand for the product, with the company already boasting an impressive roster of customers that includes several of the country’s largest architecture firms, such as HGA, HKS and Cooper Carry. And the platform has delivered compelling results – for example, one residential developer was able to identify energy solutions that cost $2 million less than the building’s original model. With the funds from its seed round, Cove.Tool plans further enhance its sales effort while continuing to develop additional features for the platform.

Changing decision-making and fighting climate change

The value proposition Cove.Tool hopes to offer is clear – the company wants to make it easier, faster and cheaper for firms to use innovative design processes that help identify the most cost-effective and energy-efficient solutions for their buildings, all while reducing the risks of redesign, delay and budget overruns.

Longer-term, the company hopes that it can help the building industry move towards more innovative project processes and more informed decision-making while making a serious dent in the fight against emissions.

“We want to change the way decisions are made. We want decisions to move away from being just intuition to become more data-driven.” The co-founders told TechCrunch.

“Ultimately we want to help stop climate change one building at a time. Stopping climate change is such a huge undertaking but if we can change the behavior of buildings it can be a bit easier. Architects and engineers are working hard but they need help and we need to change.”

Dec
04
2018
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Microsoft and Docker team up to make packaging and running cloud-native applications easier

Microsoft and Docker today announced a new joint open-source project, the Cloud Native Application Bundle (CNAB), that aims to make the lifecycle management of cloud-native applications easier. At its core, the CNAB is nothing but a specification that allows developers to declare how an application should be packaged and run. With this, developers can define their resources and then deploy the application to anything from their local workstation to public clouds.

The specification was born inside Microsoft, but as the team talked to Docker, it turns out that the engineers there were working on a similar project. The two decided to combine forces and launch the result as a single open-source project. “About a year ago, we realized we’re both working on the same thing,” Microsoft’s Gabe Monroy told me. “We decided to combine forces and bring it together as an industry standard.”

As part of this, Microsoft is launching its own reference implementation of a CNAB client today. Duffle, as it’s called, allows users to perform all the usual lifecycle steps (install, upgrade, uninstall), create new CNAB bundles and sign them cryptographically. Docker is working on integrating CNAB into its own tools, too.

Microsoft also today launched Visual Studio extension for building and hosting these bundles, as well as an example implementation of a bundle repository server and an Electron installer that lets you install a bundle with the help of a GUI.

Now it’s worth noting that we’re talking about a specification and reference implementations here. There is obviously a huge ecosystem of lifecycle management tools on the market today that all have their own strengths and weaknesses. “We’re not going to be able to unify that tooling,” said Monroy. “I don’t think that’s a feasible goal. But what we can do is we can unify the model around it, specifically the lifecycle management experience as well as the packaging and distribution experience. That’s effectively what Docker has been able to do with the single-workload case.”

Over time, Microsoft and Docker would like for the specification to end up in a vendor-neutral foundation. Which one remains to be seen, though the Open Container Initiative seems like the natural home for a project like this.

Dec
04
2018
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FortressIQ raises $12M to bring new AI twist to process automation

FortressIQ, a startup that wants to bring a new kind of artificial intelligence to process automation called imitation learning, emerged from stealth this morning and announced it has raised $12 million.

The Series A investment came entirely from a single venture capital firm, Light Speed Venture Partners. Today’s funding comes on top of $4 million in seed capital the company raised previously from Boldstart Ventures, Comcast Ventures and Eniac Ventures.

Pankaj Chowdhry, founder and CEO of FortressIQ, says that his company basically replaces high-cost consultants who are paid to do time and motion studies and automates that process in a fairly creative way. It’s a bit like Robotics Process Automation (RPA), a space that is attracting a lot of investment right now, but instead of simply recording what’s happening on the desktop, and reproducing that digitally, it takes it a step further in a process called “imitation learning.”

“We want to be able to replicate human behavior through observation. We’re targeting this idea of how can we help people understand their processes. But imitation learning is I think the most interesting area of artificial intelligence because it focuses not on what AI can do, but how can AI learn and adapt,” he explained

They start by capturing a low-bandwidth movie of the process. “So we build virtual processors. And basically the idea is we have an agent that gets deployed by your enterprise IT group, and it integrates into the video card,” Chowdhry explained.

He points out that it’s not actually using a camera, but it captures everything going on, as a person interacts with a Windows desktop. In that regard it’s similar to RPA. “The next component is our AI models and computer vision. And we build these models that can literally watch the movie and transcribe the movie into what we call a series of software interactions,” he said.

Another key differentiator here is that they have built a data mining component on top of this, so if the person in the movie is doing something like booking an invoice, and stops to check email or Slack, FortressIQ can understand when an activity isn’t part of the process and filters that out automatically.

The product will be offered as a cloud service. Chowdhry’s previous company, Third Pillar Systems, was acquired by Genpact in 2013.

Dec
04
2018
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Fivetran announces $15M Series A to build automated data pipelines

Fivetran, a startup that builds automated data pipelines between data repositories and cloud data warehouses and analytics tools, announced a $15 million Series A investment led by Matrix Partners.

Fivetran helps move data from source repositories like Salesforce and NetSuite to data warehouses like Snowflake or analytics tools like Looker. Company CEO and co-founder George Fraser says the automation is the key differentiator here between his company and competitors like Informatica and SnapLogic.

“What makes Fivetran different is that it’s an automated data pipeline to basically connect all your sources. You can access your data warehouse, and all of the data just appears and gets kept updated automatically,” Fraser explained. While he acknowledges that there is a great deal of complexity behind the scenes to drive that automation, he stresses that his company is hiding that complexity from the customer.

The company launched out of Y Combinator in 2012, and other than $4 million in seed funding along the way, it has relied solely on revenue up until now. That’s a rather refreshing approach to running an enterprise startup, which typically requires piles of cash to build out sales and marketing organizations to compete with the big guys they are trying to unseat.

One of the key reasons they’ve been able to take this approach has been the company’s partner strategy. Having the ability to get data into another company’s solution with a minimum of fuss and expense has attracted data-hungry applications. In addition to the previously mentioned Snowflake and Looker, the company counts Google BigQuery, Microsoft Azure, Amazon Redshift, Tableau, Periscope Data, Salesforce, NetSuite and PostgreSQL as partners.

Ilya Sukhar, general partner at Matrix Partners, who will be joining the Fivetran board under the terms of deal sees a lot of potential here. “We’ve gone from companies talking about the move to the cloud to preparing to execute their plans, and the most sophisticated are making Fivetran, along with cloud data warehouses and modern analysis tools, the backbone of their analytical infrastructure,” Sukhar said in a statement.

They currently have 100 employees spread out across four offices in Oakland, Denver, Bangalore and Dublin. They boast 500 customers using their product including Square, WeWork, Vice Media and Lime Scooters, among others.

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