Oct
21
2020
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Secureframe raises $4.5M to help businesses speed up their compliance audits

While certifications for security management practices like SOC 2 and ISO 27001 have been around for a while, the number of companies that now request that their software vendors go through (and pass) the audits to be in compliance with these continues to increase. For a lot of companies, that’s a harrowing process, so it’s maybe no surprise that we are also seeing an increase in startups that aim to make this process easier. Earlier this month, Strike Graph, which helps automate security audits, announced its $3.9 million round, and today, Secureframe, which also helps businesses get and maintain their SOC 2 and ISO 27001 certifications, is announcing a $4.5 million round.

Secureframe’s round was co-led by Base10 Partners and Google’s AI-focused Gradient Ventures fund. BoxGroup, Village Global, Soma Capital, Liquid2, Chapter One, Worklife Ventures and Backend Capital participated. Current customers include Stream, Hasura and Benepass.

Image Credits: Secureframe

Shrav Mehta, the company’s co-founder and CEO, spent time at a number of different companies, but he tells me the idea for Secureframe was mostly born during his time at direct-mail service Lob.

“When I was at Lob, we dealt with a lot of issues around security and compliance because we were sometimes dealing with very sensitive data, and we’d hop on calls with customers, had to complete thousand-line security questionnaires, do exhaustive security reviews, and this was a lot for a startup of our size at the time. But it’s just what our customers needed. So I started to see that pain,” Mehta said.

Secureframe co-founder and CEO Shrav Mehta

Secureframe co-founder and CEO Shrav Mehta

After stints at Pilot and Scale AI after he left Lob in 2017 — and informally helping other companies manage the certification process — he co-founded Secureframe together with the company’s CTO, Natasja Nielsen.

“Because Secureframe is basically adding a lot of automation with our software — and making the process so much simpler and easier — we’re able to bring the cost down to a point where this is something that a lot more companies can afford,” Mehta explained. “This is something that everyone can get in place from day one, and not really have to worry that, ‘hey, this is going to take all of our time, it’s going to take a year, it’s going to cost a lot of money.’ […] We’re trying to solve that problem to make it super easy for every organization to be secure from day one.”

The main idea here is to make the arcane certification process more transparent and streamline the process by automating many of the more labor-intensive tasks of getting ready for an audit (and it’s virtually always the pre-audit process that takes up most of the time). Secureframe does so by integrating with the most-often used cloud and SaaS tools (it currently connects to about 25 services) and pulling in data from them to check up on your security posture.

“It feels a lot like a QuickBooks or TurboTax-like experience, where we’ll essentially ask you to enter basic details about your business. We try to autofill as much of it as possible from third-party sources — then we ask you to connect up all the integrations your business uses,” Mehta explained.

The company plans to use much of the new funding to staff up and build out these integrations. Over time, it will also add support for other certifications like PCI, HITRUST and HIPAA.

Oct
21
2020
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Contrast launches its security observability platform

Contrast, a developer-centric application security company with customers that include Liberty Mutual Insurance, NTT Data, AXA and Bandwidth, today announced the launch of its security observability platform. The idea here is to offer developers a single pane of glass to manage an application’s security across its lifecycle, combined with real-time analysis and reporting, as well as remediation tools.

“Every line of code that’s happening increases the risk to a business if it’s not secure,” said Contrast CEO and chairman Alan Naumann. “We’re focused on securing all that code that businesses are writing for both automation and digital transformation.”

Over the course of the last few years, the well-funded company, which raised a $65 million Series D round last year, launched numerous security tools that cover a wide range of use cases, from automated penetration testing to cloud application security and now DevOps — and this new platform is meant to tie them all together.

DevOps, the company argues, is really what necessitates a platform like this, given that developers now push more code into production than ever — and the onus of ensuring that this code is secure is now also often on that.

Image Credits: Contrast

Traditionally, Naumann argues, security services focused on the code itself and looking at traffic.

“We think at the application layer, the same principles of observability apply that have been used in the IT infrastructure space,” he said. “Specifically, we do instrumentation of the code and we weave security sensors into the code as it’s being developed and are looking for vulnerabilities and observing running code. […] Our view is: the world’s most complex systems are best when instrumented, whether it’s an airplane, a spacecraft, an IT infrastructure. We think the same is true for code. So our breakthrough is applying instrumentation to code and observing for security vulnerabilities.”

With this new platform, Contrast is aggregating information from its existing systems into a single dashboard. And while Contrast observes the code throughout its lifecycle, it also scans for vulnerabilities whenever a developers check code into the CI/CD pipeline, thanks to integrations with most of the standard tools like Jenkins. It’s worth noting that the service also scans for vulnerabilities in open-source libraries. Once deployed, Contrast’s new platform keeps an eye on the data that runs through the various APIs and systems the application connects to and scans for potential security issues there as well.

The platform currently supports all of the large cloud providers, like AWS, Azure and Google Cloud, and languages and frameworks, like Java, Python, .NET and Ruby.

Image Credits: Contrast

Oct
16
2020
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Lawmatics raises $2.5M to help lawyers market themselves

Lawmatics, a San Diego startup that’s building marketing and CRM software for lawyers, is announcing that it has raised $2.5 million in seed funding.

CEO Matt Spiegel used to practice law himself, and he told me that even though tech companies have a wide range of marketing tools to choose from, “lawyers have not been able to adopt them,” because they need a product that’s tailored to their specific needs.

That’s why Spiegel founded Lawmatics with CTO Roey Chasman. He said that a law firm’s relationship with its clients can be divided into three phases — intake (when a client is deciding whether to hire a firm); the active legal case; and after the case has been resolved. Apparently most legal software is designed to handle phase two, while Lawmatics focuses on phases one and three.

The platform includes a CRM system to manage the initial client intake process, as well as tools that can automate a lot of what Spiegel called the “blocking and tackling” of marketing, like sending birthday messages to former clients — which might sound like a minor task, but Spiegel said it’s crucial for law firms to “nurture” those relationships, because most of their business comes from referrals.

Lawmatics’ early adopters, Spiegel added, have consisted of the firms in areas where “if you need a lawyer, you go to Google and start searching ‘personal injury,’ ‘bankruptcy,’ ‘estate planning,’ all these consumer-driven law firms.” And the pandemic led to accelerated the startup’s growth, because “lawyers are at home now, their business is virtual and they need more tools.”

Spiegel’s had success selling technology to lawyers in the past, with his practice management software startup MyCase acquired by AppFolio in 2012 (AppFolio recently sold MyCase to a variety of funds for $193 million). He said that the strategies for growing both companies are “almost identical” — the products are different, but “it’s really the same segment, running the same playbook, only with additional go-to-market strategies.”

The funding was led by Eniac Ventures and Forefront Venture Partners, with participation from Revel Ventures and Bridge Venture Partners.

“In my 10 years investing I have witnessed few teams more passionate, determined, and capable of revolutionizing an industry,” said Eniac’s Tim Young in a statement. “They have not only created the best software product the legal market has seen, they have created a movement.”

 

Oct
15
2020
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Temporal raises $18.75M for its microservices orchestration platform

Temporal, a Seattle-based startup that is building an open-source, stateful microservices orchestration platform, today announced that it has raised an $18.75 million Series A round led by Sequoia Capital. Existing investors Addition Ventures and Amplify Partners also joined, together with new investor Madrona Venture Group. With this, the company has now raised a total of $25.5 million.

Founded by Maxim Fateev (CEO) and Samar Abbas (CTO), who created the open-source Cadence orchestration engine during their time at Uber, Temporal aims to make it easier for developers and operators to run microservices in production. Current users include the likes of Box and Snap.

“Before microservices, coding applications was much simpler,” Temporal’s Fateev told me. “Resources were always located in the same place — the monolith server with a single DB — which meant developers didn’t have to codify a bunch of guessing about where things were. Microservices, on the other hand, are highly distributed, which means developers need to coordinate changes across a number of servers in different physical locations.”

Those servers could go down at any time, so engineers often spend a lot of time building custom reliability code to make calls to these services. As Fateev argues, that’s table stakes and doesn’t help these developers create something that builds real business value. Temporal gives these developers access to a set of what the team calls “reliability primitives” that handle these use cases. “This means developers spend far more time writing differentiated code for their business and end up with a more reliable application than they could have built themselves,” said Fateev.

Temporal’s target use is virtually any developer who works with microservices — and wants them to be reliable. Because of this, the company’s tool — despite offering a read-only web-based user interface for administering and monitoring the system — isn’t the main focus here. The company also doesn’t have any plans to create a no-code/low-code workflow builder, Fateev tells me. However, since it is open-source, quite a few Temporal users build their own solutions on top of it.

The company itself plans to offer a cloud-based Temporal-as-a-Service offering soon. Interestingly, Fateev tells me that the team isn’t looking at offering enterprise support or licensing in the near future. “After spending a lot of time thinking it over, we decided a hosted offering was best for the open-source community and long-term growth of the business,” he said.

Unsurprisingly, the company plans to use the new funding to improve its existing tool and build out this cloud service, with plans to launch it into general availability next year. At the same time, the team plans to say true to its open-source roots and host events and provide more resources to its community.

“Temporal enables Snapchat to focus on building the business logic of a robust asynchronous API system without requiring a complex state management infrastructure,” said Steven Sun, Snap Tech Lead, Staff Software Engineer. “This has improved the efficiency of launching our services for the Snapchat community.”

Oct
15
2020
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Application security platform NeuraLegion raises $4.7 million seed led by DNX Ventures

A video call group photo of NeuraLegion's team working remotely around the world

A video call group photo of NeuraLegion’s team working remotely around the world

Application security platform NeuraLegion announced today it has raised a $4.7 million seed round led by DNX Ventures, an enterprise-focused investment firm. The funding included participation from Fusion Fund, J-Ventures and Incubate Fund. The startup also announced the launch of a new self-serve, community version that allows developers to sign up on their own for the platform and start performing scans within a few minutes.

Based in Tel Aviv, Israel, NeuraLegion also has offices in San Francisco, London and Mostar, Bosnia. It currently offers NexDAST for dynamic application security testing, and NexPLOIT to integrate application security into SDLC (software development life cycle). It was launched last year by a founding team that includes chief executive Shoham Cohen, chief technology officer Bar Hofesh, chief scientist Art Linkov and president and chief commercial officer Gadi Bashvitz.

When asked who NeuraLegion views as its closest competitors, Bashvitz said Invicti Security and WhiteHat Security. Both are known primarily for their static application security testing (SAST) solutions, which Bashvitz said complements DAST products like NeuraLegion’s.

“These are complementary solutions and in fact we have some information partnerships with some of these companies,” he said.

Where NeuraLegion differentiates from other application security solutions, however, is that it was created specifically for developers, quality assurance and DevOps workers, so even though it can also be used by security professionals, it allows scans to be run much earlier in the development process than usual while lowering costs.

Bashvitz added that NeuraLegion is now used by thousands of developers through their organizations, but it is releasing its self-serve, community product to make its solutions more accessible to developers, who can sign up on their own, run their first scans and get results within 15 minutes.

In a statement about the funding, DNX Ventures managing partner Hiro Rio Maeda said, “The DAST market has been long stalled without any innovative approaches. NeuraLegion’s next-generation platform introduces a new way of conducting robust testing in today’s modern CI/CD environment.”

Oct
14
2020
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Dataloop raises $11M Series A round for its AI data management platform

Dataloop, a Tel Aviv-based startup that specializes in helping businesses manage the entire data life cycle for their AI projects, including helping them annotate their data sets, today announced that it has now raised a total of $16 million. This includes a $5 seed round that was previously unreported, as well as an $11 million Series A round that recently closed.

The Series A round was led by Amiti Ventures, with participation from F2 Venture Capital, crowdfunding platform OurCrowd, NextLeap Ventures and SeedIL Ventures.

“Many organizations continue to struggle with moving their AI and ML projects into production as a result of data labeling limitations and a lack of real-time validation that can only be achieved with human input into the system,” said Dataloop CEO Eran Shlomo. “With this investment, we are committed, along with our partners, to overcoming these roadblocks and providing next generation data management tools that will transform the AI industry and meet the rising demand for innovation in global markets.”

Image Credits: Dataloop

For the most part, Dataloop specializes in helping businesses manage and annotate their visual data. It’s agnostic to the vertical its customers are in, but we’re talking about anything from robotics and drones to retail and autonomous driving.

The platform itself centers around the “humans in the loop” model that complements the automated systems, with the ability for humans to train and correct the model as needed. It combines the hosted annotation platform with a Python SDK and REST API for developers, as well as a serverless Functions-as-a-Service environment that runs on top of a Kubernetes cluster for automating dataflows.

Image Credits: Dataloop

The company was founded in 2017. It’ll use the new funding to grow its presence in the U.S. and European markets, something that’s pretty standard for Israeli startups, and build out its engineering team as well.

Oct
14
2020
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Vivun announces $18M Series A to keep growing pre-sales platform

Vivun’s co-founder and CEO, Matt Darrow used to run pre-sales at Zuora and he saw that pre-sales team members had a lot of insight into customers. He believed if he could capture that insight, it would turn into valuable data to be shared across the company. He launched Vivun to build upon that idea in 2018, and today the company announced an $18 million Series A.

Accel led the round with participation from existing investor Unusual Ventures. With today’s investment, Vivun has raised a total of $21 million, according to the company.

Darrow says that the company has caught the attention of investors because this is a unique product category and there has been a lot of demand for it. “It turns out that businesses of all sizes, startups and enterprises, are really craving a solution like Vivun, which is dedicated to pre-sales. It’s a big, expensive department, and there’s never been software for it before,” Darrow told TechCrunch.

He says that a couple of numbers stand out in the company’s first year in business. First of all, the startup grew annual recurring revenue (ARR) six fold (although he wouldn’t share specific numbers) and tripled the workforce growing from 10 to 30, all while doing business as an early stage startup in the midst of a pandemic.

Darrow said while the business has grown this year, he found smaller businesses in the pipeline were cutting back due to the impact of COVID’s, but larger businesses like Okta, Autodesk and Dell Secureworks have filled in nicely, and he says the product actually fits well in larger enterprise organizations.

“If we look at our value proposition and what we do, it increases exponentially with the size of the company. So the larger the team, the larger the silos are, the larger the organization is, the bigger the value of solving the problem for pre-sales becomes,” he said.

After going from a team of 10 to 30 employees in the last year, Darrow wants to double the head count to reach around 60 employees in the next year, fueled in part by the new investment dollars. As he builds the company, the founding team, which is made up of two men and two women, is focused on building a diverse and inclusive employee base.

“It is something that’s really important to us, and we’ve been working at it. Even as we went from 10 to 30, we’ve worked to pay close attention to [diversity and inclusion], and we continue to do so just as part of the culture of how we build the business,” he said.

He’s been having to build that workforce in the middle of COVID, but he says that even before the pandemic shut down offices, he and his founding partners were big on flexibility in terms of time spent in the office versus working from home. “We knew that for mental health strength and stability, that being in the office nine to five, five days a week wasn’t really a modern model that would cut it,” he said.

Even pre-COVID the company was offering two quiet periods a year to let people refresh their batteries. In the midst of COVID, he’s trying to give people Friday afternoons off to go out and exercise and relax their minds.

As the startup grows, those types of things may be harder to do, but it’s the kind of culture Darrow and his founding partners hope to continue to foster as they build the company.

Oct
13
2020
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Armory nabs $40M Series C as commercial biz on top of open-source Spinnaker project takes off

As companies continue to shift more quickly to the cloud, pushed by the pandemic, startups like Armory that work in the cloud-native space are seeing an uptick in interest. Armory is a company built to be a commercial layer on top of the open-source continuous delivery project Spinnaker. Today, it announced a $40 million Series C.

B Capital led the round, with help from new investors Lead Edge Capital and Marc Benioff along with previous investors Insight Partners, Crosslink Capital, Bain Capital Ventures, Mango Capital, Y Combinator and Javelin Venture Partners. Today’s investment brings the total raised to more than $82 million.

“Spinnaker is an open-source project that came out of Netflix and Google, and it is a very sophisticated multi-cloud and software delivery platform,” company co-founder and CEO Daniel R. Odio told TechCrunch.

Odio points out that this project has the backing of industry leaders, including the three leading public cloud infrastructure vendors Amazon, Microsoft and Google, as well as other cloud players like CloudFoundry and HashiCorp. “The fact that there is a lot of open-source community support for this project means that it is becoming the new standard for cloud-native software delivery,” he said.

In the days before the notion of continuous delivery, companies moved forward slowly, releasing large updates over months or years. As software moved to the cloud, this approach no longer made sense and companies began delivering updates more incrementally, adding features when they were ready. Adding a continuous delivery layer helped facilitate this move.

As Odio describes it, Armory extends the Spinnaker project to help implement complex use cases at large organizations, including around compliance and governance and security. It is also in the early stages of implementing a SaaS version of the solution, which should be available next year.

While he didn’t want to discuss customer numbers, he mentioned JPMorgan Chase and Autodesk as customers, along with less specific allusions to “a Fortune Five technology company, a Fortune 20 Bank, a Fortune 50 retailer and a Fortune 100 technology company.”

The company currently has 75 employees, but Odio says business has been booming and he plans to double the team in the next year. As he does, he says that he is deeply committed to diversity and inclusion.

“There’s actually a really big difference between diversity and inclusion, and there’s a great Vern? Myers quote that diversity is being asked to the party and inclusion is being asked to dance, and so it’s actually important for us not only to focus on diversity, but also focus on inclusion because that’s how we win. By having a heterogeneous company, we will outperform a homogeneous company,” he said.

While the company has moved to remote work during COVID, Odio says they intend to remain that way, even after the current crisis is over. “Now obviously COVID been a real challenge for the world, including us. We’ve gone to a fully remote-first model, and we are going to stay remote-first even after COVID. And it’s really important for us to be taking care of our people, so there’s a lot of human empathy here,” he said.

But at the same time, he sees COVID opening up businesses to move to the cloud and that represents an opportunity for his business, one that he will focus on with new capital at his disposal. “In terms of the business opportunity, we exist to help power the transformation that these enterprises are undergoing right now, and there’s a lot of urgency for us to execute on our vision and mission because there is a lot of demand for this right now,” he said.

Oct
08
2020
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Headroom, which uses AI to supercharge videoconferencing, raises $5M

Videoconferencing has become a cornerstone of how many of us work these days — so much so that one leading service, Zoom, has graduated into verb status because of how much it’s getting used.

But does that mean videoconferencing works as well as it should? Today, a new startup called Headroom is coming out of stealth, tapping into a battery of AI tools — computer vision, natural language processing and more — on the belief that the answer to that question is a clear — no bad Wi-Fi interruption here — “no.”

Headroom not only hosts videoconferences, but then provides transcripts, summaries with highlights, gesture recognition, optimised video quality and more, and today it’s announcing that it has raised a seed round of $5 million as it gears up to launch its freemium service into the world.

You can sign up to the waitlist to pilot it, and get other updates here.

The funding is coming from Anna Patterson of Gradient Ventures (Google’s AI venture fund); Evan Nisselson of LDV Capital (a specialist VC backing companies building visual technologies); Yahoo founder Jerry Yang, now of AME Cloud Ventures; Ash Patel of Morado Ventures; Anthony Goldbloom, the co-founder and CEO of Kaggle.com; and Serge Belongie, Cornell Tech associate dean and professor of Computer Vision and Machine Learning.

It’s an interesting group of backers, but that might be because the founders themselves have a pretty illustrious background with years of experience using some of the most cutting-edge visual technologies to build other consumer and enterprise services.

Julian Green — a British transplant — was most recently at Google, where he ran the company’s computer vision products, including the Cloud Vision API that was launched under his watch. He came to Google by way of its acquisition of his previous startup Jetpac, which used deep learning and other AI tools to analyze photos to make travel recommendations. In a previous life, he was one of the co-founders of Houzz, another kind of platform that hinges on visual interactivity.

Russian-born Andrew Rabinovich, meanwhile, spent the last five years at Magic Leap, where he was the head of AI, and before that, the director of deep learning and the head of engineering. Before that, he too was at Google, as a software engineer specializing in computer vision and machine learning.

You might think that leaving their jobs to build an improved videoconferencing service was an opportunistic move, given the huge surge of use that the medium has had this year. Green, however, tells me that they came up with the idea and started building it at the end of 2019, when the term “COVID-19” didn’t even exist.

“But it certainly has made this a more interesting area,” he quipped, adding that it did make raising money significantly easier, too. (The round closed in July, he said.)

Given that Magic Leap had long been in limbo — AR and VR have proven to be incredibly tough to build businesses around, especially in the short to medium-term, even for a startup with hundreds of millions of dollars in VC backing — and could have probably used some more interesting ideas to pivot to; and that Google is Google, with everything tech having an endpoint in Mountain View, it’s also curious that the pair decided to strike out on their own to build Headroom rather than pitch building the tech at their respective previous employers.

Green said the reasons were two-fold. The first has to do with the efficiency of building something when you are small. “I enjoy moving at startup speed,” he said.

And the second has to do with the challenges of building things on legacy platforms versus fresh, from the ground up.

“Google can do anything it wants,” he replied when I asked why he didn’t think of bringing these ideas to the team working on Meet (or Hangouts if you’re a non-business user). “But to run real-time AI on video conferencing, you need to build for that from the start. We started with that assumption,” he said.

All the same, the reasons why Headroom are interesting are also likely going to be the ones that will pose big challenges for it. The new ubiquity (and our present lives working at home) might make us more open to using video calling, but for better or worse, we’re all also now pretty used to what we already use. And for many companies, they’ve now paid up as premium users to one service or another, so they may be reluctant to try out new and less-tested platforms.

But as we’ve seen in tech so many times, sometimes it pays to be a late mover, and the early movers are not always the winners.

The first iteration of Headroom will include features that will automatically take transcripts of the whole conversation, with the ability to use the video replay to edit the transcript if something has gone awry; offer a summary of the key points that are made during the call; and identify gestures to help shift the conversation.

And Green tells me that they are already also working on features that will be added into future iterations. When the videoconference uses supplementary presentation materials, those can also be processed by the engine for highlights and transcription too.

And another feature will optimize the pixels that you see for much better video quality, which should come in especially handy when you or the person/people you are talking to are on poor connections.

“You can understand where and what the pixels are in a video conference and send the right ones,” he explained. “Most of what you see of me and my background is not changing, so those don’t need to be sent all the time.”

All of this taps into some of the more interesting aspects of sophisticated computer vision and natural language algorithms. Creating a summary, for example, relies on technology that is able to suss out not just what you are saying, but what are the most important parts of what you or someone else is saying.

And if you’ve ever been on a videocall and found it hard to make it clear you’ve wanted to say something, without straight-out interrupting the speaker, you’ll understand why gestures might be very useful.

But they can also come in handy if a speaker wants to know if he or she is losing the attention of the audience: The same tech that Headroom is using to detect gestures for people keen to speak up can also be used to detect when they are getting bored or annoyed and pass that information on to the person doing the talking.

“It’s about helping with EQ,” he said, with what I’m sure was a little bit of his tongue in his cheek, but then again we were on a Google Meet, and I may have misread that.

And that brings us to why Headroom is tapping into an interesting opportunity. At their best, when they work, tools like these not only supercharge videoconferences, but they have the potential to solve some of the problems you may have come up against in face-to-face meetings, too. Building software that actually might be better than the “real thing” is one way of making sure that it can have staying power beyond the demands of our current circumstances (which hopefully won’t be permanent circumstances).

Oct
08
2020
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Grid AI raises $18.6M Series A to help AI researchers and engineers bring their models to production

Grid AI, a startup founded by the inventor of the popular open-source PyTorch Lightning project, William Falcon, that aims to help machine learning engineers work more efficiently, today announced that it has raised an $18.6 million Series A funding round, which closed earlier this summer. The round was led by Index Ventures, with participation from Bain Capital Ventures and firstminute. 

Falcon co-founded the company with Luis Capelo, who was previously the head of machine learning at Glossier. Unsurprisingly, the idea here is to take PyTorch Lightning, which launched about a year ago, and turn that into the core of Grid’s service. The main idea behind Lightning is to decouple the data science from the engineering.

The time argues that a few years ago, when data scientists tried to get started with deep learning, they didn’t always have the right expertise and it was hard for them to get everything right.

“Now the industry has an unhealthy aversion to deep learning because of this,” Falcon noted. “Lightning and Grid embed all those tricks into the workflow so you no longer need to be a PhD in AI nor [have] the resources of the major AI companies to get these things to work. This makes the opportunity cost of putting a simple model against a sophisticated neural network a few hours’ worth of effort instead of the months it used to take. When you use Lightning and Grid it’s hard to make mistakes. It’s like if you take a bad photo with your phone but we are the phone and make that photo look super professional AND teach you how to get there on your own.”

As Falcon noted, Grid is meant to help data scientists and other ML professionals “scale to match the workloads required for enterprise use cases.” Lightning itself can get them partially there, but Grid is meant to provide all of the services its users need to scale up their models to solve real-world problems.

What exactly that looks like isn’t quite clear yet, though. “Imagine you can find any GitHub repository out there. You get a local copy on your laptop and without making any code changes you spin up 400 GPUs on AWS — all from your laptop using either a web app or command-line-interface. That’s the Lightning “magic” applied to training and building models at scale,” Falcon said. “It is what we are already known for and has proven to be such a successful paradigm shift that all the other frameworks like Keras or TensorFlow, and companies have taken notice and have started to modify what they do to try to match what we do.”

The service is now in private beta.

With this new funding, Grid, which currently has 25 employees, plans to expand its team and strengthen its corporate offering via both Grid AI and through the open-source project. Falcon tells me that he aims to build a diverse team, not in the least because he himself is an immigrant, born in Venezuela, and a U.S. military veteran.

“I have first-hand knowledge of the extent that unethical AI can have,” he said. “As a result, we have approached hiring our current 25 employees across many backgrounds and experiences. We might be the first AI company that is not all the same Silicon Valley prototype tech-bro.”

“Lightning’s open-source traction piqued my interest when I first learned about it a year ago,” Index Ventures’ Sarah Cannon told me. “So intrigued in fact I remember rushing into a closet in Helsinki while at a conference to have the privacy needed to hear exactly what Will and Luis had built. I promptly called my colleague Bryan Offutt who met Will and Luis in SF and was impressed by the ‘elegance’ of their code. We swiftly decided to participate in their seed round, days later. We feel very privileged to be part of Grid’s journey. After investing in seed, we spent a significant amount with the team, and the more time we spent with them the more conviction we developed. Less than a year later and pre-launch, we knew we wanted to lead their Series A.”

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