Mar
17
2021
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OctoML raises $28M Series B for its machine learning acceleration platform

OctoML, a Seattle-based startup that offers a machine learning acceleration platform built on top of the open-source Apache TVM compiler framework project, today announced that it has raised a $28 million Series B funding round led by Addition. Previous investors Madrona Venture Group and Amplify Partners also participated in this round, which brings the company’s total funding to $47 million. The company last raised in April 2020, when it announced its $15 million Series A round led by Amplify

The promise of OctoML, which was founded by the team that also created TVM, is that developers can bring their models to its platform and the service will automatically optimize that model’s performance for any given cloud or edge device.

As Brazil-born OctoML co-founder and CEO Luis Ceze told me, since raising its Series A round, the company started onboarding some early adopters to its “Octomizer” SaaS platform.

Image Credits: OctoML

“It’s still in early access, but we are we have close to 1,000 early access sign-ups on the waitlist,” Ceze said. “That was a pretty strong signal for us to end up taking this [funding]. The Series B was pre-emptive. We were planning on starting to raise money right about now. We had barely started spending our Series A money — we still had a lot of that left. But since we saw this growth and we had more paying customers than we anticipated, there were a lot of signals like, ‘hey, now we can accelerate the go-to-market machinery, build a customer success team and continue expanding the engineering team to build new features.’ ”

Ceze tells me that the team also saw strong growth signals in the overall community around the TVM project (with about 1,000 people attending its virtual conference last year). As for its customer base (and companies on its waitlist), Ceze says it represents a wide range of verticals that range from defense contractors to financial services and life science companies, automotive firms and startups in a variety of fields.

Recently, OctoML also launched support for the Apple M1 chip — and saw very good performance from that.

The company has also formed partnerships with industry heavyweights like Microsoft (which is also a customer), Qualcomm and AMD to build out the open-source components and optimize its service for an even wider range of models (and larger ones, too).

On the engineering side, Ceze tells me that the team is looking at not just optimizing and tuning models but also the training process. Training ML models can quickly become costly and any service that can speed up that process leads to direct savings for its users — which in turn makes OctoML an easier sell. The plan here, Ceze tells me, is to offer an end-to-end solution where people can optimize their ML training and the resulting models and then push their models out to their preferred platform. Right now, its users still have to take the artifact that the Octomizer creates and deploy that themselves, but deployment support is on OctoML’s roadmap.

“When we first met Luis and the OctoML team, we knew they were poised to transform the way ML teams deploy their machine learning models,” said Lee Fixel, founder of Addition. “They have the vision, the talent and the technology to drive ML transformation across every major enterprise. They launched Octomizer six months ago and it’s already becoming the go-to solution developers and data scientists use to maximize ML model performance. We look forward to supporting the company’s continued growth.”


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Oct
05
2020
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Strike Graph raises $3.9M to help automate security audits

Compliance automation isn’t exactly the most exciting topic, but security audits are big business and companies that aim to get a SOC 2, ISO 207001 or FedRamp certification can often spend six figures to get through the process with the help of an auditing service. Seattle-based Strike Graph, which is launching today and announcing a $3.9 million seed funding round, wants to automate as much of this process as possible.

The company’s funding round was led by Madrona Venture Group, with participation from Amplify.LA, Revolution’s Rise of the Rest Seed Fund and Green D Ventures.

Strike Graph co-founder and CEO Justin Beals tells me that the idea for the company came to him during his time as CTO at machine learning startup Koru (which had a bit of an odd exit last year). To get enterprise adoption for that service, the company had to get a SOC 2 security certification. “It was a real challenge, especially for a small company. In talking to my colleagues, I just recognized how much of a challenge it was across the board. And so when it was time for the next startup, I was just really curious,” he told me.

Image Credits: Strike Graph

Together with his co-founder Brian Bero, he incubated the idea at Madrona Venture Labs, where he spent some time as Entrepreneur in Residence after Koru.

Beals argues that today’s process tends to be slow, inefficient and expensive. The idea behind Strike Graph, unsurprisingly, is to remove as many of these inefficiencies as is currently possible. The company itself, it is worth noting, doesn’t provide the actual audit service. Businesses will still need to hire an auditing service for that. But Beals also argues that the bulk of what companies are paying for today is pre-audit preparation.

“We do all that preparation work and preparing you and then, after your first audit, you have to go and renew every year. So there’s an important maintenance of that information.”

Image Credits: Strike Graph

When customers come to Strike Graph, they fill out a risk assessment. The company takes that and can then provide them with controls for how to improve their security posture — both to pass the audit and to secure their data. Beals also noted that soon, Strike Graph will be able to help businesses automate the collection of evidence for the audit (say your encryption settings) and can pull that in regularly. Certifications like SOC 2, after all, require companies to have ongoing security practices in place and get re-audited every 12 months. Automated evidence collection will launch in early 2021, once the team has built out the first set of its integrations to collect that data.

That’s also where the company, which mostly targets mid-size businesses, plans to spend a lot of its new funding. In addition, the company plans to focus on its marketing efforts, mostly around content marketing and educating its potential customers.

“Every company, big or small, that sells a software solution must address a broad set of compliance requirements in regards to security and privacy. Obtaining the certifications can be a burdensome, opaque and expensive process. Strike Graph is applying intelligent technology to this problem — they help the company identify the appropriate risks, enable the audit to run smoothly and then automate the compliance and testing going forward,” said Hope Cochran, managing director at Madrona Venture Group. “These audits were a necessary pain when I was a CFO, and Strike Graph’s elegant solution brings together teams across the company to move the business forward faster.”

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