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HerculesAI has been working on large-scale language models long before they became popular.

TechBrunchBy TechBrunchJuly 11, 20243 Mins Read
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HerculesAI (formerly Zero Systems) has been working on automating professional services since 2017, initially focusing on the legal industry. As part of that, the company has been building large language models for years, long before the idea became public knowledge. So when ChatGPT came along in late 2022 and suddenly everyone was talking about LLMs, the company was in the right place at the right time.

The company today announced a $26 million Series B investment to build on its recent momentum.

The company's CEO and co-founder, Alex Babin, said the company had been working since around 2020 on developing smaller models with 500 million to 2 billion parameters, running them on edge devices for compliance purposes, but that before ChatGPT came along, no one had paid much attention to that side of the solution.

“I think about eight or nine months before ChatGPT came along, I was talking to clients and explaining to CIOs what an LLM was, and nobody was interested,” Babin told TechCrunch. By November of that year, of course, things quickly changed and suddenly everyone was interested in the concept. This shift helped fuel the business's rapid growth over the past year.

Today, the company has multiple models that perform three main functions: intelligent data extraction, data transformation and data validation. The first function is standard and involves grabbing data from documents. The second part automatically builds a set of rules and structures around that data, but the third part, validation, is particularly important, he says.

“That's really the holy grail, being able to compare that information that you extract and turn it into a source of truth — be it a regulation, a policy, a contract, a law — is what Babin said. This would allow any issues that contradict the source material to be automatically flagged to employees.”

These three buckets allowed the startup to build multi-agent systems on top of these services to automate all these activities. “These multi-agent systems can be applied to high-value, continuous processes and workflows.” [automated] “It's a decision,” he said.

All of this is especially important for core clients in regulated industries, which today include not only law but also insurance and financial services.

Its AI strategy appears to be paying off: the company reported fourfold growth last year and counts 30% of the top 100 U.S. law firms as clients, along with many Fortune 500 companies, including Mercer, Standard & Poor's, and State Farm.

The company currently has about 75 employees, but Babin said that despite the additional funding, the company plans to stay lean and invest in improving its internal processes rather than adding more employees. “I don't see why we need to hire more people. Rather, we're going to invest more in our internal processes and automation. We need to use our own product and be more scalable ourselves,” he said.

Today's round was led by Streamlined Ventures, with participation from Proof VC, Thomson Reuters Ventures, Alumni Ventures and angel investors across multiple industries.



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