HerculesAI (formerly Zero Systems) has been working on skilled services automation since 2017, originally specializing in the legal industry. As a part of this work, the corporate has been developing large language models for several years, long before the thought entered the general public consciousness. So it was in the best place at the best time when ChatGPT got here on the scene in late 2022 and suddenly everyone was talking about LLMs.
Today, the corporate announced a $26 million Series B investment to further construct on its recent momentum.
Alex Babin, CEO and co-founder of the corporate, says that they had been working on small models with half a billion to 2 billion parameters since around 2020, running them on edge devices for compliance reasons, but before the arrival of ChatGPT, nobody paid much attention to this aspect of their solution.
“It was possibly eight or nine months before ChatGPT and I remember talking to our customers and explaining to the CIOs what an LLM was – and no one cared,” Babin told TechCrunch. Of course, that quickly modified in November of that 12 months and suddenly everyone was involved in the concept. That shift has contributed to the corporate's rapid growth during the last 12 months.
Today, the corporate has several models that perform three primary functions: intelligent data extraction, data transformation and data verification. The first is fairly standard and involves extracting data from documents. The second part mechanically creates a algorithm and structures around that data, however the third part, verification, is particularly necessary, he says.
“It's really the holy grail when you possibly can compare extracted information after which convert it to the source of truth, whether that's regulations, policies, contracts, laws or the rest,” Babin said. This ensures that any issues that conflict with the source materials are mechanically flagged to employees.
These three areas have also enabled the startup to construct a multi-agent system on top of those services that helps automate all of those activities. “These multi-agent systems could be applied to high-value, continuous processes or workflows that require (automated) decision making,” he said.
All of this is especially necessary for its core customers within the regulated industry. Today, this includes not only legal services, but additionally insurance and financial services.
Their AI strategy appears to be working, as the corporate reported four-fold growth within the last 12 months. Their clients include 30% of the highest 100 law firms within the US. In addition, they’ve quite a lot of other Fortune 500 clients, including Mercer, Standard & Poor's, and State Farm.
The company currently employs around 75 people, but despite the more money, Babin plans to remain lean and invest more in improving internal processes than in hiring latest employees. “I don't see any reason why we’d like to rent more people. In fact, we’ll invest more in our internal processes and automation. We may have to eat our own pet food and use our own products to change into more scalable,” he said.
Today’s funding was led by Streamlined Ventures with participation from Proof VC, Thomson Reuters Ventures, Alumni Ventures and various industry investors.
