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Patronus AI gets off to a magical start as LLM governance tools gain momentum

TechBrunchBy TechBrunchMay 22, 20242 Mins Read
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These days, every company wants to ensure that its large-scale language models comply with the rules, laws, or regulatory requirements that it considers important. The need is even more acute if you are in a regulated industry. Perhaps that's why Patronus AI is finding early success in the market.

The company, which helps customers ensure their models are compliant in many ways, announced a $17 million Series A on Wednesday, just eight months after announcing a $3 million seed round. .

“What excited our investors was that we are the clear leader in this space, and it's a very large market, and it's also a very fast-growing market,” CEO and Co-Founder Anand Kanappan told TechCrunch. Additionally, Patronus was able to jump in early when he recognized that LLM governance tools were needed for companies to remain compliant.

They believe in the potential of a growing market that is only just beginning: “Since launching, we've worked with a range of portfolio companies, AI companies and mid-stage companies, resulting in clients making hundreds of thousands of requests through our platform,” he said.

The company's main focus is a piece called Patronus Evaluators. “These are essentially API calls that can be implemented in one line of code and allow us to scalably measure the performance of LLMs and LLM systems across many different aspects in a very high quality and reliable manner.” he says Kannappan.

This includes potential for hallucinations, copyright risks, safety risks, and even company-specific features such as detecting business-sensitive information and brand voice and style that companies care about from both a regulatory and reputational perspective. included.

As we wrote during the seed announcement:

“The company was in the right place at the right time, building a security and analytics framework in the form of a managed service for testing language models at scale and identifying potential problem areas, especially if the model We are identifying possible hallucinations that may constitute an answer.

The company has doubled from six employees when it raised seed funding last year, and expects to double again this year.

The $17 million investment was led by Notable Capital with participation from Lightspeed Venture Partners, Factorial Capital, Datadog, and industry angels.



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