Patronus AI unveils security platform for LLMs with $3m boost

Patronus

Patronus AI, a newcomer in the world of enterprise AI solutions, has announced its official launch and raised fresh financing. 

This innovative company has stepped onto the scene with its first automated evaluation and security platform, specifically tailored for the safe deployment of LLMs.

The company’s launch was fuelled by a $3m seed funding round. Notable investors throwing their weight behind Patronus AI included Lightspeed Venture Partners, Factorial Capital, Replit CEO Amjad Masad, Gokul Rajaram, as well as several other top-tier executives and board members from Fortune 500 companies.

At its core, Patronus AI’s platform is engineered to tackle the challenges that come with LLMs. Using its proprietary AI, the platform facilitates enterprise development teams in evaluating model performance, constructing adversarial test cases, and benchmarking various models. The essence of Patronus AI’s mission is to replace the time-consuming, manual model evaluation methods that have become commonplace in enterprises, paving the way for a more efficient and scalable solution.

The aim of the raised capital is to advance the development and scalability of their unique platform. With these funds, the enterprise intends to bolster its ability to help organisations deploy LLMs with minimal risks associated with model failures and misaligned outputs.

Behind Patronus AI’s vision are its founders – machine learning specialists Anand Kannappan and Rebecca Qian. Their combined experience from roles at Meta AI and Meta Reality Labs inspired them to create a solution to the massive challenge of LLM evaluation faced by enterprises.

Patronus AI CEO and co-founder Anand Kannappan commented on the industry’s urgent need for their solution. He said, “Every company is looking for ways to use LLMs today, yet they are concerned that unexpected model behaviour, incorrect outputs and hallucinations will put their business and customers at risk. Whether off-the-shelf, open-source or custom, models today remain inadequately vetted and tested in real-world scenarios. And until now, the process of evaluating LLMs has been extremely inefficient and unscalable, producing unreliable results.”

Patronus AI’s platform is uniquely positioned to address these concerns, automating scoring, test generation, and benchmarking processes for LLMs, ensuring they are ready for real-world deployment.

Furthermore, the company has previously attracted investments, but the recent $3m seed funding round is a significant step forward.

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