ZeroDrift raises $10 million to protect AI models from themselves

As enterprises troubleshoot their AI systems, governance has emerged as a key challenge. Some are taking a dual approach: One model to handle incoming queries, and another to keep the first one from getting into trouble.

That’s the premise of ZeroDrift, a new AI compliance service that on Tuesday said it had raised $10 million in a seed funding round that saw investments from a16z Speedrun, Reign Ventures, PitchDrive Ventures, and U&I Ventures, among others. The company deals entirely with the second part of the system, sitting between AI models and end users to flag and replace any messages that might present a compliance problem.

It might seem strange to build an AI tool to correct other AI systems’ mistakes, but ZeroDrift says its system has a few architectural advantages over the models it will be correcting. The system is triggered by conventional programs that deterministically apply known compliance standards like SOC 2 or GDPR, and the LLM only comes into play once a message has been flagged, rewriting a compliant version of the same message.

“We’re able to identify, deterministically, what are all the regulated areas, what’s the violation that’s being broken, and then we have LLMs that can do the rewrites,” CEO Kumesh Aroomoogan says.

Critically, the company says its entire system can be run with lower latency and more reliability than a conventional LLM. This is what ZeroDrift touts as its primary advantage over big labs like OpenAI and Anthropic, which are often already present in the underlying system.

The most obvious use case is for AI chatbots, which are already deployed in front of consumers where there can be serious consequences for rogue answers. But Aroomoogan sees a much larger total addressable market, potentially spanning AI-generated messages that are generated only within automated systems that humans will never see. So far, it’s a relatively small market, but it’s one that will grow as AI proliferates.

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