AI Startup Lemma Raises $2.3M in Pre-Seed Round

The round included Matrix, Y Combinator, Liquid 2 Ventures, Vermilion Cliffs Ventures, Irregular Expressions, Cervin Ventures, Comma Capital, Position Ventures and Eight Capital, along with angel investors and technology operators from companies including OpenAI, xAI, Meta and DoorDash.

Funding Snapshot

About Lemma

Founded by Jerry Zhang and Cole Gawin, Lemma develops monitoring and observability technology designed specifically for AI agents operating in production environments.

The platform analyzes live agent activity to determine whether agents are successfully completing their intended tasks, rather than simply checking whether an application has crashed or generated an error.

Lemma currently monitors more than 1 million agent traces per day. Its platform can identify problems, trace them to potential causes, suggest fixes and push those fixes back into the codebase.

• Core offerings include:
• Automated remediation
• AI agent monitoring
• Production observability
• Silent failure detection
• Root-cause analysis

“Cole and I started Lemma because we experienced the pain of building AI agents firsthand,” Zhang said. “We kept running into the same problem: agents would appear to work, but the results weren’t reliable enough in production.”

“We wanted to build the tools we wished we had: something that helps teams catch issues earlier, learn from production data, and continuously improve agent performance in the real world,” he added.

“We’re in the very early innings of improving agent quality, and I’m excited to see the Lemma founders tackle it with a focus on silent failures and automated resolution,” Sukhar said.

Ashley Smith, founder of Vermilion Cliffs Ventures, said existing monitoring systems often focus on identifying technical breakdowns after they occur, while Lemma is focused on determining whether an AI agent actually completed its intended job.

“Existing tools tell you what broke after the fact. Lemma tells you whether the agent actually did its job, catching silent failures before users churn,” Smith said.

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