Graph AI raises $13.3M Series A to automate drug safety work
What's the deal? Graph AIDealroom has a profile for this one. Try Dealroom → has raised a $13.3 million Series A led by Insight Partners, with existing investor Bessemer Venture Partners participating. The Pleasanton, California startup builds Graph Safety, an AI-native platform for pharmacovigilance — the drug-safety monitoring that pharma teams are required to run.
What's the endgame? Founded in 2024, Graph AI wants software to absorb the manual processing that dominates safety teams' work. Its platform combines AI with deterministic controls, validation layers, and end-to-end audit trails built for regulated environments. The money will fund expansion across the US and Europe.
Why now? Since its seed round in October 2025, Graph AI has shipped two modules: /intake, which triages incoming adverse-event reports, and /nucleus, a safety database that automates case processing. A third module, /report, launches this September.
The numbers: In live deployments, Graph Safety cut case processing time from more than three hours to under 10 minutes — a reduction of more than 90% — and lowered operating costs by up to 66%. The company has onboarded pharma and biotech customers across North America and other markets.
What could go wrong? The platform operates in a heavily regulated field. Graph AI says it built to reference the FDA's risk-based credibility framework for AI, the EU Artificial Intelligence Act, and the CIOMS Working Group XIV report on AI in pharmacovigilance — but shifting regulatory expectations for AI in medicines remain a live risk.
The signal: "This is what AI disrupting a services-heavy industry looks like," said Nithin Kaimal, partner at Bessemer Venture Partners. Graph AI's bet is that intelligent systems can replace the "add people and processes" model that pharmacovigilance has long relied on. "We are not replacing human judgment," said chief executive officer Raghav Parvataraju. "We are building technology that allows experts to apply it where it matters most."
Image credit: Graph AI
