Graph Safety combines AI with deterministic controls, validation layers and end-to-end audit trails designed for regulated pharmacovigilance environments. Output and source data remain traceable, supporting customer validation, inspection readiness and human oversight. The platform has been designed with reference to applicable regulatory requirements and evolving expectations for AI in medicines development and patient safety.
In live deployments, Graph Safety has reduced case processing turnaround time from more than three hours to under 10 minutes, a reduction of more than 90 per cent, and lowered operating costs by up to 66 per cent.
Since raising its seed round in October 2025, Graph AI has brought two modules to market: Intake, which captures and triages incoming adverse-event reports across every channel, and Nucleus, an intelligent safety database that automates case processing end to end.
A third module, called Report, for automated aggregate reporting, is also launching this month. The company has onboarded pharmaceutical and biotech customers across North America and other markets, and secured design partnerships for the modules ahead, including Signal, which surfaces emerging safety signals and patterns across cases.
"Pharmacovigilance has traditionally scaled against rising case volumes by adding people and processes around legacy systems. We believe intelligence can change that. Graph Safety gives safety experts an intelligent system that takes on operational complexity, while keeping traceability, accountability, and human oversight at the center. We are not replacing human judgment — we are building technology that allows experts to apply it where it matters most," said Raghav Parvataraju, the chief executive officer of the firm.
