Graph AI: Leveraging AI for Patient Safety
Graph AI, a startup focused on patient safety powered by AI, has successfully secured $13.3 million in its Series A funding round. This investment round was led by Insight Partners and included contributions from existing investor Bessemer Venture Partners. This latest funding follows closely on the heels of the startup’s seed round, which took place in October 2025.
Funding Utilisation
Graph AI intends to use the newly acquired funds to boost its reach in both the US and European markets while also accelerating its product development efforts.
About Graph AI
Established in 2024, Graph AI has developed Graph Safety, an AI-driven platform designed to automate workflows for pharmacovigilance and patient safety teams within the pharmaceutical and biotechnology industries. The platform merges AI technology with deterministic controls, validation layers, and comprehensive audit trails, allowing pharmaceutical firms to effectively manage safety operations while ensuring traceability and maintaining human oversight.
Operational Efficiency
Graph Safety automates the handling of adverse event reports as well as safety cases. The company reports that, through its live deployments, the turnaround times for case processing have been reduced from over three hours to under ten minutes. This marks a significant decrease of more than 90%. Moreover, the platform has claimed to reduce operating costs by as much as 66%.
Product Modules
The startup currently has two operational modules. The Intake module is designed to capture and triage adverse event reports, whereas Nucleus serves as an intelligent safety database that automates case processing. Additionally, a third module called Report, which focuses on automated aggregate reporting, is anticipated to launch this month.
Client Engagement
Graph AI has successfully integrated pharmaceutical and biotech clients across North America and other regions. The startup is also collaborating with its customers on forthcoming products, including Signal, which aims to detect emerging safety signals and patterns within cases.