Graph AI Raises $13.3 Million Series A Funding Led by Insight Partners
Graph Safety has reduced pharmacovigilance case-processing turnaround times from 3+ hours to under 10 minutes, while reporting up to 66% lower operating costs and supporting safety monitoring for 300+ drugs.
Graph AI, an AI-native startup focused on pharmacovigilance and patient safety, has raised $13.3 million in Series A funding led by Insight Partners, with participation from existing investor Bessemer Venture Partners.
The company plans to use the new capital to expand across the US and Europe and scale its Graph Safety platform, which is designed to automate and connect workflows used by pharmaceutical and biotechnology companies for drug safety monitoring and reporting.
Founded in 2024 by Raghav Parvataraju, Vijay Ponukumati, Mohan Konyala and Ashutosh Bordekar, Graph AI develops Graph Safety, which it describes as an AI-native operating system for patient safety. The company is based in Pleasanton, California, with operations in India as well.
The latest round comes less than a year after Graph AI raised $3 million in seed funding from Bessemer Venture Partners in October 2025. The seed funding was used to accelerate product development, expand the engineering team and drive adoption of its pharmacovigilance platform. With the latest round, Graph AI has raised about $16.3 million in disclosed funding.
Graph AI is targeting a longstanding operational challenge in the pharmaceutical industry. Pharmacovigilance teams are responsible for collecting, assessing and reporting adverse events and other safety information throughout the lifecycle of a medicine, from clinical development through post-market use. These workflows have traditionally involved fragmented systems, manual processing and large service teams.
Graph Safety is designed to bring these activities into a connected platform. The company says its architecture combines AI with deterministic controls, validation layers and end-to-end audit trails so that case information and the sources behind decisions remain traceable. The platform is also designed to retain human oversight, with safety professionals remaining responsible for analysis, review and decisions that require clinical or scientific judgement.
In live deployments, Graph AI said Graph Safety has reduced case-processing turnaround times from more than three hours to under 10 minutes and lowered operating costs by as much as 66%. Bessemer has separately reported more than 90% efficiency gains among enterprise customers using the platform. These figures are company and investor-reported metrics rather than independently audited results.
Graph AI currently has three product modules available. The first, /intake, captures, classifies and routes incoming adverse-event reports across multiple sources. /nucleus functions as the company’s safety database and is designed to structure, validate and connect the evidence required to process individual safety cases. /report is designed to generate regulator-ready outputs, including E2B(R3) generation, multi-region regulatory alignment and gateway submission support.
Graph AI says its platform is now being used by enterprise customers to monitor the safety of more than 300 drugs. The company has also reported more than 90% efficiency gains and up to 66% cost savings compared with existing workflows.
The company has also secured design partnerships for products under development and is expanding its customer base across pharmaceutical and biotechnology markets. Its current expansion plans are focused on the US and Europe, where it is targeting pharmaceutical companies and contract research organisations with its patient safety platform.