Graph AI Raises $13.3M Series A to Scale AI-Native Pharmacovigilance Platform
核心洞察
Graph AI (搜索) closed a $13.3 million Series A led by Insight Partners (搜索) with participation from existing investor Bessemer Venture Partners (搜索) to scale its AI-native patient safety platform.
In live deployments, Graph Safety (搜索) cut adverse-event case processing turnaround from over three hours to under 10 minutes, a reduction exceeding 90%, and lowered operating costs by up to 66%.
The platform pairs AI with deterministic controls, validation layers and end-to-end audit trails, and was designed with reference to FDA, EU AI Act and CIOMS expectations for AI in pharmacovigilance.
Graph AI (搜索), developer of the Graph Safety (搜索) AI-native patient safety platform, has raised a $13.3 million Series A financing led by Insight Partners (搜索), with participation from existing investor Bessemer Venture Partners (搜索). The company said the funding will accelerate its expansion across the US and Europe, scaling a platform built to absorb the operational load of pharmacovigilance so that safety experts can concentrate on analysis and decision-making.
Founded in 2024, Graph AI (搜索) was created to address the operational inefficiencies and regulatory complexity facing modern pharmacovigilance and patient safety teams. According to the company, pharma teams currently devote much of their effort to manual processing and operational workflows — work that intelligent software can increasingly take on.
Measured Reductions in Case Processing Time and Cost
The company reported that in live deployments, Graph Safety (搜索) has reduced case processing turnaround time from more than three hours to under 10 minutes, a reduction of more than 90%, while lowering operating costs by up to 66%. These figures were cited by Graph AI (搜索) as outcomes from live enterprise deployments rather than from a controlled trial.
"Pharmacovigilance has traditionally scaled against rising case volumes by adding people and processes around legacy systems. We believe intelligence can change that," said Raghav Parvataraju, CEO of Graph AI (搜索). "Graph Safety (搜索) gives safety experts an intelligent system that takes on operational complexity, while keeping traceability, accountability, and human oversight at the centre. We are not replacing human judgment—we are building technology that allows experts to apply it where it matters most."
Regulatory Alignment and Traceability by Design
Graph Safety (搜索) 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 was designed with reference to applicable regulatory requirements and evolving expectations for AI in medicines development and patient safety, including the FDA's risk-based credibility assessment framework for AI used to support regulatory decision-making, the EU Artificial Intelligence Act, and the CIOMS Working Group XIV report on Artificial Intelligence in Pharmacovigilance.
Module Rollout and Investor Rationale
Since raising its seed round in October 2025, Graph AI (搜索) has brought two modules to market: /intake, which captures and triages incoming adverse-event reports (搜索) across every channel, and /nucleus, an intelligent safety database that automates case processing end to end. A third module, /report, for automated aggregate reporting, is launching this September. The company has onboarded pharmaceutical and biotech customers across North America and other markets and secured design partnerships for modules ahead, including /signal, which surfaces emerging safety signals and patterns across cases.
Investors framed the financing around the gap between what AI can now deliver and the fragmented tooling that safety organizations have historically relied on. "Pharma companies must strive to get patient safety exactly right, and almost none of them want to be in the business of integrating disparate tools to do it. Meanwhile the software and service providers they rely on haven't kept up with what AI can now do to drive accuracy and value for their pharma customers," said Richard Matus, Principal at Insight Partners (搜索). "We believe that's a perfect problem for an AI team that lives inside this industry with complete focus, and why we're proud to back Raghav and the Graph AI (搜索) team as they scale."
"Since leading Graph AI (搜索)'s seed round, we've watched Raghav and the team turn a bold thesis into live enterprise deployments with measurable outcomes. Patient safety should run an intelligent, integrated platform - not fragmented tools and manual handoffs. We are thrilled to deepen our partnership alongside Insight Partners (搜索) as Graph scales globally. This is what AI disrupting a services-heavy industry looks like," said Nithin Kaimal, Partner and India COO at Bessemer Venture Partners (搜索).