Graph

Graph Safety Suite is an AI-native software platform developed by Graph AI for patient safety and pharmacovigilance in the life sciences industry. The platform is designed to serve pharmaceutical, biotech, cosmetics, and medical device organisations, combining safety monitoring, regulatory compliance, and AI-driven automation into a single connected ecosystem. Graph AI received a $3 million seed round led by Bessemer Venture Partners to scale its AI platforms globally.

The graph safety suite is described as the first GenAI SaaS platform for unified patient safety. It is powered by graphx, Graph AI's proprietary domain-tuned AI foundation, which connects diverse data sources, builds a living knowledge graph, and orchestrates AI reasoning through retrieval, orchestration, and workflow layers. The platform unifies source intake, case processing, aggregate reporting, signal detection, risk management, and regulatory compliance into one integrated system.

Products and Modules

• /intake — Handles multi-channel data ingestion with decoded intelligence across all incoming safety data sources.
• /nucleus — Described as a safety neural network, serving as the core processing and intelligence layer of the platform.
• /assure — Focused on real-time, evidence-driven risk management; scheduled to launch in H2 2026.
• /signal — Provides root causality analysis and clinical context for signal detection; scheduled to launch in H2 2026.
• /report — Delivers AI-drafted, graph-validated regulatory reports; scheduled to launch in H2 2026.
• /comply — Addresses compliance requirements beyond standard regulatory frameworks; scheduled to launch in H2 2026.

Core Platform: graphx

• graphx is Graph AI's proprietary enterprise GenAI platform that unifies fragmented enterprise data and workflows into a context-aware intelligence layer.
• It is built with domain understanding at its core, connecting diverse data sources and building a living knowledge graph.
• The architecture includes retrieval, orchestration, and workflow layers that transform raw data into actionable intelligence.
• graphx is designed to operate securely and compliantly at scale across regulated industries.
• It enables domain-specific AI that adapts and learns, and is described as accelerating time to value while maintaining transparency.
• graphx also powers plug-and-play GenAI pipelines with built-in domain intelligence for pharma, biotech, cosmetics, and medical devices beyond the safety suite.

Key Capabilities

• Unified, AI-native architecture replacing fragmented legacy systems.
• Collaborative functional system with automation across safety workflows.
• Agentic and generative AI intelligence embedded throughout the platform.
• API-first and integration-ready ecosystem.
• Systematic signal management assisted by generative AI.
• Proactive risk management capabilities.
• Dynamic knowledge graph for connected data intelligence.
• Built-in compliance and audit readiness with explainable AI.
• User-centric workflow design and collaborative platform environment.
• Insight-driven decision support across safety functions.

Reported Performance Metrics

• Productivity gains of approximately 70% through intelligent automation.
• Cost reduction of 55% or more.
• Efficiency gains exceeding 80%.
• Regulatory reporting accuracy above 99%.
• Industry-leading AI accuracy and completeness for safety data processing.
• Audit-ready outputs with compliance embedded throughout the platform.

Compliance and Trust

• The platform is built to meet regulatory requirements across the life sciences sector.
• AI outputs are designed to be explainable and traceable, supporting regulatory confidence.
• Complete, traceable data is maintained for every safety process.
• The system is positioned as audit-ready by design, with compliance embedded natively rather than added as a layer.

Graph AI positions the graph safety suite as an alternative to legacy pharmacovigilance systems, offering a fully integrated, AI-native approach to patient safety that covers the full spectrum of safety functions from data intake through to regulatory reporting and risk management.