This company provides the graph safety suite, a GenAI SaaS platform unifying patient safety workflows including intake, case processing, signal detection, and regulatory compliance. Powered by the graph x intelligence fabric, it uses domain-tuned AI to automate processes and ensure audit-ready, explainable outputs for life sciences organizations. The platform delivers productivity gains, cost reduction, and faster regulatory reporting through an integrated, AI-native architecture.
Funding
$3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Life‑science organizations manage safety data across disparate legacy systems, spreadsheets, and external channels, leading to fragmented case records, manual reconciliation, delayed signal detection, and heightened regulatory risk.
Solution
Graph Safety Suite delivers a GenAI‑powered SaaS platform that consolidates source data, intake, case processing, signal detection, reporting, and compliance into a single, context‑aware ecosystem. Built on the Graph X knowledge‑graph engine, the platform ingests multi‑channel safety inputs, applies domain‑tuned biomedical models, and generates audit‑ready, explainable intelligence. Real‑time AI agents orchestrate workflows, surface high‑confidence signals, and auto‑code adverse events to industry ontologies, enabling safety teams to act faster while maintaining full regulatory traceability.
Target Audience
Primary customers are pharmaceutical, biotech, medical‑device, and cosmetics manufacturers, as well as CROs and BPOs that operate pharmacovigilance, materiovigilance, or cosmetovigilance programs and require compliant, AI‑enhanced safety operations.
Features
- Multi‑channel ingestion pipeline that normalizes data from literature, email, social media, clinical trials, and partner systems into a governed intake layer.
- Ontology‑driven knowledge graph aligning MedDRA, WHODrug, SNOMED CT, and E2B R3 to create semantic relationships across drugs, patients, and events.
- Context‑aware AI models for automatic MedDRA coding, duplicate detection, and confidence scoring, reducing manual effort and variability.
- Nucleus safety neural network provides continuous, event‑driven intelligence, routing cases in real time based on SLA urgency and reviewer availability.
- Agentic workflow orchestration with visual composer APIs that enable low‑code integration into existing safety databases and ERP systems.
- Built‑in compliance framework (GVP, 21 CFR Part 11, HIPAA) with immutable audit trails, source verification, and explainable rationale for every inference.
- Scalable cloud‑native architecture delivering >99 % faster regulatory reporting and up to 70 % productivity gains through automation.
- Role‑based user interfaces and persona‑driven dashboards that surface actionable insights for safety officers, clinicians, and regulatory analysts.