Raw Signal Ingestion
Disconnected systems, fragmented safety data, and growing regulatory complexity make it difficult for teams to detect risks early and maintain clear visibility across post-market surveillance workflows.
Built for Modern
Healthcare Ecosystems
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Domain Models
Domain-trained AI models analyze healthcare and regulatory data to identify risks, detect patterns, assess severity, and understand regulatory relevance with contextual accuracy.
Safety Graph
A grounded safety graph connects devices, risks, regulations, and historical outcomes to provide contextual understanding and reduce hallucinations.
Reasoning Agents
Reasoning agents investigate signals, assess regulatory impact, and distinguish real safety events from noise with explainable decision-making.
Human-in-the-Loop
Human oversight keeps experts in control through validation, approvals, and audit-ready workflows.