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AI Grounded in
Regulatory Reality

The Intelligence Layer
Behind the Platform

The Safety Graph transforms fragmented regulatory and quality data into a connected system of products, complaints, recalls, clinical outcomes, suppliers, and risk events.

Instead of analyzing isolated documents, the platform understands how signals relate across systems and time.

  • 50M+ Safety relationships mapped

  • Multi-source signal validation

  • Continuous risk learning

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Why Traditional AI Falls Short

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No Context

Generic AI predicts text patterns without
understanding regulatory relationships.

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Weak Traceability

Outputs often cannot be linked back to
evidence or source systems.

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Hallucinated Results

Models may generate confident but
unsupported conclusions.

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Disconnected Signals

Traditional systems fail to connect complaints,
recalls, and operational events together.

How the
Safety Graph Works

Data Ingestion

Ingests data from regulatory, clinical, and operational systems.

Step 01

Signal Validation

Maps relationships between products, events, suppliers, complaints, and risks.

Step 02

Relationship Mapping

Validates signals across multiple evidence sources.

Step 03

AI Insights

Generates explainable AI insights with traceable reasoning paths.

Step 04

What Powers the Graph

FDA MAUDE, recalls, safety notices, and
global vigilance databases.

FDA MAUDE, recalls, safety notices, and global vigilance databases.

FDA MAUDE, recalls, safety notices, and global vigilance databases.

FDA MAUDE, recalls, safety notices, and global vigilance databases.

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From Fragmented Data to
Connected Intelligence

Before

Reactive &
Disconnected Systems

Traditional safety operations rely on siloed tools, manual reviews, and fragmented data sources that slow investigations and limit visibility.

  • Siloed safety systems
  • Manual investigations
  • Slow signal detection
  • Inconsistent analysis
Connected Intelligence
After

Connected &
Explainable Intelligence

The Safety Graph unifies regulatory, clinical, and operational signals into one continuously learning intelligence layer.

  • Unified intelligence platform
  • Faster investigations
  • Connected risk signals
  • Explainable AI outputs