## In 2024, 79% of FDA Warning Letters
cited data integrity failures

85% of safety and efficacy issues in Complete Response Letters
are never disclosed by companies.

With AI making more decisions, the audit trail matters more than ever.

79% stat: FY2024 FDA Form 483 analysis - most common deficiency is lack of audit trails. 85% stat: 2015 BMJ cross-sectional study on CRL disclosure gaps. Example: Feb 2025 Warning Letter to Exer Labs for AI diagnostic without QMS (inspection Oct 2024).

## Why this keeps happening

- Your data warehouse stores the current answer. Sources disagree.
- When a study is retracted, which decisions did it affect?
- AI recommended X. Can you reconstruct why?

"Black box" is a documented rejection reason. Traditional databases overwrite history.

These aren't hypotheticals. The retraction question is what kills you in audits. "Can you reconstruct why" is the question every CMO dreads. 510(k) submissions have grown to 1,000+ pages - FDA explicitly rejects "black box" AI.

# StemeDB

A knowledge graph that stores claims, not facts.

Append-only. Auditable. Built for regulated industries.

Quick intro - don't linger here. The next slide explains the approach. "Steme" from episteme (Greek for knowledge).

## Every claim has a source

StemeDB stores assertions with provenance, not overwritten facts.

- When sources disagree, you see the disagreement
- When a source is retracted, you know what's affected in seconds
- History is preserved. Nothing gets silently overwritten.

This is the key insight. Version control for knowledge. Don't say "Git for Truth" - just describe the behavior.

## What this enables

#### Conflict Visibility

See when sources disagree. Confidence scores show you how much.

#### Cascade Invalidation

Retract a source. See every downstream decision affected.

#### Complete Audit Trail

Every query logged with provenance. Export for regulators.

Time-travel queries: "What did we believe on January 1st?"

Keep this brief. The demo will prove these claims. Time-travel is the differentiator from every data warehouse.

## Here's what it looks like

FDA guidance now requires audit trails for all AI-enabled devices. This is what compliance looks like.

Query:

subject: semaglutide:gastroparesis_risk
predicate: risk_level

FDA labels say low incidence. Patient reports say otherwise.
Watch how StemeDB surfaces that conflict.

"FDA has authorized over 1,200 AI-enabled devices. All require audit trails." "I'm going to run this exact query live. Watch what happens when sources disagree." Then switch to dashboard tab. Query should already be typed in.

## Questions

What you saw:

- Conflict visibility — FDA vs patient reports, with confidence scores
- Cascade invalidation — Source retraction, instant impact assessment
- Audit trail — Every query logged, export-ready
- Time-travel — Point-in-time queries
- Trust & Safety — Quarantine queue, circuit breakers

Be ready for: - "What's the latency?" → 340ms on 2.3M assertions - "SOC 2?" → In progress, not yet certified - "How do I get my data out?" → Standard export formats - "Who else uses this?" → Be honest about stage