Beta launch

AI systems fail in ways you can't see.

DriftShield helps AI teams understand what failed, why it failed and where to focus first.

Understand how your AI system actually fails

DriftShield reconstructs failed workflow runs so teams can see how failures emerged across prompts, tools, models and workflows.

Automatically trace the sequence of events behind a failed AI run.

Identify recurring failure structures across workflows and environments.

analysis_report.json

01"step": "constraint_validation"

02"status": "failed_divergence"

03"reason": "Policy Divergence detected at node 4"

04"confidence": 0.982

DRIFTSHIELD_INSIGHTThe agent acknowledged the budget constraint in step 2 but discarded it during vendor selection in step 4.

As workflows become more complex, similar failure structures begin appearing across very different systems.

Our growing taxonomy continues to evolve as new failure structures emerge across production AI workflows.

Open source

DriftShield OSS starts with one failed run at a time.

Analyse individual failed runs locally, reconstruct execution paths, and classify failures into emerging categories.

Self-serve platform for shared failure analysis within AI engineering teams.

Organisational failure intelligence for teams operating complex and high stakes AI systems.