SchemaPilot
Safe agentic data migration
Live on Google Cloud
LEGACY DATA → VERIFIED TARGET
Move messy enterprise data
without silent mistakes.
SchemaPilot combines deterministic safety checks with specialist Gemini agents. It automates what is safe, escalates what is uncertain, and proves that every source row is accounted for.
Zero silent data lossHuman approval for ambiguityAuthoritative master data
LIVE ORCHESTRATION
Migration pipeline
0/7 stages
•
Ingest
Read and normalize source
Pending
•
Profile
Schema, duplicates and dates
Pending
•
Map
Agentic semantic mapping
Pending
•
Risk
Deterministic safety gate
Pending
•
Human review
Approval only when required
Pending
•
Transform
Create safe target records
Pending
•
Verify
Reconcile every source row
Pending
◎
AI reasons. Policy decides.Semantic agents never bypass deterministic risk gates or reconciliation.
CSV MIGRATION
Run the sample or upload your own employee CSV.
CSV
employees.csv
5 synthetic employee records · bundled sample
✓
This sample intentionally contains the kinds of issues that make legacy migrations risky:
!
Ambiguous date01/04/1990 has two valid interpretations
!
Invalid dateOne DOB cannot be safely normalized
!
Legacy organizationDepartment names require semantic mapping
!
Controlled rejectionUnsafe records are rejected, never silently fixed
TargetNormalized employee schema
AI specialistsOrganization + Date
SafetyRisk gate + HITL + reconciliation
WHY TRUST THIS MIGRATION?
Safety is enforced outside the model.
Gemini handles semantic interpretation, while deterministic checks control what may be written and verify that every source row has a final outcome.
✓Authoritative organization IDs only
✓Ambiguous values require approval
✓Invalid records are never silently corrected
✓Every source row must be reconciled
ADK EVAL
4/4
Holdout safety cases passedCurrent organization-mapping baseline · deterministic judge · score 1.00