Public engineering proof / Python · FastAPI
Reliable Data Intake Pipeline
Turns inconsistent provider data into validated, canonical records with explicit outcomes and provenance.
Problem
External data arrives malformed, incomplete, duplicated, or conflicting. Passing it directly into an application makes downstream state difficult to trust.
System
A FastAPI ingestion service uses provider adapters, typed canonical models, deterministic identity resolution, conservative deduplication, and transactional persistence. Records are accepted, routed for review, rejected, or identified as duplicates.
Architecture
- Provider adapters
- Typed validation
- Canonicalization
- Identity and conflict checks
- Accept / review / reject
- Transactional persistence
Demonstrated capabilities
- • Provider adapters and typed API boundaries
- • Validation, normalization, and conservative deduplication
- • Idempotent requests, conflict detection, and provenance
- • Explicit review, rejection, and duplicate outcomes
Commercial applications
- • Ingestion APIs
- • Enrichment and ETL workflows
- • Provider integrations
- • Review queues and canonical data models
Related VantaBlade Product Systems
Where this pattern appears in integrated product evidence.
These relationships indicate a shared engineering pattern. This repository does not reproduce the complete product or imply code identity.