Build an OpenAI Agents SDK Aadhaar Identity Verification Triage System
High-volume citizen onboarding services need rapid verification of OCR-extracted identity documents against Aadhaar metadata formatting standard constraints. Build an OpenAI Agents SDK identity verification agent that validates document tokens and flags fraudulent attempts with 98% accuracy.
What you are building
The core problem, expected build, and operating context for this challenge.
Construct an identity verification agent using OpenAI Agents SDK to validate Aadhaar metadata schema structures and anomaly indicators.
How work is evaluated
Evaluates checksum validity verification and PII masking completeness.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
pii_masking_check
Confirms identity numbers are properly masked
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
verification_accuracy
Accuracy of identity document authenticity decisions • target: 0.98 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Implement OpenAI Agents SDK agents with custom tool functions for Verhoeff checksum validation
Detect structural anomalies in OCR extracted identity payloads
Enforce privacy protection masking on citizen identity numbers
Generate encrypted KYC audit payloads compliant with UIDAI standards
Reference links and supporting material
Synthetic identity document OCR text Extractions and metadata records.
How this agent runs
Evaluates checksum validity verification and PII masking completeness.
Challenge input
JSON identity OCR extraction object
OpenAI Agents SDK
Agent loop execution and function calling
Evaluated output
JSON audit result with checksum_valid and masked_id
- Confirms identity numbers are properly masked
- Accuracy of identity document authenticity decisions • target: 0.98 • range: 0-1
- Benchmark: Identity Document Parsing Benchmark
- Verification Accuracy target: 0.98
- 1 public reference case
- Python execution harness
- Python sandbox
View technical recipe
Configured tools
- OpenAI · Required
- RAI · Optional
- LangWatch · Optional
Evaluation contract
- pii_masking_check · Weight 1
- verification_accuracy · Weight 1
Recipe state
This is a preview. The configuration can change before the evaluation recipe is locked.