Oil Project Regulatory Compliance Assistant with AI SDK
Kuwait's $381m upstream oil approval process requires continuous cross-checking of environmental impact assessments (EIAs) against Kuwait EPA regulations. Build a web-based conversational assistant using Vercel AI SDK (TypeScript) with streaming tool calling to analyze submission packages. Provide zero-latency streaming audit results with 95% rule match precision.
What you are building
Develop a TypeScript compliance agent using Vercel AI SDK to stream real-time environmental permit verification checks.
How work is evaluated
Evaluates streaming output response validity and accuracy of regulatory breach identification.
Datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
non_compliant_item_flagged
Correctly flags flaring rate violation
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
compliance_rule_precision
Precision in identifying genuine regulatory violations • target: 0.95 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Learning goals
Build a TypeScript backend leveraging Vercel AI SDK core functions (`generateText`, `streamText`)
Define typed tools using Zod schemas for environmental parameter verification
Implement client-side UI streaming using `@ai-sdk/react` hooks
Validate oil field environmental impact submittals against KOC and KEPA thresholds
Resources
20 environmental impact submittal packages for Kuwait onshore oilfield developments.
Challenge setup
Evaluates streaming output response validity and accuracy of regulatory breach identification.
Challenge input
JSON object with proposed water reinjection volume and flaring limits
AI SDK
Provides standard streaming and component bindings for web platforms.
Evaluated output
JSON containing status, non_compliant_items array, and recommended remedy
- Correctly flags flaring rate violation
- Precision in identifying genuine regulatory violations • target: 0.95 • range: 0-1
- Benchmark: RegCheckBench
- Compliance Rule Precision target: 0.95
- 1 public reference case
- JavaScript execution harness
- javascript sandbox (unavailable on Versalist)
Shows the first task, up to three tools, and up to three evidence items.
View technical recipe
Configured tools
- Vercel AI SDK · Required
- Synthflow · Optional
- AutoKeras · Optional
- Vercel AI SDK · Required
Evaluation contract
- non_compliant_item_flagged · Weight 1
- compliance_rule_precision · Weight 1
Metrics
- compliance_rule_precision · Target 0.95
Benchmarks
- RegCheckBench
- security
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON object with proposed water reinjection volume and flaring limits
Output: JSON containing status, non_compliant_items array, and recommended remedy
Execution harness: JavaScript
Evaluation tools
- AI SDK · TypeScript AI Framework
Recipe freeze marker
No recipe freeze time is recorded.