Build a Fund Prospectus Compliance Audit Engine with LangChain and Windsurf
Develop a compliance verification agent using LangChain and Windsurf IDE workflows to audit asset management fund prospectuses against MAS regulatory directives. Extract investment mandate rules and detect clause contradictions in real time.
What you are building
Utilize LangChain LangGraph agent workflows developed with Windsurf developer assistance to parse, verify, and highlight non-compliant fund prospectus terms.
How work is evaluated
Evaluates detection accuracy of non-compliant clauses in simulated fund prospectus texts.
Datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
violation_detected
Verifies that excessive concentration is flagged as non_compliant
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
citation_precision
Precision of extracted text citations • 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
Construct stateful compliance checking graphs using LangChain's LangGraph framework
Optimize local prompt engineering and workflow iterations using Windsurf AI engineering tools
Extract structured investment limit rules from unstructured regulatory PDF texts
Generate automated compliance violation matrix reports with precise citations
Resources
Dataset containing 20 fund prospectus excerpts with synthetic regulatory violations.
Challenge setup
Evaluates detection accuracy of non-compliant clauses in simulated fund prospectus texts.
Challenge input
JSON object with prospectus_text and rule_set_version
LangChain
Provides LangGraph for building stateful compliance workflows.
Windsurf
Accelerates agent development and prompt iteration.
Evaluated output
JSON object with compliance_status, violations array, and source_clause_citations
- Verifies that excessive concentration is flagged as non_compliant
- Precision of extracted text citations • target: 0.95 • range: 0-1
- Benchmark: LegalBench Regulatory Compliance
- Citation Precision target: 0.95
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
Shows the first task, up to three tools, and up to three evidence items.
View technical recipe
Configured tools
- LangChain · Required
- Langchain · Optional
- Windsurf · Optional
- Windsurf · Optional
- LangChain · Required
- Langchain · Optional
Evaluation contract
- violation_detected · Weight 1
- citation_precision · Weight 1
Metrics
- citation_precision · Target 0.95
Benchmarks
- LegalBench Regulatory Compliance
- general
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON object with prospectus_text and rule_set_version
Output: JSON object with compliance_status, violations array, and source_clause_citations
Execution harness: Python
Evaluation tools
- LangChain · Agent Chains & Graphs
- Windsurf · AI Engineering Environment
Recipe freeze marker
No recipe freeze time is recorded.