Orchestrate Startup IPO Readiness Audits using CrewAI Agents
Tech startups preparing for public listing in India must fulfill complex SEBI disclosure requirements across financial balance sheets and cap tables. Orchestrate a team of specialized CrewAI agents to cross-verify compliance documents, statutory audit filings, and valuation reports. Achieve a 95% detection rate on regulatory discrepancies.
What you are building
The core problem, expected build, and operating context for this challenge.
Deploy a multi-agent team using CrewAI to automate financial audit, SEBI compliance, and cap-table risk checking for IPO-bound startups.
How work is evaluated
Evaluates CrewAI team report output against known compliance violations in synthetic DRHP documents.
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.
critical_finding_test
Checks if critical related party non-disclosure is flagged
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
discrepancy_detection_rate
Percentage of deliberate filing discrepancies successfully identified • target: 0.95 • 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
Define collaborative CrewAI roles for Financial Auditor, Legal Counsel, and SEBI Compliance Analyst
Build sequential and hierarchical multi-agent execution tasks
Parse multi-year DRHP drafts and financial statement footnotes
Produce consolidated IPO readiness risk matrices with regulatory references
Reference links and supporting material
Synthetic startup DRHP draft excerpts, cap-table structures, and statutory financial audits.
How this agent runs
Evaluates CrewAI team report output against known compliance violations in synthetic DRHP documents.
Challenge input
JSON object containing financial summary and regulatory criteria
CrewAI
Provides collaborative multi-agent delegation and task management primitives.
Evaluated output
JSON object with compliance status, audit findings, and risk score
- Checks if critical related party non-disclosure is flagged
- Percentage of deliberate filing discrepancies successfully identified • target: 0.95 • range: 0-1
- Benchmark: SEBI Compliance Audit Benchmark
- Discrepancy Detection Rate target: 95%
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
View technical recipe
Configured tools
- CrewAI · Required
- crewAI · Optional
- Zed · Optional
Evaluation contract
- critical_finding_test · Weight 1
- discrepancy_detection_rate · Weight 1
Recipe state
This is a preview. The configuration can change before the evaluation recipe is locked.