Contract Review AI Agent
An AI-powered contract analysis system that extracts obligations, detects risky clauses, identifies missing protections, and generates structured risk reports for commercial agreements.
01. The Problem
Manual contract review is time-consuming, error-prone, and difficult to scale. Small teams and startups often lack structured tools to systematically detect risky clauses, missing protections, or one-sided obligations in commercial agreements.
02. The Logic
Extract text from uploaded contract documents (PDF/DOCX) and normalize structure.
Segment contract into individual clauses using rule-based parsing.
Run multi-pass AI extraction to identify obligations, liability caps, termination rights, indemnities, and governing law.
Compare extracted clauses against a predefined standard template to detect missing or high-risk provisions.
Apply a hybrid rule-based risk scoring engine to compute overall risk level.
Generate a structured JSON risk report with explanations and confidence score.
Log outputs for human review and continuous improvement.
03. The Stack
04. The Solution
Implementation Result
Built a multi-stage AI agent architecture combining deterministic clause parsing, template comparison, and controlled LLM reasoning to produce auditable, structured contract risk assessments rather than free-form summaries.
Key Outcomes
- 01.Reduced preliminary contract review time by over 60% in internal testing.
- 02.Achieved consistent structured JSON outputs with schema validation.
- 03.Enabled clause-level risk detection instead of document-level general summaries.
Reflection
- LLMs must be constrained with strict schemas to prevent hallucinated clauses.
- Risk scoring should be hybrid (rules + AI explanation) rather than purely generative.
- Breaking analysis into multiple deterministic passes improves reliability.
- Human-in-the-loop review is essential for legal-domain applications.