ContractGuard

About the Project

Contracts are everywhere in business, but understanding them is often slow, complicated, and expensive. Important details such as termination conditions, payment obligations, deadlines, liability clauses, and unusual terms can easily be missed during manual review.

We built ContractGuard, an AI-powered contract analysis platform that helps users understand contracts before they sign or approve them.

What inspired us

We wanted to solve a simple problem: make contract review faster and easier without requiring users to read dozens of pages line by line.

Instead of building another chatbot that simply answers questions about a document, we designed ContractGuard as an AI agent that actively investigates the contract. It reads the document, extracts important information, identifies potential risks, explains why they matter, and points the user back to the relevant clause.

How it works

The user uploads a contract, and ContractGuard processes it through an agentic workflow:

Upload → Document Processing → Information Extraction → Risk Analysis → Verification → Report

The system extracts key information such as:

• Parties involved
• Payment terms
• Important dates
• Obligations
• Renewal conditions
• Termination clauses
• Liability and indemnity provisions
• Other potentially important clauses

The AI then analyzes the contract for potentially unfavorable, unusual, ambiguous, or missing terms.

Each finding is presented with a risk level, explanation, and supporting contract context, allowing the user to understand not only what was detected, but why it matters.

Users can also ask questions about their contract through an AI-powered interface and receive answers grounded in the uploaded document.

What we learned

Building ContractGuard taught us that creating a useful AI product involves much more than connecting an LLM to a prompt.

We had to think carefully about document extraction, context management, reliable AI responses, structured outputs, agent workflows, and user experience. We also learned how important it is to make AI decisions transparent by showing the evidence behind each finding rather than presenting unexplained conclusions.

Challenges

One of the biggest challenges was handling contracts as real documents rather than simple text. Contracts can contain long sections, complex language, and information spread across different clauses.

Another challenge was designing the AI workflow so that it could analyze the document systematically instead of producing a generic summary.

We addressed this by structuring the analysis into multiple stages and grounding findings in the original contract content.

Why ContractGuard matters

ContractGuard is designed to save users time and help them focus their attention on the parts of a contract that deserve closer review.

Our goal is not to replace lawyers or professional legal advice. Instead, ContractGuard acts as an AI first-pass review assistant, helping users understand documents and identify areas that may require further attention.

What's next

We plan to expand ContractGuard with features such as:

• Contract comparison and version tracking
• Clause recommendations
• Negotiation assistance
• Automated deadline and obligation tracking
• Team collaboration
• Integration with document management platforms
• More advanced contract-specific AI agents

ContractGuard turns a long contract into an understandable, actionable review.

Built With

• agentic
• ai
• artificial
• css
• fastapi
• intelligence
• llm
• next.js
• openai
• pdf
• postgresql
• processing
• python
• rag
• react
• tailwind