Signed Owl

Inspiration

Justice delayed is justice denied. A recent study showed that roughly one-third of backlog court cases have been pending for over an year. Key cause? The agreement trap.

Lawyers are often buried under a ton of paperwork which is hard to understand and navigate, but not anymore. Signed Owl helps you 10x your legal capabilities by supercharging your workflow with AI.

What it does

It solves the problem of Agreement trap in 3 stages:

1. Categorization: Using the Navigator API, you can extract fields that would have otherwise taken a ton of time, and sort and search documents by them.
2. Edits: For redlining and contract negotations, you can use AI agents which use the document data along with metadata from Navigator API to edit changes.
3. Insights: Use of AI agents to extract clauses and obligations, flag deviations and prepare a well researched report using web searched, along with the citations.
4. AI Chat: Upload documents, which are stored as vectors and then quried. Storing them as vectors and then sematically searching for data helps answers complex questions.
5. Reports: Provides Statistical insights into AI extracted fields using Navigator API.
6. Kanban and Calendar: Helps manage the workload effectively.

How we built it

I build it using Langgraph - for the AI agents, FastAPI for the backend and React for the Front end, combined with MongoDb's Atlas for vector storage.

Built With

• atlas
• fastapi
• lanngraph
• mongodb
• openai
• react