LegalEase AI is a comprehensive, AI-powered platform designed to demystify complex legal documents by translating them into plain English using Google's cutting-edge Gemini 2.0 model. The platform goes beyond static document analysis by offering a built-in Chrome extension for real-time Google Meet transcription, a RAG-enhanced interactive AI chat for contextual querying, and multilingual voice support. It effectively makes enterprise-grade legal analysis and risk assessment accessible to everyone.
Upload contracts and agreements for AI analysis, automatic risk assessment, and plain English translation.
A custom Chrome extension captures Google Meet audio and streams it via WebSockets for live legal topic analysis.
Query your documents using Retrieval-Augmented Generation (RAG). The AI remembers uploaded documents and their semantic content.
Find highly specific legal clauses across your entire document library using advanced vector similarity search.
Ask questions naturally using Speech-to-Text and listen to AI responses via Text-to-Speech, optimized for complex legal terminology.
A Next.js web dashboard paired with a custom Manifest V3 Chrome Extension that injects into Google Meet for live audio capture.
Socket.IO manages low-latency WebSocket connections, streaming transcription data instantly from the extension to the user's dashboard.
Document text is chunked, vectorized using Google's text-embedding-004, and indexed in Vertex AI. User queries trigger a hybrid search to feed into Gemini 2.0 for generation.
Firebase Firestore stores user profiles, document metadata, and chat histories, operating in tandem with the Vertex AI vector index.
Robust backend endpoints (/api/analyze, /api/rag-query, /api/vector-search) orchestrate the flow between the UI, the vector database, and the Gemini APIs.
Introduce a feature to generate standard legal agreements based on conversational prompts and dynamically retrieve approved clauses.
Enable teams to simultaneously annotate, review, and interact with the AI on the same document in real-time.
Connect the RAG pipeline to public legal databases to cross-reference clauses with active laws and provide citation checking.
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