Legal Confidentiality.
Cryptographically Enforced.
Legal documents carry the most sensitive trade secrets, financial terms, and strategic roadmaps of your company. We architected LegalGPT with zero compromise on privacy.
Zero Model Training
We never use customer contracts, proprietary clauses, or confidential disclosures to train or fine-tune public or proprietary AI models.
In-Memory Parsing & Ephemeral Processing
Uploaded documents are streamed and parsed into volatile memory. Once your analysis report and session complete, raw documents are scrubbed.
Sovereign Vector Isolation
Contract embeddings generated for the RAG assistant are partitioned with strict session-level UUIDs in Supabase pgvector with row-level security.
Stateless AI Inference
Invocations to LLM inference providers (Google Gemini & Groq) enforce zero-day retention agreements ensuring prompts are never cached or logged.
Technical Architecture & Data Lifecycle
1. Transport Encryption: All client communications utilize TLS 1.3 with Perfect Forward Secrecy. Uploaded PDFs or raw text never pass over unencrypted connections.
2. Multi-Agent Pipeline Isolation: Our LangGraph pipeline processes documents through modular state transitions. When Tavily web search runs to check governing law statutes, only abstracted clause concepts (not your identifying client names or proprietary business terms) are queried.
3. Vector Partitioning: Clause chunk embeddings stored in Supabase pgvector use HNSW indexing isolated strictly by contract UUID. Cross-tenant retrieval is architecturally impossible.
4. Right to Erasure: You retain complete ownership. You can purge your contract session at any time, which cryptographically destroys vector embeddings and session state instantly.