Source-grounded legal review

Contract analysis inside the client’s infrastructure.

Lawyers needed to find clauses, compare terms and inspect potential risks across heterogeneous legal documents.

A pipeline for OCR, document structure, clause retrieval and risk extraction, with source references and exportable review results.

• Scalable Ingestion Pipeline. M&A data rooms contain hundreds to thousands of documents in varied formats. We needed a robust pipeline to handle OCR, metadata extraction, and content normalization quickly.
• Clause-Level Understanding. The assistant must identify key legal clauses, extract obligations, and detect crucial risks or anomalies in documents.
• Cited, contextual answers. The system was designed to ground findings in retrieved legal text and expose source references for review.
• Custom Legal Taxonomies and Schema. NDAs, MSAs, board resolutions, and commercial leases all carry different review requirements. The system needed flexible, domain-aware tagging and search across contract types.
• Enterprise-Grade Security and Deployment. Legal documents contain confidential and privileged information. Our platform had to support full encryption, fine-grained access controls, audit logging, and VPC or on-prem deployment options.

• Documents are uploaded or synced via secure integrations. We use OCR, PDF parsers, and layout-aware NLP to extract structural metadata (dates, parties, signatures, etc.).
• Clause-level embeddings are stored in Milvus, allowing the LLM to retrieve highly relevant passages for analysis and summarization.
• A custom RAG layer ensures summaries and Q&A responses are grounded in retrieved text. Prompts are domain-tuned for legal accuracy.
• Multilayer LLM-based architecture identifies and categorizes key clauses (e.g., indemnity, termination, governing law) and detects possible risks.
• AI Assistant is equipped with tools for exploring summaries, clicking on citations, tagging documents, and exporting structured reports.
• The solution is deployed within the client’s infrastructure without external model APIs, keeping document processing within the agreed deployment boundary.
• The system operates without reliance on external APIs or third-party platforms, providing full data sovereignty and making it easier to meet strict regulatory, privacy, and client confidentiality requirements.

Outcome

A pilot that connects legal-review findings with the underlying contract clauses.

The pilot combined document ingestion, clause retrieval and source-linked findings. Lawyers remained responsible for interpreting the material.