AI Legal Documents Manager

Overview

A mid-size law practice serving corporate and commercial clients needed a modern way to manage a rapidly growing library of contracts and case files. They partnered with Laalain to build a secure AI-powered document manager that could summarize, classify, and surface risks across thousands of legal documents—without compromising confidentiality.

The Challenge

The firm's operations were slowed by fragmentation:

• Contracts lived across email threads, local drives, and shared folders.

• Document search depended on file names, not content.

• Associates manually summarized agreements for senior review.

• Clause-level risk checks were inconsistent and time-consuming.

• No clear audit trail for document changes.

They needed a centralized platform that could accelerate reviews while remaining compliant with strict legal data policies.

Goals

1. Create a single, secure system for storing and organizing legal documents.

2. Enable semantic search across all matters and clients.

3. Automate summaries and clause extraction to reduce manual work.

4. Highlight risks and missing clauses using AI.

5. Keep full version history and user-level auditability.

Our Approach

We ran a discovery sprint to map attorney workflows and identify high-impact automation points. From there:

• Designed a minimal, attorney-friendly UI with fast navigation.

• Implemented a retrieval-based AI pipeline (RAG) to prevent hallucination and keep outputs grounded in source documents.

• Built a permission system aligned with matter-based access.

• Added compliance-grade logging and encryption at rest and in transit.

The Solution

A cloud-based legal document manager with AI-enhanced intelligence at every step.

Key Features

• Smart Ingestion + OCR: Upload PDFs, DOCX, or scans; auto-convert to searchable text.

• Auto-Classification: Documents sorted by type, client, and matter with confidence scores.

• AI Summaries: One-click executive summaries and structured briefs.

• Clause Extraction: Pulls critical terms (termination, indemnity, liability, jurisdiction).

• Risk Flags: Highlights deviations from firm standards and missing sections.

• Semantic Search: Natural-language queries like "find NDAs missing termination dates."

• Version Control + Audit Trails: Track every edit, review, and access event.

Tech Stack

Next.js, Node.js, PostgreSQL, Redis, AWS (S3/ECS), OCR pipeline, RAG/LLM orchestration, secure logging.

Results

• 72% reduction in document review time.

• 3–5x faster document retrieval.

• 30% fewer missed clause issues in internal audits.

• Adopted by the majority of the firm within 6 weeks of launch.

What's Next

Future iterations include multilingual contract support and firm-specific clause template learning.