Fixing Slow, Inconsistent Contract Review with AI Document Intelligence

The Problem

Legal and finance teams were burdened by slow, manual contract review processes that relied heavily on individual interpretation and inconsistent workflows. Reviewing diverse document types, identifying obligations, spotting risky clauses, and capturing key dates took excessive time and often resulted in missed obligations or delayed deal cycles. Without a standardised first-pass output, teams struggled to scale their contract throughput or maintain consistent risk assessment across matters.

The Solution

One of our digital squads built an AI document-intelligence pipeline capable of analysing diverse contract formats, extracting obligations, assessing risks, and generating actionable insights. The system combined robust OCR for scanned or low-quality documents with native parsing for PDFs and Word files. A clause-extraction and scoring engine—supported by specialised prompts and RAG over a precedent library—identified obligations, key dates, risk indicators, and recommended edits.

The platform produced executive summaries, negotiation playbooks, suggested clause amendments, and machine-readable metadata ready for CLM systems. Workflow connectors triggered alerts, renewals, and internal handoffs, ensuring that insights flowed seamlessly into downstream processes and review cycles.