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Pranuthanjali@inextlabs
Pranuthanjali@inextlabs

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How We Built an AI Document Intelligence System That Cut Compliance Review Time by 85%

Originally published on iNextLabs Casestudy


The Problem

A leading Malaysian bank had 25+ legal and compliance professionals manually searching through thousands of contracts and regulatory documents every week.
Simple queries like "which clauses are affected by the latest BNM guidelines?" took hours. That's not a search problem it's an architecture problem.
Here's how we solved it..


The Stack

  • LLMs for contextual understanding and clause analysis
  • Semantic search (vector embeddings) instead of keyword matching
  • RAG (Retrieval-Augmented Generation) to ground responses in actual documents
  • RBAC with database-driven permission management
  • PDPA-aligned data governance controls

What We Built

  1. Natural Language Query Engine Users ask plain-English questions. The system retrieves semantically relevant document chunks, passes them to the LLM with context, and returns a precise answer not a list of files.
  2. Automated Compliance Analysis LLMs scan policies against regulatory frameworks (BNM, PDPA Malaysia), flag inconsistencies, and summarize obligations. No manual cross-referencing.
  3. Contract Diff & Risk Engine Compares contract versions, highlights changed clauses, and scores risk across thousands of documents simultaneously.
  4. Secure Multi-Tenant Access Role-based permissions ensure users only query documents they're authorized to see. Critical in a banking environment. ---

The Results

  • 85% reduction in document review time
  • Hour-long searches → seconds
  • Improved compliance accuracy and consistency

Key Takeaway

Keyword search is dead for enterprise document workflows. Semantic search + RAG + LLMs is the architecture that actually works at scale in regulated industries.
Happy to go deeper on any part of the stack drop a comment.

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Top comments (1)

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mary_mrazo_05cbbbf3b9ee profile image
Mary M. Razo •

Solid case study with results that match what we see in practice when RAG and semantic search replace manual document review. The key is having the document management layer govern what the AI can access, which is what keeps those efficiency gains compliant. Dokmee fits naturally as that governance foundation.