CASE STUDY: LOGISTICS & SUPPLY CHAIN

Reducing Documentation Retrieval by 85% with AI-Powered Semantic Search

How a 3PL provider with 200+ warehouses transformed internal knowledge access for 800 operations staff.

85%
Faster Retrieval
60%
Onboarding Cut
15k+
Docs Indexed
3sec
Answer Time

The Problem

Operations staff were spending 45+ minutes per shift searching through outdated SharePoint folders. Critical SOPs were buried in PDFs, and new hires took 3+ months to become productive due to tribal knowledge.

  • 15,000+ documents across 12 different systems.
  • No search functionality beyond exact keyword matching.
  • High error rates from outdated procedure references.

The Architecture

We deployed a Semantic Knowledge Agent that understands natural language queries and retrieves precise answers.

Technical Components:

  • Semantic Index All docs vectorized with OpenAI embeddings for meaning-based search.
  • Chat Interface Slack bot for instant answers: "How do I process a damaged pallet?"
  • Auto-Sync Pipeline n8n workflow re-indexes updated docs nightly from SharePoint.

The Results

Within 90 days, average time-to-answer dropped from 8 minutes to under 3 seconds. New hire onboarding was cut from 12 weeks to 5 weeks. The client estimated $320k annual savings in productivity gains.