Enterprise Knowledge Chatbot
Global Industrial Equipment Manufacturer (Fortune 500) — 45,000+ employees across 12 countries.
2025
The challenge
What we found.
A Fortune 500 industrial equipment manufacturer with 45,000+ employees across 12 countries faced a critical knowledge management crisis. Their engineering and service teams spent an average of 2.5 hours per day (30% of their workday) searching for information across disconnected systems—SharePoint, legacy documentation, product manuals, and tribal knowledge locked in email threads.
New technicians took 6–9 months to become productive, and institutional knowledge was walking out the door as experienced engineers retired. The company estimated they were losing $18M annually in productivity due to information fragmentation.
The approach
How we built it.
PRR deployed an Enterprise Knowledge Assistant using Azure AI Foundry with a secure RAG architecture:
- Connected 14 enterprise data sources including SharePoint, Confluence, ServiceNow, SAP documentation, and 2.3M historical support tickets
- Implemented document-level access control ensuring users only see information they're authorized to access
- Integrated via Microsoft Teams and Copilot Studio for seamless adoption within existing workflows
- Custom-trained embeddings on industrial equipment terminology and part numbers for high-precision retrieval
- 01Ingestion14+ sources via Azure Data Factory
- 02VectorizationQdrant + OpenAI embeddings
- 03GenerationGPT-4 Turbo with citation tracking
The outcome
The impact.
| Metric | Before | After | Improvement |
|---|---|---|---|
| Time to find information | 2.5 hrs/day | 0.4 hrs/day | 84% reduction |
| New hire ramp time | 7 months | 3 months | 57% faster |
| First-call resolution rate | 62% | 89% | +27 pts |
Stack
Tools used.
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