Enterprise AI Assistant Case Study | Global Manufacturer
Client Profile
A multinational heavy equipment manufacturer with engineering headquarters in Germany, production facilities in China and Japan, and a global maintenance workforce.
The Problem: Scattered Manuals Were Turning Routine Repairs Into Multi-Day Delays
Every hour a technician spent hunting for the right repair step was an hour the production line stayed down. The client’s technical manuals, repair protocols, and engineering schematics were scattered across legacy intranet systems, written mostly in German or English, with no reliable way to search across languages.
Maintenance staff in Japan and China couldn’t self-serve. They either guessed, waited on a translated reply from central engineering in Germany, or escalated to a specialist — and each of those paths added hours or days to a repair that should have taken minutes.
| Failure Point | Business Impact |
|---|---|
| Manuals scattered across legacy intranets in German/English | Technicians couldn’t self-serve on the factory floor |
| No cross-lingual search | Japanese and Chinese staff waited on manual translation from HQ |
| Escalation to central engineering | Equipment downtime stretched from hours to days |
| Unofficial workarounds | Risk of technicians following outdated or incorrect steps |
The Solution: A Custom AI Assistant Built on Enterprise RAG
ISZ.AI built a secure, multilingual enterprise AI assistant that answers a technician’s question in their own language and cites the exact source document — no manual translation, no escalation queue. The system runs on an enterprise RAG architecture, giving technicians a knowledge base chatbot they can trust on the floor, not a generic model guessing at an answer.
- Data Ingestion: We indexed over 50,000 pages of PDF manuals, schematics, and past maintenance logs into a secure vector database.
- Multilingual LLM Integration: We deployed a foundation model optimized for cross-lingual understanding, so a technician can ask a question in Japanese and get an accurate answer synthesized from a German source document.
- Source Citations: Every generated answer links back to the original engineering manual, so technicians never act on an unverified or hallucinated instruction.
The Results: Enterprise RAG That Cut Search Time 80% and Recovered Uptime
The assistant paid for itself by removing the translation bottleneck between Asian maintenance teams and German engineering. Technicians stopped waiting on HQ and started resolving repairs the moment a question came up.
- 80% Reduction in Search Time: Technicians found answers in seconds instead of hours.
- 98% Cross-Lingual Accuracy: Verified across German, English, Japanese, and Chinese technical translation and retrieval.
- Decreased Downtime: Faster repairs drove a measurable increase in overall equipment effectiveness (OEE) across the Asian facilities.
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