CLIFFGATECLIFFGATE · Industrial AI
Industrial AI: Engineer knowledge assistant
LLM-based search and decision support for maintenance, process, and incident teams
Problema de negocio
Engineering knowledge is usually scattered across PDFs, manuals, equipment passports, incident reports, shift logs, regulations, emails, and the memory of experienced specialists. When a non-standard situation occurs, time is lost searching for the right instruction and past cases.
Enfoque técnico
- —Build a controlled knowledge base from manuals, procedures, equipment documentation, repair history, incident journals, and internal regulations.
- —Use retrieval-augmented generation so the assistant answers from approved sources rather than uncontrolled memory.
- —Allow engineers to describe a symptom in natural language and receive likely causes, relevant procedures, similar historical incidents, and recommended checks.
- —Apply access control so sensitive operational, safety, or financial information is only visible to authorized roles.
- —Log questions and answers to identify knowledge gaps and improve documentation.
Resultado de negocio
- —Faster troubleshooting and lower dependency on a small number of senior engineers.
- —More consistent decisions across shifts and locations.
- —Shorter onboarding time for new technical staff.
- —Better use of historical incidents and maintenance records.
- —A living knowledge system that improves as the company operates.