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Industrial maintenanceServices and IT companiesillustrative example

Internal AI assistant on the know-how of a technical services company

An industrial maintenance firm depended on 4 senior technicians. Their knowledge was structured and made available to the whole team through an internal AI assistant.

-45%resolution time for junior technicians
620procedures and cases structured
8 wksfrom workshop to daily use

This case study is an illustrative example built from typical situations in our projects. Figures are indicative.

Context

Maintenance and service company for industrial equipment, ~45 employees, 4 senior technicians with 15+ years of experience each. Knowledge about equipment, recurring faults and customers lived in their heads, in emails and in phone photos.

The challenge

Junior technicians called the seniors for every new problem; resolution time depended on their availability. One senior had announced retirement within 12 months.

The approach

We inventoried critical knowledge by equipment type and customer, extracted it through structured interviews and field shadowing, and structured 620 procedures, solved cases and parameters. We built an internal AI assistant that answers questions from this knowledge base (with sources cited), accessible from a phone, and defined the update ritual: every new intervention with a new solution goes into the base.

Results

Average resolution time for junior technicians dropped 45%. Calls to seniors were reduced to truly new cases. The knowledge base grows by ~30 cases a month and has become the onboarding tool for new employees.

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