Begin away from machine control
Potential early investigations include retrieving approved work instructions, summarising shift notes, routing non-critical maintenance requests or helping staff locate equipment documentation. These are possibilities to evaluate, not guaranteed solutions. Keep machine control, safety actions, maintenance release and production approvals outside an assistant’s authority unless a separately validated engineering process explicitly allows otherwise.
Map context, permissions and exceptions
Before selecting a model or agent, understand the workflow: who asks, what records are trusted, how revisions are managed, what information may be sensitive and who resolves exceptions. If a procedure is outdated or the knowledge base conflicts, the system should make that uncertainty visible and defer to the responsible person.
Why localization matters
Tamil Nadu’s industrial base includes automotive, electronics and heavy-engineering clusters, each with different operational vocabulary and supplier structures. The same assistant design may not transfer across plants or even across departments. Build a representative test set with the workers and process owners who know the local task.
Treat evaluation as an operating discipline
Measure answer correctness against controlled sources, time saved after human review, escalation quality and the rate of unsupported responses. Monitor changes when work instructions, equipment or policies change. A literature survey on agentic AI in manufacturing identifies both application opportunities and integration challenges; teams should read such work as a research map, not deployment evidence.