How streaming operational technology data into Databricks lets compound AI agents reason, optimize, and advise, not just monitor.
by Mohammad Khelghati
09:14, mid-shift. The filler trips. The line manager has minutes, not hours, before downstream equipment starts to starve. The crew already knows what to do mechanically. The questions that take longer are the planning ones. Can we still hit the shift target? Is it cheaper to push speed afterwards or call overtime? Has the same fault hit this line before, and how did the previous shift recover?
The data to answer all three already exists, scattered across PLCs, SCADA, MES, ERP, and LIMS.
ProdLine CoPilot is built for that window. It reads live state from the Databricks Data Intelligence Platform, routes the question to a domain specialist, and runs the underlying math (schedule recovery, depletion, quality risk). The plan comes back tested against 1,000 scheduling scenarios balancing trade-offs in cost, overtime, and service. The line manager picks. The system drafts the artifacts (work order, hold, schedule note) for approval.
