AI Agents for Statistical Process Control

Established SPC tools are mostly batch and human-in-the-loop: someone pulls data, generates the chart, reviews it, files the result. PipeIQ agents run the same statistical methods continuously, on streaming data, and act when a rule fires — opening the CAPA, paging the owner, or triggering a downstream adjustment. Most engagements complement existing tooling rather than replace it.

Yes, when the metric is meaningful. Continuous metrics (cycle time, AHT, model score) chart well with I-MR or EWMA. Count metrics (errors per case, escalations per shift) chart with c or u. Proportion metrics (FCR, defect rate) chart with p or np. The agent picks the right chart, validates the assumptions, and runs it.

Configurable per rule and per process. Low-risk processes can let agents close the loop (auto-adjust setpoint, route to next agent). Regulated or high-risk processes always require human approval before any action — the agent prepares the CAPA, the human signs it. Both modes maintain a complete audit log.

Every chart, every rule check, and every CAPA is logged with the underlying data, time window, model version, and decision rationale. Audit packages are exportable as ISO-compliant control records. For FDA-regulated processes, the validation package covers IQ/OQ/PQ requirements and CFR Part 11 electronic record controls.

Two to four weeks for first-chart production on a single process. Six to ten weeks for the full charting library across a function. The expensive work is rarely the SPC itself — it's wiring the agent to the source data and the downstream action systems.