Agent-driven industrial decisioning with human supervision, running steady in water-treatment operations.
About this page
This page only depicts a conceptual architecture and capability summary. No customer production data, sensor readings, or live system UI is shown.
What the agent takes off people's plates
Sensor arrays feed water quality, flow, and dosing metrics into the agent context at second-level latency.
Threshold models combined with LLM reasoning produce dosing recommendations and risk levels for human review.
Actuators adjust dosing, results feed back to the agent to form an adaptive closed loop.
Decisions outside critical thresholds require human confirmation; all actions are audit-logged per regulation.
How the agent and human supervision collaborate
source
Sensor array
agent
Agent layer
output
Dosing actuator
human
Operator
Flow