You ask an AI tool a question. An operational agent understands what to inspect, who to involve and how to follow the decision through to its outcome.
The problem on the shop floor is often not a lack of insight. An alarm appears, a chart changes and a team notices a deviation. The real loss occurs while people investigate its meaning, find the right owner and follow the action to completion.
A torque failure is not only a maintenance issue. It can affect quality risk, production planning, material flow, delivery promises and financial impact at once. When every team looks at a different screen and priority, the shared decision slows down.
Kaptan AI is therefore designed not as a separate chat screen, but as an operational agent inside the PiriVision Industrial Decision Layer. It brings connected systems, boards, alarms, conversations, actions and historical events into one decision loop.
Not another AI tool. An operational agent.
A general-purpose AI tool responds to the text a user provides. An operational agent considers the asset, station, shift, product, recipe, order and team context in which the problem occurs. Generating an answer is only the beginning; the goal is to prepare the next decision and follow it to an outcome.
Living inside the operation does not mean replacing control systems. PLC and SCADA retain control responsibilities, MES retains production records and ERP retains planning and orders. Kaptan brings their signals together as evidence, priority and recommendations people can evaluate.
Kaptan does not take over the control loop. It accelerates the human operational decision loop.
Context is more than a single screen
An alarm label alone is insufficient. The same value can mean different things for a different product, shift or machine state. Kaptan considers the related KPI, historical trend, similar events, open actions and business impact.
This living context includes data sources, dashboards, alarms, messages, users, actions, notifications and history. Connected around one signal, it shifts the discussion from “which number is right?” to “which decision is right?”
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Identify the asset and process behind the signal
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Compare the live value with historical behavior
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Connect affected products, orders and KPIs
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Retrieve similar events and previous interventions
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Prepare decision options for the right role
Every alarm should lead somewhere
The goal of alarm management is not more notifications. ISA-18.2 treats alarm systems as a lifecycle spanning definition, prioritization, operation, monitoring and change management, supporting meaningful and timely operator response.
In PiriVision, an alarm becomes a decision object with acknowledgement, ownership, discussion, evidence, due time and closure result. The gap between “alarm received” and “risk managed” becomes visible.
Watch context turn into action
Kaptan follows the live signal, combines historical context and coordinates the next step inside the operation. Recommendation, ownership and verification do not remain in disconnected tools.
The closed loop runs alarm → investigate → decide → own → execute → impact. When work is complete, the system checks whether the KPI recovered and whether the expected impact occurred.
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Open the alarm in shared context
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Review historical signals and similar events
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Present the recommendation for human approval
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Assign the action to the right role and due time
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Record execution results
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Verify KPI and financial impact
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Add learning to operational memory
Keep the conversation where context lives
Email, calls and messaging can speed communication, but context disappears when discussion is separated from the signal. Teams must repeatedly explain which chart, decision and responsibility they mean.
PiriVision keeps the conversation with the event, KPI and action. Maintenance findings, production capacity decisions, supply-chain checks and sales delivery assessments remain in one traceable event history.
Better collaboration is not more messages. It is shared context around the same signal.
One torque failure, multiple operational decisions
Torque NOK count rises at WP6. Kaptan identifies that torque tool #2 temperature exceeds 65°C across most NOK cycles and resembles previous overheating events.
While maintenance inspects cooling, Kaptan connects affected production orders and delivery risk. Production evaluates controlled slowdown or alternate capacity, supply chain checks spares, and sales sees only orders genuinely at risk.
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Signal: WP6 torque NOK count rises
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Context: Tool #2 temperature and history are connected
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Root-cause candidate: Cooling performance is prioritized
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Decision: Inspection and capacity plan are approved
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Ownership: Maintenance, production and planning tasks are separated
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Verification: Torque distribution and temperature recover
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Impact: Avoided downtime and protected orders become visible
You do not need to speak SQL. PiriVision does.
The people with the best operational questions do not always write SQL. Makinist helps translate natural-language needs into queries inside Compass.
Technical users can inspect and deepen the query; others can start with a business question such as “Rank torque loss by station this shift.” Query validation and data-access policy remain under organizational control.
Follow one signal. Watch the loop close.
A decision system is valuable not only when it generates a correct insight, but when it shows whether that insight reached execution. Kaptan’s experience does not end in an answer box.
The user opens the signal, reviews evidence, approves the recommendation, assigns an owner and confirms completion. Decision time, ownership and KPI outcome remain in one event history.
The same signal. The right decision for every role.
Shared context does not mean everyone sees the same screen. The WP6 event means a safe check for the operator, technical evidence for maintenance, capacity risk for production, delivery impact for sales and financial outcome for leadership.
Role-based surfaces emphasize the relevant part of one event without fragmenting information or overwhelming decision-makers.
Operator
Sees the deviation, safe check and assigned task.
Maintenance engineer
Evaluates temperature, torque distribution, similar events and the technical inspection.
Shift lead
Tracks line target, action owner and due time.
Production manager
Sees capacity loss, alternate plans and affected orders.
Supply chain
Assesses critical parts, spare equipment and material-flow risk.
Sales
Tracks orders that may be affected and current delivery risk.
Leadership
Reads operational loss through financial impact, closure time and recurrence risk.
Trust for an operational agent: human oversight and traceability
Industrial environments require governance as much as speed. The NIST AI Risk Management Framework treats clearly defined human-AI roles, responsibilities and oversight as part of trustworthy AI management.
Kaptan recommends; critical decisions move through authorization, policy and human approval. Evidence, recommendations, approvals, actions and measured outcomes should remain traceable.
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Define role and authority boundaries
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Show recommendations with supporting evidence
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Require human approval for critical steps
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Record decisions and change history
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Measure outcomes and allow recommendations to be overridden
Measure closed loops, not chat volume
The value of an operational agent is not the number of questions it answers. The meaningful measures are time to owner, time to decision, action closure rate, recurring events, avoided downtime and protected financial impact.
McKinsey’s digital performance-management framing similarly emphasizes the right data, source, time, person and decision. Kaptan operationalizes that chain inside daily production.
Conclusion: A living decision loop from insight to impact
Kaptan AI is different because it is not another tool outside manufacturing context. It connects live signals with history, technical findings with business impact, conversation with action and action with measurable outcome.
A torque signal does not disappear into a maintenance screen. Each role sees its decision on shared context, tasks move with human approval, the KPI closes the loop and learning remains for the next event.
Not another AI tool. A decision partner living inside your operation.