AI Agent

An expert colleague that never goes off shift.

An AI agent grounded in your asset model, live data, manuals and incident history. It answers questions, triages alarms, explains anomalies and recommends the next step, in every product on the platform.

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customers

Trusted by teams running critical operations

Enterprises across energy, heat, water and infrastructure rely on Blockbax to keep critical assets running.

"By automating tasks and improving productivity, we're prepared to support Eneco's asset growth strategy across our full portfolio."

Michel Klaasse
Michel Klaasse Head of Asset Control & Steering

"Blockbax is key to operating our heat networks at the highest standard, with full control over asset performance across all sources."

Harold Maasen
Harold Maasen Manager of Realisation, Operations & Asset Management

"With Blockbax, our maintenance and operations teams have real-time insight into our full fleet of energy solutions."

Noël Steentjes
Noël Steentjes Technical Director
Firan Eteck Heijmans Elix Nett Eneco Bredenoord TBI Van der Ende Group Gemeente Rotterdam Volta Energy Aquon Gigastorage Inwarmte Electroproject Caeli Additive Restrain
capabilities

AI that knows your operation

Built on your asset model, so every answer is grounded in your own data, history and context.

Natural-language questions

Ask about any asset in plain language, answered with cited sources.

Proactive surfacing

Spots developing issues before they trip a threshold.

Alarm-flood triage

Collapses alarm cascades to the probable root, prioritized by history.

Anomaly explanation

Every insight comes with the measurements and events behind it.

Similar-incident recall

See how comparable cases were resolved, and what to do next.

Predictive maintenance

ML forecasts flag degradation and likely failures before downtime.

A second pair of expert eyes,
always on

Ask what the live data means, and what to do about it.

AI answers in natural language, grounded in your asset data, manuals and history, and surfaces issues before they become alarms.

  • Natural-language questions: answered from live data, with cited sources
  • Context-aware follow-up: suggestions drawn from event history
  • Proactive surfacing: spots anomalies before they trip a threshold
Explore live condition monitoring
AI agent Heat pump A · District Heating

Why is heat pump A's COP trending down since Tuesday?

COP dropped 8% after source temp fell below 10°C. The same pattern in January was resolved by raising the flow setpoint. The filter is also due in 12 days.

Suggested actions
Sources: 3 metrics · 1 incident

When fifty alarms fire at once, where do you start?

AI triage answers that question in seconds.

Cluster alarm floods, surface the probable root alarm, and get the follow-up drafted for you.

  • Alarm-flood clustering collapse cascades to the probable root
  • Suggested prioritization from historical patterns
  • Drafted handovers shift and stakeholder updates, ready to send
Explore central alarm management
AI agent 47 alarms → 1 root
Alarm flood 47 alarms in 90 seconds · Substation 14

Heads up, 47 alarms just fired at Substation 14 in 90 seconds. I clustered them into one probable root. A breaker trip at 14:02 cascaded to 46 downstream sensors, so those are follow-on noise, not separate faults.

Suggested actions

A diagnosis partner with
perfect recall

Everything your operation has ever seen, at hand.

AI explains anomalies with the data behind them, recalls how similar incidents were resolved, and suggests the next step.

  • Anomaly explanation with the measurements and events behind it
  • Similar-incident recall how comparable cases were resolved
  • Suggested next step when the cause isn't obvious yet
Explore root-cause analysis
AI agent 47 alarms → 1 root

T-03 keeps tripping on pitch fault. What’s the cause?

7 trips in 7 days, all after wind gusts > 18 m/s. Identical signature to incident #2041 (Jan), resolved by recalibrating the pitch sensor.

Suggested actions

From 'what happened' to
'what to do next'

Recommendations that connect performance to known fixes.

AI links a performance dip to maintenance history and forecasts degradation before it becomes downtime.

  • Performance recommendations dips linked to maintenance history
  • Forecast-based early warning ML forecast conditions on key signals
  • Predictive maintenance flag likely failures ahead of time
Explore asset performance & reliability
AI agent
Predictive note

Bearing vibration trending to threshold in ~11 days. Similar profile preceded 3 past failures. Recommend inspection this cycle.

Put an expert on every shift

One AI agent across monitoring, alarms, diagnostics and performance,
grounded in your own asset model and history.

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