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Step 3 of five

AI Advisory

Reports that arrive without being asked for, saying what changed and what to look at.

How a report becomes an answer The whole operating record, holding sensors, shift notes, work orders and production batches, produces a daily note and a weekly summary without being asked. Reading them raises a follow-up question in plain language, which is answered from the same record. The whole operating record sensors, shift notes, work orders, production batches Daily note what moved since yesterday Weekly summary and what it cost Your question in plain language arrives without being asked for answered from the same record
The two reports run on a timer. The question is yours, and it lands back in the record the reports were built from, so the answer can put a trend, a shift note and a work order side by side.

Replaces

  • The analyst's Monday morning
  • An ad-hoc spreadsheet nobody maintains
  • Asking three people what happened last week

Pays for itself by

Turning the Monday production meeting from assembling numbers into deciding on them. Surfacing a drift nobody had time to go looking for.

The number a buyer checks: Hours a week spent building reports, and issues found by the system rather than by someone noticing.

Reports that arrive on their own

A daily note on what moved and a weekly summary of what it cost. Both are drawn from the whole operating record rather than one system’s slice of it: maintenance cost and completion trends, created against completed work, inspection outcomes, per-asset history, energy per unit of output, and any chart you have saved from your own metrics.

The value is that nobody has to remember to go and look.

Ask the follow-up question

A report tells you energy per tonne rose on the night shift. The next question is always specific and always different. Which line. Which product. Was the moisture higher. Did somebody change a setpoint. Was that the week the dryer fan was down.

You ask that in plain language and get an answer drawn from the same record, with the trend and the shift note and the work order side by side.

Why this is hard for anyone else to build

Asking a plant questions in plain language only works if the sensor trend, the shift note and the maintenance history sit in one queryable place, against the same equipment and the same production batch.

That is the thing Koidra spent years building, and it is the reason this level exists at all. A chat window bolted onto a historian can answer questions about sensors. It cannot tell you that the week output dropped was the week a stand-in operator logged three manual overrides, because it has never seen the log.

The order matters. The data foundation is not a feature we added to support the AI. The AI is the first thing that became possible once the foundation was there.

What we build for you

Reporting is shaped around what your plant actually needs to know, which differs by process and by who reads it. A pellet plant manager and a data centre operations lead want different weekly notes, and both want something different from what a maintenance lead wants on a Monday.

That is a conversation rather than a configuration screen. Tell us the questions your team keeps asking and we will build the answer into the reporting.

Where this sits

Four steps to autonomous operations. Each one is a complete product with its own payback, and each makes the next possible. Read the full ladder.

  1. STEP 1

    Essentials

    Every signal the plant produces, in one place, live and historical.

  2. STEP 2

    Maintenance Management

    The system decides what maintenance is due, dispatches it, and tracks what it cost.

  3. STEP 3

    AI Advisory

    Reports that arrive without being asked for, saying what changed and what to look at.

  4. STEP 4

    KoPilot

    Closed-loop control of the process, minute by minute, with no human at the panel.

Next step: KoPilot. Closed-loop control of the process, minute by minute, with no human at the panel.

See Koidra on your own plant data

Bring a week of readings from one line. We will show you what the platform sees, what it would have flagged, and what it would have scheduled.

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