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AI Board

For operations leaders

AI for COOs and operations directors, grounded in your own operations data

You know the questions before anyone asks them: what's our real on-time number, where did the margin go, which accounts are about to blow up. The problem is that the answer lives in three systems that disagree, and the version you walk into the MT with is the one you couldn't fully reconcile in time. An AI grounded in your own operational files closes that gap.

The enemy isn't a hard question. It's the hour before the monthly MT, still hunting for a figure that holds up while ERP and the planning tool quietly contradict each other. That gap is not a you problem; it is the AI problem, told at the operations seat. Gartner predicts that through 2026, organizations will abandon 60% of AI projects that aren't supported by AI-ready data, and 63% of data leaders aren't sure they even have the practices in place. A COO lives inside that statistic every close: the data isn't reconciled, so no answer can be trusted.

Most tools aimed at your seat make it worse, not better. Consulting decks promise 'predictive operations' with no week-one payoff. Ops-automation and RPA move tasks around but never tell you which of your two on-time numbers is right. A BI dashboard shows the figure but not why ERP and planning disagree, or what to do about it. None of them read your actual files and reconcile them.

AI Board is different because it is grounded in your own operational files (the ops dashboard, the margin-by-project export, the SLA report) and names the source and version behind every figure, so you can check it in ten seconds instead of trusting it blind. This page is about how you work with it week to week. For the underlying move (asking a question of your own files and getting one grounded answer), see chat with your data.

The week you recognize

One ops number that reconciles: the hour before the board

ERP says on-time delivery is 94%, the planning tool says 91%, and you can't walk into the MT with a figure you can defend, let alone explain the three-point gap. So you version MT Ops Dashboard Q2 definitief.xlsx for the fourth time and pick the number that looks least wrong. What you actually need isn't a prettier dashboard; it's the reconciled figure and the one-line reason the systems disagree, ready for the CFO's counter-question.

Gross margin dropped two points and everyone shouts 'volume'

The margin slips, you're held accountable in the MT for a drop you can't yet attribute, and isolating the real drivers (overtime and rework on specific projects versus purchasing creep) takes two days pivoting across three systems. You distrust the over-exact numbers those pivots spit out against messy multi-system data, and you're right to. The answer you want is honest about how it's estimated and still lands on a move, not a spuriously precise decimal.

You learn a top customer is unhappy when they call, angry

There's no escalation radar. A key account has been slipping below 90% on-time for weeks, but you find out only when the phone rings, after the damage. What you can't see is which of the top-20 will breach SLA next week while the backlog holds, and which line you'd move to stop it. That after-hours dread is firefighting escalations that were visible in the data days ago.

Live demo

Your personal AI assistant, thinking

Which top customers are about to escalate before they call me?

Four top-20 accounts slipped below 90% on-time this month. Van Leeuwen and Kramer Groep breach SLA next week if the backlog holds. Call both today and pull a line onto their orders.

SLA Performance Top 20 - Q2 2026.xlsxOn-time by account · Q2
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What changes

The reconciled number, with the reason for the gap

Ask for the clean on-time figure and you get the reconciled number, which system leads and why (ERP's actual goods-issue dates versus planning's old promised dates), and a one-line rebuttal for the CFO, sourced to the exact file and tab so you can verify before you commit. A dashboard stops at the number; a second brain grounded in your files carries it through to something you can defend in the room.

The margin drivers, estimated honestly, ending in a move

Where the margin actually went (overtime and rework isolated by project versus purchasing creep at a named supplier), assembled from your own files instead of two days in Excel. It tells you what's estimated on booked hours rather than pretending to be exact, and ends on the action: reprice the project that's leaking, before the next run.

An escalation radar, not a rear-view mirror

Which top accounts breach SLA next week if the backlog holds, when it breaks, and which line to move to prevent it, surfaced before the customer calls, not after. That turns the after-hours dread into a decision you can take to the capacity meeting: call today, pull a line, name the trade-off. It's not a dashboard; it's an action.

Answered on demand

Orders behind the gap

How many orders sit behind the three-point gap between our ERP and planning on-time numbers, and what's it worth?

Capacity trade-off

If I pull a line onto the accounts at risk, which orders slip, and at whose cost?

Where the backlog is aging

Which orders in the backlog are oldest against their promised date, and which customers do they belong to?

Overtime and rework

Which projects are running the most overtime and rework right now, and is it eating the margin or the schedule?

Questions, answered

What can AI actually do for a COO?
It works at your level, grounded in your own operational files (ops dashboards, margin-by-project exports, SLA reports) rather than the open internet. You ask the questions you already ask yourself before every MT: what's our real on-time number, where did the margin go, which accounts are about to escalate. It answers from your actual data, names which system leads and why when they disagree, and cites the source document so you can check it. It doesn't replace your judgement; it removes the two-day hunt between you and the answer.
How is this different from an ops dashboard or RPA?
A dashboard shows you a number but not why your two systems disagree about it, or what to do next. RPA and ops-automation move tasks around. They don't reconcile your on-time figure or attribute a margin drop. AI Board reads your own files, gives you the reconciled figure with the reason for the gap, isolates the real drivers, and ends on the move. It's the decision layer neither a dashboard nor an automation tool gives you.
Which number does it reconcile, and how?
Whichever one your board asks about (on-time delivery, margin, SLA performance), where two systems hold different versions of the truth. It reads both sources, names which one leads and why (for example, ERP's actual goods-issue dates versus the planning tool's old promised dates), gives you the reconciled figure, and traces it to the exact file and tab. The point isn't a confident single number; it's a number you can defend because you can see where the gap came from.
Does our operational data stay private?
AI Board is private by design: it runs grounded in the files on your own machine, so your ops dashboards, margin data and customer SLA reports stay where they are. The honest alternative is already happening informally: [MIT's NANDA initiative found employees at over 90% of companies use personal AI tools for work while only about 40% of companies have an official AI subscription](https://fortune.com/2025/08/19/shadow-ai-economy-mit-study-genai-divide-llm-chatbots/), which means operational and customer data pasted into personal chatbots. A grounded second brain on your own laptop is the private alternative. More on that on the [security](/en/security) page.

The org-wide AI programme stalls on data: RAND found more than 80% of AI projects fail, roughly twice the rate of comparable IT projects, mostly on data issues rather than model magic. Your own second brain over your real files doesn't wait on that programme. And the operational decision surface is moving your way: Gartner predicts at least 15% of day-to-day work decisions will be made autonomously by agentic AI by 2028, up from none in 2024. The COO who walks in with a reconciled, grounded number is positioned for that. The one who waits on the next dashboard project is not.

Walk into the MT with a number that holds up

See how a second brain grounded in your ops, margin and SLA files reconciles the figure, explains the gap, and names the move, before the board meeting starts.

Runs on your own laptop. Your data never leaves it.