An assistant that knows your figures, not the internet

Every answer is based on your own, current business data and can be traced back to the figures behind it.

Test the AI assistant Works on sample data with fictitious figures

Orders today · live demo Sample data

Your AI assistant

Where is it going wrong: which orders are at risk of leaving late today, and why?

At 7 am, 14 orders are at risk: 8 are waiting for replenishment and 6 have too few people in their zone. The 8 orders waiting for replenishment are all in zone C. Start replenishment there first: the first order must leave at 12:00.

Which customer has the most orders at risk today? How many orders are there today, and how many are on schedule?

Type your question… Send

Why you can trust the answers

Calculate first, then explainThe calculation is done directly on your data. Only then does the AI explain the result in plain language.

Only your own sourcesIt does not search the internet and works only with the systems and files you designate.

You decideThe assistant gives explanation and advice. It does not carry out actions in your systems.

Two examples from the demo

Orders At 7 am you know what is going wrong "Today 14 orders at risk. 8 are waiting for replenishment in zone C. Start replenishment before 9:00." You see it before the truck leaves, not after. Try it in the demo: Orders today →

Stock An alert three days in advance "Item 4711 runs out within 3 days. Usage 120 per day, 350 left in stock. Order today." No more empty locations during picking. Try it in the demo: Stock →

What teams also use it for

Stock advice Quality check on deviations Delay alerts on delivery Forecast per product line Staff capacity planning KPIs explained in plain language

What the assistant does for each problem

AI only works well when the process and the data are in order. That is why each solution comes with its own task for the assistant. The assistant suggests, a person decides.

The figures don't add upA check flags a figure that is illogical or missing before anyone makes a decision based on it.

When someone drops out, the work stopsEvery morning there is a proposal for who can take over which task, based on the training matrix.

Productivity is not measured correctlyYou get an alert when productivity deviates from the standard, with the likely cause.

Information is scattered everywhereQuestions in plain language get an answer from your own figures, instead of searching in ten files.

Improvements stay superficialAI finds patterns in months of scans and errors that the naked eye cannot see.

Improvements don't stickEvery week there is a summary of what has improved, what is slipping and which action is still open.

Forecasting and planning are done by handAI forecasts the volume per day and per hour and proposes a staffing level. The planner decides.

Which questions would your team ask tomorrow? Whether your data is ready for such an assistant, you will see after the quick scan.

See the quick scan