AI that already knows your factory
A general assistant can only answer from what you paste into it. The AI in EpoSystem is already inside the data — every project, stage, material reservation, absence and supplier date — so it can rank the day, predict a delivery and explain why, without anyone preparing a report for it first.
- Reads
- Your live production data
- Recalculates
- Whenever anything changes
- Answers
- In chat, from your numbers
The day, already sorted
Before the morning meeting the assistant has read the whole operation and put it in order. Not a summary of yesterday — a ranked list of what today needs.
Lead with this
One action at the top, with the project it affects, the team it involves and the reason it came first.
What is at risk
Projects whose predicted finish has moved past the promised date — while there is still time to do something about it.
What is waiting
Jobs that cannot start because material, an earlier stage or a person is missing, and which of those you can clear today.
Where the spare capacity is
Teams with hours free this week, so an urgent order has somewhere to go.
Four things happen, in order
There is no separate AI project to run first. The assistant works on the data the system already holds, every time something in it changes.
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It reads the whole operation
Projects, workflow stages, tasks, materials, warehouse stock, supplier dates, absences and the working calendar — the same records your people work from.
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It ranks what matters
Everything that could move a delivery date is scored, so a shortage stopping four jobs outranks one stopping none.
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It recalculates the plan
When a stage runs long or a delivery slips, the schedule, the capacity forecast and the delivery confidence are recomputed as it happens — not at the end of the week.
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It answers in plain language
Ask why a project is late, what to start next, or whether a new order fits. The answer comes from your live records, with the numbers it used.
What it is watching while you work
These are the inputs behind every ranking and every predicted date.
- Project readiness — which stages can actually start today
- Capacity per team, per day, against your working calendar
- Material availability, reservations and open purchase orders
- Supplier lead times and deliveries that have slipped
- Absences, and who is qualified for each production stage
- Workflow dependencies — what a delay pushes back downstream
- Delivery risk per project, before the date slips
An assistant beside the work, or inside it
Both are useful, and many factories will use both. The difference is what the assistant can see without being told.
| Criterion | A general AI chat | AI added to reports | EpoSystem |
|---|---|---|---|
| Where the data comes from | What you paste in | Yesterday's export | The live system |
| How current it is | The moment you pasted | As old as the last refresh | Now |
| Knows your capacity | Only if you describe it | Headline numbers | Per team, per day |
| Knows material and reservations | No | Rarely | Yes |
| Preparation before a question | Gather and paste the context | Build the report first | None |
| Can take you to the record | No | Sometimes | Opens the job |
| When the plan changes | Ask again with new context | Wait for the next refresh | Already recalculated |
| Where your production data sits | Whatever you paste leaves your systems | Depends on the tool | Your own database |
The time this actually saves
Most of a production morning is not spent deciding. It is spent assembling the facts to decide with: a call to the shop floor, a look in the warehouse, a message to purchasing, a spreadsheet somebody updated yesterday. By the time the picture is complete, half the day has been committed anyway.
When the assistant already holds those facts, that round disappears. The question changes from "what is going on?" to "do I agree with this order of work?" — and that is a question a production manager can answer in minutes.
The second saving is later and larger. A delivery date that is drifting becomes visible weeks before it slips, while there is still capacity to move, material to reserve or a customer to talk to. Reacting on the day it happens costs overtime; seeing it early usually costs nothing.
What it does not do
Deliberate limits. An assistant that acted on its own would be impossible to trust with a promise to a customer.
It does not decide for you
It ranks and explains. Releasing work, accepting an order and moving a date stay with the people accountable for them.
It does not invent numbers
Every figure it shows comes from a record in your system, and it can take you straight to that record.
It does not need a data project
Nothing to export, connect or schedule. It reads the system your people are already working in.
Frequently asked questions
Do we have to prepare anything for the AI?
No. It reads the same records your people already create — projects, stages, materials and the working calendar. There is nothing to export, connect or clean up first.
Can we ask it questions in Lithuanian?
Yes. It answers in the language the system is set to, and uses the same product terms as the interface.
Does it replace the production planner?
No. It prepares the decision — the ranking, the risks and the reasons behind them — and a person makes the call.
Where is our data processed?
Each company has its own separate database, and the assistant works against that data only. Nothing about one company's production is visible to another.
We already use a general AI assistant — why add this one?
They answer different questions. A general assistant is good at drafting and reasoning about whatever you give it; this one already holds your live production data, so it can answer about today without being briefed first.
How soon is it useful?
As soon as your workflow stages, your people and a first project exist. The rankings get sharper as more real work runs through the system.