A platform that preserves an enterprise’s expertise and helps specialists make decisions.
Specialists’ experience lives in their heads and in scattered documents — and walks out of the door with them.
Years of accumulated experience leave the enterprise with them.
One person made the call — and there is no longer anyone to ask.
Equipment collects readings, but they never turn into decisions.
Most systems set out to take the human out of the loop. OpenEgiz does the opposite: it prepares a well-founded choice for the specialist and leaves the decision to them.
The system makes the decision. The specialist’s experience is devalued.
A person makes the decision, backed by prepared data and a forecast. Experience is preserved and compounded.
The modules do not depend on one another. Any of them can be replaced or updated on its own — swapping the AI model, for instance, without touching the rest of the system. A failure in one module does not halt the others.
Track equipment condition: temperature, pressure, humidity.
Identifies delays and bottlenecks along the production chain.
Records the movement of product and staff, and how zones are loaded.
All the sources work in concert. A new source can be added without rebuilding the system.
The knowledge base stores not isolated facts but how they connect: which equipment, which recipe, who is responsible, what has happened before.
“What is the temperature limit?”
A simple question — an ordinary spreadsheet can answer it.
“Which recipe is this equipment running, who is responsible, which procedures apply, and has a similar case come up before?”
A real question — this needs a connected knowledge base.
It is a continuously updated picture of production: what is happening, where, and to which batch, right now.
A sensor records “41.5 °C in the zone” but has no idea which batch that is. The system matches readings against record data — and gives them meaning.
The specialist marks off stages on a tablet. A simple start — running within a week.
Data is taken from what is already there: scales, control panels, 1C.
Recognition by tags or through video monitoring.
Indicative targets for the pilot project, to be confirmed at the first deployment.
Every enterprise runs its own instance of the system on its own hardware. Only the standard templates are shared — never the data.
Rolling everything out at once is inefficient. Each stage delivers a result and funds the next.
The future is not about replacing people with artificial intelligence, but about people, the digital twin and AI working together.
OpenEgiz is a platform for preserving and growing the knowledge of Kazakhstan’s industrial enterprises.
We are ready to demonstrate OpenEgiz and discuss a pilot at your enterprise.