Every plant starts the day with a plan and a reason it is already wrong. The demand we keep hearing: a scheduler that takes live production data, reasons about the whole board when a disruption lands, and writes the result back into the systems that run the plant.
Production data flows in. A scheduler reasons about the whole board - every line, every job, every constraint - and the result flows back into the production systems that execute it. That is the ask, in one breath: not a dashboard that suggests, a loop that closes.
The planners feel this pain daily. When a delay lands, someone rebuilds the day by hand, under pressure, while the plant waits on the outcome. The endorsement we heard was plain and specific: this would be useful to the sites, and useful to the planners who run them.
Heard from the leader of an ERP-improvement team at an enterprise coatings and specialty-chemicals maker. Paraphrased, like everything on this map.
A scheduler is only as good as the live constraint data underneath it, and shop floors are fragmented. Several generations of MES. A legacy ERP. Spreadsheets guarding the edges. Getting a current, trustworthy picture of the board into the scheduler - and the result back out - is most of the work. Integration is the product; the optimization is the smaller half.
The second failure mode is quieter. Run the same inputs twice and get two different schedules, and planners stop trusting the tool - quickly, and for good. The outcome is not allowed to move unless the inputs did. That is a hard engineering requirement, and most demos quietly ignore it.
So we say AI-assisted and dynamic scheduling, and we mean it narrowly: the reasoning helps only after the plumbing and the repeatability are solved. Anyone who leads with the algorithm has not met your shop floor.
Directional by design. How big each pool is depends on your mix, your constraints and your data - but which pools exist does not. The same four come up wherever we hear this ask.
When a disruption lands, the gaps stay where they fell - and every hour a line waits on a plan is an hour the plan pays for.
A re-pack squeezes the gaps out of the board instead of leaving them where the disruption dropped them.
The published plan and the executed day drift apart, and every commitment downstream of the plant is made against the wrong document.
Plan and day converge, so commitments downstream of the plant stop being fiction.
Rebuilding the day by hand, under pressure, is skilled work spent on mechanics - while the plant waits on the outcome.
The planners get their judgment back and lose the re-keying.
Every disruption becomes a meeting, and people learn to plan around the plan instead of trusting it.
A disruption absorbed by the board never becomes a meeting. The plan survives contact with reality.
Two engines run in production today - Analytical Lab Reports and account Knowledge Twins. Everything else on this map is an extension on the same foundation.
Scheduling is one of the domain agents the framework is built to carry. CONNECT streams production data between your MES, your ERP and the agent - both directions. The agent reasons about the whole board. ACT pushes the result into the systems that execute it. AI reasons; your enterprise systems execute. No new system of record, no rip-and-replace.
Inside your infrastructure, inside your boundary. Constraint data and schedule logic never leave, and you keep freedom of action: choose the models, move the workloads, control the economics as the landscape shifts.
Walk us through one real disruption - the delay, the collisions, the manual re-plan. We will show you where a scheduling agent absorbs it, and where the integration work sits. If the answer does not convince you, you have lost an hour.
On-prem. Your data never leaves your boundary.