Where ConstraintFlow fits — and where it doesn't
The fastest way to waste your time is to evaluate a tool built for a different problem. This page says plainly what ConstraintFlow is for, what it is not for, and which tools are right for the jobs we don't do.
ConstraintFlow runs live across an 11-plant packaging network — recommending cost-optimal site and machine assignments on real orders since June 2026, validated by the customer's own master schedulers.
How we measure results →Built for discrete, multi-plant manufacturing decisions
ConstraintFlow is the decision layer above the systems you already run — strongest where orders move between plants, changeovers are expensive, and expert scheduling knowledge is scarce.
A co-pilot for operating decisions
ConstraintFlow recommends; your planners approve, adjust or reject. It is built for operations that want better decisions with people accountable — not lights-out automation.
Trade-offs made visible
Every recommendation shows what it protects and what it costs — setup hours, freight dollars, delivery risk — so the decision is defensible, not just fast.
A lightweight layer, not a migration
Zahir, ConstraintFlow's governed Data & Context Foundation, connects to any system of record — modern, legacy, or homegrown. Start with the systems and context required for the first decision, then expand the operational model over time; our production customer runs OneMax and JD Edwards.
Networks, not just plants
The core question ConstraintFlow answers is one no within-plant tool asks: which plant should run this order at all, on total landed cost — setup, run, and freight.
Sequence-dependent complexity
In envelope converting, a die-match changeover can run 2 hours and a full product change 21. ConstraintFlow models that spread instead of treating every setup as the same constant.
Operations that want to keep expert knowledge
Every planner decision is recorded with its reason and measured against execution — your schedulers' expertise, remembered, even as they retire.
Pharmaceutical and medical packaging
Discrete, serialized, changeover-heavy and tightly regulated — pharma secondary packaging shares the physics ConstraintFlow was built for. Recommendations remain human-approved and fully audit-trailed; the process-chemistry side of pharma remains out of scope.
If this is your problem, buy something else
These are real jobs that need real tools — they just aren't this one. We'd rather you bounce here than six weeks into an evaluation.
Not an MES or eBR
ConstraintFlow does not track execution on the floor or manage electronic batch records. Purpose-built MES and eBR platforms do that job — ConstraintFlow sits above them.
Not for continuous or process manufacturing
Refineries, chemicals, and other continuous-process operations are a different optimization problem, served by specialized process-optimization suites. ConstraintFlow is built for discrete manufacturing.
Not machine or PLC control
ConstraintFlow never touches a controller. Industrial automation platforms run the machines; ConstraintFlow recommends what the machines should run.
Not a global supply-chain planning suite
If the problem is multi-echelon global network design and S&OP at enterprise scale, enterprise supply-chain planning suites are the right tool. ConstraintFlow is the operational decision layer for your manufacturing network.
Plant-level suites run the plant. ConstraintFlow decides across plants.
If you run packaging, you already run a plant-level MIS or scheduling suite — the tools that estimate, schedule and track work inside a facility. They are good at running the plant. ConstraintFlow asks the question they don't: which plant — and which machine — should run this order at all, on total landed cost including freight. It sits on top of them, and hands them a better plan to execute.
The same logic applies at enterprise scale: ConstraintFlow complements enterprise planning stacks rather than competing with them.
Sound like your problem?
Bring us one difficult cross-plant decision and we'll map how ConstraintFlow would handle it — or tell you honestly if it wouldn't.