Turn complex operations into better decisions.
ConstraintFlow connects enterprise data, operational context, domain knowledge and AI into one governed intelligence layer — helping teams understand what is changing, evaluate what to do next, act with confidence and learn from the outcome.
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 →One intelligence platform. Deep industry context.
The underlying intelligence architecture is reusable. The operational models, constraints, knowledge, workflows and decisions are specific to each industry.
Operational Intelligence for Manufacturing
Connect orders, machines, materials, labor, inventory, customer commitments and production constraints into a living operational model that helps teams make better decisions across the operation.
In production Deployed across an 11-plant packaging manufacturing network.
Operational Intelligence for Life Sciences
Connect scientific evidence, research knowledge, datasets and workflows into governed intelligence that helps teams investigate complex questions with context, traceability and human oversight.
Understand → Decide → Act → Measure → Improve
Every ConstraintFlow deployment — whatever the industry — runs the same governed cycle from fragmented context to measurable outcomes.
Understand
Create a current, contextual model of the environment from enterprise data, documents, knowledge, events, rules, relationships and human expertise.
Decide
Evaluate risk, evidence, constraints, alternatives and expected outcomes — with prediction, optimization, reasoning, simulation and retrieval.
Act
Turn intelligence into governed workflows: agents, tools, approvals, escalations, notifications and human handoffs.
Measure
Capture what actually happened — the decision, the approval, the execution, the variance and the outcome.
Improve
Use outcomes to refine knowledge, rules, models, workflows and retrieval under controlled governance.
ConstraintFlow does not stop at the recommendation. It follows the decision through the outcome.
From fragmented context to measured improvement
Most enterprise AI stops at the answer. ConstraintFlow follows the decision through the outcome.
Every recommendation, review, action and result is captured in a governed learning loop — so intelligence improves through measured adaptation, never silent self-modification.
Observe → Understand → Recommend → Human Review → Act → Measure → Learn ↺
Schedule recommended → Planner adjusts → Production runs → Variance measured → Outcome captured → Future intelligence improves.
Evidence synthesized → Scientist reviews → Hypothesis investigated → New evidence generated → Outcome captured → Research context improves.
Cross-site scheduling across an 11-plant packaging network.
Production planners manage orders across machines with different size, tooling, print and operating capabilities. ConstraintFlow runs live on this network today, evaluating eligible plants and machines, sequence-dependent changeovers, freight, capacity and customer priorities to recommend the schedule with the lowest true landed cost.
Every recommendation is tracked — accepted, adjusted or rejected, with reasons — and compared against what the floor actually executed.
- Setup time avoided
- Schedule acceptance
- Execution variance
- Throughput impact
- Customer commitments protected
Turn fragmented scientific knowledge into decision-ready intelligence.
Literature, experimental results, internal documents, datasets and institutional knowledge live in disconnected systems — while the questions research teams investigate cross all of those boundaries. ConstraintFlow brings scientific evidence, research context and governed AI workflows together, with provenance, human review and reproducibility built in.
Improve the operation without replacing the systems that run it.
Works with what you have
Keep your systems of record in place. Connects to any system — database, API, file, mainframe, and streaming; batch and real-time.
People remain accountable
Recommendations can require review and approval before they affect operations or research.
Deploy around your requirements
Support enterprise security, data isolation and customer-approved deployment patterns.
Questions leaders ask
What does ConstraintFlow do?
ConstraintFlow is an Operational Intelligence Platform. It connects enterprise data, operational context, domain knowledge and AI into one governed intelligence layer — helping teams understand what is changing, evaluate what to do next, act with confidence and learn from the outcome.
Which industries does ConstraintFlow serve?
ConstraintFlow is applied today in Manufacturing and Life Sciences. In manufacturing it runs in production across an 11-plant packaging network. In life sciences it brings scientific evidence, research knowledge and governed AI workflows together for research teams. The underlying intelligence architecture is the same; the operational models, constraints, knowledge and decisions are specific to each industry.
Does ConstraintFlow replace our ERP or MES?
No. Your existing systems continue to manage orders, inventory and production execution. ConstraintFlow uses that information to help your team make better operating decisions.
Who is ConstraintFlow for?
ConstraintFlow is built for teams in complex industries whose decisions depend on interconnected data, domain knowledge, constraints and human judgment. In manufacturing that means leaders, planners and plant teams responsible for throughput, scheduling, inventory and customer delivery — it is built first for the complexity of packaging manufacturing, and runs in production there today. In life sciences it means research teams working across fragmented scientific evidence and knowledge.
Why packaging manufacturing first?
Packaging operations face frequent order changes, machine-specific capabilities, tooling constraints, expensive changeovers — in envelope converting, a changeover can run anywhere from 2 to 21 hours depending on what changes — and demanding delivery commitments. These are exactly the conditions where better operational decisions create visible value.
What is ConstraintFlow not?
ConstraintFlow is not an MES and does not control machines. It is not a global supply-chain planning suite, and it is not built for continuous or process manufacturing. It is the decision layer above the systems you already run: it recommends, explains the trade-offs, and your team approves.
How do we begin?
Start with one difficult, measurable operating decision. ConstraintFlow runs alongside the existing process so your team can compare recommendations, build confidence and measure the result before expanding the scope.
Is ConstraintFlow only a scheduling product?
No. Scheduling was first because it is frequent and measurable — it runs in production today. The full family of Operational Intelligence Modules — Inventory, Contract, Workforce, Customer Service, Demand Planning, Guided Setup, Purchasing, and Financial Intelligence — is available for deployment on the same operational model.
How does ConstraintFlow improve over time?
ConstraintFlow records the recommendation, the planner's response, what was executed and the operational result. That feedback can be used to improve data, rules, capabilities, workflows and future recommendations under controlled governance.
Bring us one difficult operating decision.
Show us a decision your team struggles to make consistently — in the plant or in the research program. We will map the decision, the context, the constraints and the measurable outcome ConstraintFlow should improve.