One semantic layer. Multiple operational workspaces.
PatternLab Cortex gives complex manufacturers an operational semantic layer: one shared understanding of products, processes, orders, materials, capacity and time. PatternLab then helps configure governed workspaces for the recurring operational decisions that use that meaning.
ERP, MES, spreadsheets, records and documents retain source, time and lineage.
Products, processes, orders, materials and resources connect through common relationships and rules.
Roles, evidence, validation and approvals are configured around a recurring operational responsibility.
Teams produce a feasible plan, lower-cash inventory position, reliable promise or another governed result.
Supply Chain is one workspace. Plan, Inventory and Sales are its views.
The live Supply Chain workspace applies the shared semantic layer to connected planning decisions. A changed promise alters demand; demand changes the plan; the plan changes material and inventory needs; the resulting availability changes what Sales can promise next.
Test and commit dates against the same model used to plan.
Re-solve production when orders, supply or the floor changes.
Recalculate shortages, policy and cash from the new plan.
Your systems store records. Operations runs on meaning.
An ERP field can say “item,” a schedule can say “job,” and an SOP can describe a forbidden transition. Decisions fail when those facts are never connected. Cortex gives each fact identity, relationships, effective dates and evidence—then derives the operational consequences.
Start from shared meaning. Configure the work around it.
PatternLab works with your team to map existing fields, records and documents into the shared operational model, then configure each workspace around its users, decisions and controls. AI assists the mapping; every mapping is reviewable, traceable and versioned. This is an assisted activation path, not a self-serve workspace builder.
Reuse operational meaning
Start with stable identities, relationships, rules, time and evidence instead of rebuilding context for every workflow.
Shape a governed workspace
PatternLab helps define the views, decisions, roles, validation and approval paths for the operating team.
Put meaning to work
Use the workspace to produce a feasible plan, a lower-cash inventory position, a reliable promise or another governed operational outcome.
A change travels. Control travels with it.
A supplier slip, yield change or rush order propagates through the shared model to affected plans, stock positions and promises. AI proposes. Rules and solvers validate. People approve high-impact decisions. Every accepted change retains lineage and an audit trail.
The new fact retains its source, timestamp, identity and effective period.
Rules derive the blast radius; solvers test feasible responses across the connected workspace.
Low-risk updates can flow automatically; high-impact decisions wait for the right role.
Industry physics, visible in the decision.
See live models handle grade yield in shrimp, make-readies in folding carton, production wheels in FMCG and validated transitions in Pharma OSD. Poultry and non-OSD pharma are clearly labeled design-partner coverage. The proof is not a generic chatbot—it is the changed operational decision and the evidence behind it.
Judge the model by a transparent chain.
We do not substitute hypothetical ROI or unnamed client claims for evidence. Every sample proof uses the same six-part structure.
Named sample files, records, documents and assumptions.
PatternLab-assisted sample mapping or a governed production deployment.
Objects, identities, relationships, rules, time and lineage.
The plan, inventory position or delivery promise affected.
Measured output, clearly labeled as sample—not client performance.
What AI proposed, what validation proved and what a person accepted.
Explore the live reference—or activate an assisted workspace.
Supply Chain workspace
Use the live Plan, Inventory and Sales views on a pre-modeled plant.
A workspace for your operation
Map your data into the semantic layer, configure the workflow with PatternLab, then deploy with production controls.