PatternLab-assisted workspace activation

Activate a workspace on shared meaning.

Start with one decision worth improving and the customer data that supports it. PatternLab identifies the relevant industry model, maps the minimum useful sources into the shared Cortex semantic layer, validates the resulting meaning with your experts and configures the operational workspace and controls needed for production use.

Request activation

Tell us the decision. We configure the workspace.

One form for workspace activation and security-first assessments. No production extracts yet — company, role, and the operating decision you want to improve.

  • Assisted activation on the operational cortex — not a self-serve upload wizard.
  • We map the minimum useful sources into shared meaning before any sensitive data moves.
  • One plan, one solver — every team's answer agrees once the workspace is live.

Prefer email? support@patternlab.ai

Activation request

We reply from support@patternlab.ai. Typical first reply within one business day.

Explore the live demo

No commitment. Do not attach production extracts to this request.

Choose the right activation level

A preview is not an activated workspace.

Cortex is the shared operational semantic layer. Each workspace is configured with PatternLab around an operating decision; this is an assisted activation process, not a self-serve workspace builder.

Five-minute resultSample / template

A rapid output from a standard template or sample data. Useful for seeing the shape of the model and a decision; assumptions remain unvalidated.

PatternLab-assistedCustomer model and workspace mapping

Your exports and documents are mapped with domain experts. Identities, conflicts, rules, missing evidence and the first workspace workflow are reviewed.

GovernedProduction workspace operation

Approved mappings, integrations, roles, audit, monitoring, versioning and change control support operational use.

Assessment agenda

Begin with the decision, not the upload.

01Outcome and decision

Which operational decision should improve, and who acts on its answer?

02Semantic model fit

Which ready-made industry objects, relations and rules apply—and what is genuinely specific?

03Customer source landscape

Which systems, files and documents hold evidence for that decision?

04Mapping and identity

How will records become stable operational objects on the shared layer without losing lineage?

05Workspace configuration

Which views, workflow steps and human controls turn the shared model into an operational workspace?

06Validation and operation

Define the model, decision proof, workspace result, human authority and controls required to run it.

Security before data

For pharma and multi-plant, review first. Upload later.

Do not send production extracts with the initial request. Start with system names, data categories and a description of the first workflow. We will establish transfer, access, environment, retention, deletion, residency and approval requirements before any sensitive data moves.

Data minimization

Only what proves the workflow

Begin with schemas, metadata or synthetic examples; request record-level evidence only when necessary.

Regulated use

Human authority stays explicit

AI proposes. Rules and solvers validate. People approve high-impact decisions. GMP release remains a human decision.

Multi-plant

Scope identity and access

Define plant boundaries, role scopes, shared objects and cross-site governance before integration.

What happens to a source

Mapped once into shared meaning. Used in the configured workspace.

AI maps your existing fields, records and documents into the shared operational model. Every mapping is reviewable, traceable and versioned. A mapping contract governs a class of source records; each individual fact retains the evidence and lineage needed to explain its use.