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Bring us your hardest data problem
How it works

Reasoning-first architecture for product and party data.

Enough architecture to judge whether this is real: five layers, a set of collaborating agents, decision memory that persists, a policy that decides what runs without you, and how it all works over the systems you already own.

Bring us your hardest data problem
Architecture

Works over what you own, not instead of it.

  1. 4

    Outputs

    Governed write-back into your systemsAPIs for applications and channelsContext for agents and assistantsReview tasks for people
  2. Cogentric Enterprise Digital Brain
    1. 3

      Governance and trust

      EvidenceProvenanceConfidencePolicyHuman reviewDecision history
    2. 2

      The brain

      Understand · Reason · Act, and learns from every decision.
      01Understand the businessKnowledge and context
      02Continuously improve the data foundationOntology, MDM architecture, monitoring and improvement
      03Build trusted intelligenceCognitive reasoning, confidence, provenance, and decision memory
      04Discover, anticipate, and solveAgent orchestration

      Decision memory: rules, mappings, exceptions, decisions, and provenance. Yours, and independent of any single model or platform.

  3. 1

    Your systems

    They stay the system of record.

    PIM / PXMMDMERPCRM and commerceSupplier feeds, files, and spreadsheetsPDFs, manuals, and documentsData platforms and warehousesApproved external sources, only where your policy allows
Works over what you own

Start with what you already have.

Cogentric Enterprise Digital Brain works around the systems you already run.

  • Your PIM and MDM stay the system of record.
  • Your ERP stays the source of truth for items.
  • Your commerce and CRM platforms keep doing their jobs.

The brain reads from them, builds the understanding they were not designed to hold (meaning, relationships, rules, and decision history), reasons over it, and returns governed results into the systems where your teams already work.

And if it's not in those systems, the brain creates and enhances the data it needs.

Start small. Compound intelligence. Unlock what’s next.

  1. 01 · PROVE

    Start with one hard data problem

    Examples

    Cleanse product data, match customer records, enrich supplier data, resolve duplicates.

  2. 02 · OPTIMIZE

    Expand from a task to a process

    Examples

    Automate supplier onboarding, continuously improve product data, streamline master-data stewardship.

  3. 03 · SCALE

    Power the next business initiative

    Examples

    AI readiness, PIM/MDM modernization, commerce transformation, new channel launch, ERP migration.

  4. 04 · ANTICIPATE

    Discover what the business should do next

    Examples

    Predict product gaps, identify hidden cross-sell opportunities, flag supplier risk, anticipate service needs.

Agent collaboration

Specialized agents, one shared knowledge base.

Agents do not each keep their own copy of the truth. They collaborate around the same ontology, rules, and memory.

Policy and confidence

Confidence and your policy decide who acts.

Advise, by default.

The brain recommends, with its evidence and confidence. A person decides.

Act inside policy.

Where your policy allows it, the brain acts and records what it did, why, and on what evidence.

Owner decides.

When confidence is low or the decision is consequential, nothing moves until a named owner rules on it. The ruling becomes precedent. It becomes policy when an owner approves it.

Questions architects and platform owners ask

Every decision shows its sources, its confidence, and its reasoning path, along with the rules applied and who approved it. In the demo, a decision reads, for example, confidence 0.92 (Illustrative example, demo values).

The correction becomes intelligence. A reviewer corrects the decision, the brain records why, and it applies that reasoning to the next similar case. Every decision is recorded and reversible; the brain learns from corrections, but governed rules never change without visibility and traceability.

Only where your policy allows it. Anticipations and recommendations advise by default; actions wait for approval unless policy lets the brain act, and consequential decisions go to a named owner. The thresholds are yours to set.

The brain shows the conflict instead of hiding it. It weighs source authority, recency, your rules, and past decisions, adjusts its confidence, and escalates to a reviewer when the conflict matters.

Enterprise decision memory is the record of why each data decision was made, on what evidence, and when to reuse it. Enterprise Digital Brain keeps it with the customer, so it survives a model change, a platform replacement, or a person leaving. The model is replaceable. The accumulated understanding of the enterprise isn't.

The graph is part of how the brain remembers and reasons, not the outcome. Enterprise Digital Brain uses an ontology and a graph of products, parties, and relationships to perform governed data work, apply your rules, and keep the reasoning behind each decision.

It's an agentic data intelligence platform, not a general-purpose agent builder. Enterprise Digital Brain builds, orchestrates, and governs AI agents for enterprise data, and it arrives with specialized intelligence for PIM, MDM, data quality, product data, party data, and transformation, so you start with solutions rather than a blank canvas. Its agents act inside your policy, with the evidence and confidence behind every decision.

Usually no. The brain is designed to work around the PIM, MDM, ERP, and commerce systems you already own and to write governed results back through them. Replacing a platform can be a separate decision; it is not required to get value from the layer.

No. A PIM is a system for managing product records and distributing them to channels. Enterprise Digital Brain works around the PIM you run, creates and improves the intelligence that feeds it, and writes back through it, while the PIM stays the system of record.

Not by default. MDM remains the system of record and the governance foundation. Enterprise Digital Brain performs the matching, enrichment, relationship discovery, and exception work around mastering, and writes governed results back.

No. It takes on the repetitive work around the PIM so the team can own standards, policy, and the hard decisions. PIM and MDM owners become the governors and teachers of the brain.

A system of record such as a PIM, MDM, or ERP stores, governs, and distributes the decisions people have made about data. An intelligence layer does the work of deciding: it classifies, enriches, matches, and reconciles data across those systems, shows its evidence, and writes governed results back. PIM and MDM manage the record. Enterprise Digital Brain does the work around it.

A PIM manages product records, workflow, and syndication to channels. An MDM masters core entities such as customers, suppliers, and products and governs the golden record. An intelligence layer such as Enterprise Digital Brain works across both, doing the classification, enrichment, matching, and exception work around them and writing governed results back; it replaces neither.

Bring us your hardest data problem.

Bring the systems, the volumes, and the constraints. We will walk the layers against them.

Bring us your hardest data problem