{{ quoteLabel }}“Our PIM or MDM works, but too much effort still happens around it.”
Continuously monitor and improve the data, models, mappings, rules, and processes around existing PIM and MDM investments — without replacing them.
When the data, models, mappings, rules, or processes around the platform have degraded or are still too manual. The brain monitors them continuously, runs the routine cleansing and stewardship inside your policy, and sends only the exceptions to a steward, with the evidence attached.
When the platform works and the business wants much more from it. The brain adds the understanding the platform was not built to hold, such as compatibility, relationships, and account hierarchies, and writes governed results back.
Either way, the platform stays where it is.
Pick a problem to read more.
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Reads from the PIM, MDM, ERP, and commerce platforms you already run, connects what each one holds, and monitors the data, models, mappings, and rules around them.
Proposes classification, normalization, enrichment, and matches with evidence and confidence, decides what can run inside policy, and adds the understanding those systems were not built to hold: compatibility, relationships, account hierarchies, and the reasoning behind decisions.
Runs routine work continuously, sends exceptions to a steward with the evidence attached, and returns governed results through each platform's own interfaces where integrations permit, so your teams keep working where they work today.
And it learns from every decision, so the next similar case needs less human work.
Your PIM and MDM stay the system of record. The brain builds the understanding they were not designed to hold and writes governed results back. Which systems and connection methods are supported is confirmed per engagement.
See what the brain can take off the implementation before it starts.
You sendA representative sample of source data, exactly as it sits today.
See how much resolves without a person touching every record.
You sendThe product or party domain causing the most pain, as a representative dataset.
The next assortment you are about to launch, before your team starts working through it.
You sendOne new supplier, category, or channel you are about to onboard.
A few examples of what companies might use Enterprise Digital Brain for here. They are possibilities, not a closed list or the core offering, and each is offered as a challenge or a pilot on your own data.
Moves beyond a golden record to an understanding of the whole relationship.
Offered as a challenge or pilotShows where a customer, supplier, or account sits in its relationship with the business.
Offered as a challenge or pilotDetermines which customers and accounts should receive attention, from context and business rules.
Offered as a challenge or pilotIdentifies which products, parts, accessories, components, and consumables work together.
Offered as a challenge or pilotIdentifies what a PIM, MDM, ERP, or commerce platform upgrade changes in schema, attributes, rules, and integrations, and carries the data forward so the upgrade does not stall on data.
Offered as a challenge or pilotAdd understanding and decisions around it instead of replacing it. Enterprise Digital Brain works over the PIM, MDM, ERP, and commerce platforms you already run, adding context those systems were not built to hold, such as compatibility, relationships, and account hierarchies. Only 29% of companies surveyed have full upstream and downstream MDM integration (McKinsey, May 2024).
Because a PIM is built to store, govern, and distribute product records, not to decide what the data should be. Reading supplier files, mapping to your taxonomy, normalizing units, filling gaps, and handling exceptions still fall on people. 82% of large organizations surveyed spend one or more days a week resolving master data quality issues (McKinsey, May 2024).
Move routine decisions into a governed layer and keep people on the exceptions. Enterprise Digital Brain is designed to run onboarding, cleansing, enrichment, and matching continuously inside the policy you set, send low-confidence or high-risk cases to a steward with the evidence attached, and learn from each reviewed decision. Measure it against a baseline: human review, first-pass acceptance, and time-to-ready.
A golden record tells you what is true about one party. It does not tell you how that party relates to others: the parent company, the sites, the suppliers behind a line, the equipment an account runs. Customer and supplier 360, an example solution, moves from the record to that understanding.
Assortment optimization, an example solution, surfaces missing products, redundant SKUs, and gaps against what customers are trying to do, each as a recommendation with its evidence. The Assortment expansion challenge runs it on one category.
Bring one workflow around the platform you already own. We will show what the brain adds, and what it writes back.