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Bring us your hardest data problem
LIFE SCIENCES

Reasoning you can put in front of an auditor.

Life sciences companies need data decisions they can defend. Enterprise Digital Brain reconciles product, device, and party identifiers with the evidence and approval behind every change.

Bring us your hardest data problem
See it in action →

Suggested startData quality challenge

WHAT GETS IN THE WAY

In life sciences, a good answer isn't enough. You have to show how you got it.

UDI, IDMP, and identifier reconciliation

Product and device identifiers and registrations must agree across ERP, regulatory, and commercial systems.

HCP and HCO identity and affiliation

Healthcare professional and organization records drift, duplicate, and lose their affiliations.

Evidence and approval on every change

Every change to regulated master data needs its evidence and its approval recorded.

WHAT THE BRAIN CAN DO HERE

What the brain can do here.

Product and device identifiers, regulatory registrations, and healthcare professional and organization records must agree across ERP, regulatory, commercial, and partner systems, and every change has to be explainable. Enterprise Digital Brain understands how these records relate, continuously reconciles them, and records the evidence, confidence, and human approval behind every decision. That makes the reasoning something quality, regulatory, and compliance teams can review, and something AI can be trusted to use.

EXAMPLE

Product risk detection

Identifies products with missing compliance, documentation, compatibility, or quality information.

Offered as a challenge or pilot
EXAMPLE

Product lifecycle intelligence

Identifies products nearing obsolescence and recommends replacements or migration paths.

A likelihood with evidence and confidence. People decide.

Offered as a challenge or pilot
EXAMPLE

Account hierarchy intelligence

Discovers parent companies, subsidiaries, branches, contacts, and organizational relationships.

Offered as a challenge or pilot

Examples of what companies might use it for. 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.

PRODUCT + PARTY

Product and HCP/HCO intelligence

A medtech company can connect each device identifier to the organizations and professionals who use it, its registrations by market, and its suppliers, so a change or field action reaches the right records with its evidence attached.

Product tells you what something is. Party tells you who it matters to. Together, they tell you what to do next.

HOW IT BUILDS

How it builds.

  1. 01
    LEVEL 1 · UNDERSTAND

    Understand the business

    Product, device, and party relationships (HCP and HCO affiliations).

  2. 02
    LEVEL 2 · IMPROVE

    Continuously improve the data foundation

    Identifiers and registrations.

  3. 03WHERE LIFE SCIENCES LEADS
    LEVEL 3 · TRUST

    Build trusted intelligence

    Evidence, provenance, and decision memory for every change.

  4. 04
    LEVEL 4 · ACT

    Discover, anticipate, and solve

    Product risk detection and anticipated data gaps before submission.

Better data is the foundation. Better decisions are the outcomes.

How the four levels work →
PICK A CHALLENGE

Pick the one that matches what you are funding.

HEAL & AMPLIFY PIM / MDM SUGGESTED START

Data quality challenge

See how much resolves without a person touching every record.

You sendThe product or party domain causing the most pain, as a representative dataset.

Start this challenge All challenges →
MODERNIZE, MIGRATE & TRANSFORM

PIM and MDM data readiness challenge

See what the brain can take off the implementation before it starts.

You sendA representative sample of source data, exactly as it sits today.

Start this challenge All challenges →
AI & AGENT READINESS

Agent-ready data challenge

Test whether an agent can understand one of your most important categories.

You sendOne category you would want an assistant or agent to sell.

Start this challenge All challenges →

Bring us your hardest data problem.

Send a real slice of your data. We will reason against it in your vocabulary.

Bring us your hardest data problem