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    Accelerate creating your common data model and speed up your AI transformation.

    Agentic workflows need a shared, up-to-date understanding of data across fragmented systems.

    Reduce the time spent in meetings and exchanging documents, so you can start using your data as an asset sooner.

    Neuroplastiq scans your source systems and proposes a common data model for your team to review, identifying the attributes and data elements that need to be aligned.

    Book a demoSee how it works
    Neuroplastiq's Common Data Model screen. It lists 16 entities inferred from 16 source systems at 80% average confidence, a Model Explorer with entities such as activity, business_users, catalog_items and person_records, and an AI modelling panel flagging a sales_transaction_lines identity question as review required.
    The common data model screen: entities inferred from connected sources, their definitions, and AI recommendations waiting for review.

    The problem

    The same data looks different in every system

    • Different systems represent the same customer, transaction or business concept differently.
    • Engineers dig through each source to learn how it behaves, then reconcile definitions and models that never quite match.
    • Documentation is often incomplete, or written for the people who run the application rather than the people who use the data.
    • Upstream changes need review and downstream updates.

    How it works

    A simple process to build and maintain your common data model

    Read the detail
    1. 1

      Connect your sources

      Point Neuroplastiq at the source systems you want to understand.

    2. 2

      Review the suggestions

      See proposed definitions, attributes, relationships and mappings, with the reasoning behind them.

    3. 3

      Build your common data model

      Neuroplastiq forms the canonical and semantic models, allowing your team to refine as required.

    4. 4

      Connect your platforms

      Leverage the common data model to integrate systems, populate the data warehouse and stream data.

    5. 5

      Keep it up to date continuously

      When sources change, your team reviews the proposed updates before they reach the model.

    You stay in control

    Neuroplastiq proposes. Your team decides.

    • Suggestions, not silent changes

      Neuroplastiq proposes. Your team implements or dismisses each recommendation, and the model only changes when approved.

    • Reasoning you can inspect

      Recommendations explain why they were made and what action is suggested, so reviewers can judge them on the evidence.

    • Decisions flagged for people

      Questions that need business judgement, such as which attribute identifies a record, are marked as needing review.

    How review and control work

    A Neuroplastiq recommendation titled activity to purchase, marked important. Why: both objects represent related events and share user and purchase identifiers. Suggested action: compose the source object into the candidate object. Buttons: Implement and Dismiss.
    Every recommendation shows why it was made. A person implements or dismisses it.

    What is a common data model?

    A common data model gives your organisation a shared definition of data across its systems: names, attributes, characteristics, relationships and business meaning. It provides a foundation for system integration, data analytics and AI transformation. Without that shared understanding, teams spend more time reconciling differences and have less confidence in the results.

    A common data model is also often called a canonical data model.

    How does Neuroplastiq help me build a common data model?

    Building a common data model takes substantial data engineering time. Teams need to understand their source systems, identify data attributes and relationships, and reconcile different definitions. Aligning the people around those definitions often takes further meetings and document reviews.

    Neuroplastiq provides a structured starting point: a proposed common data model that your team can inspect, refine and approve. This reduces manual discovery and gives people something concrete to review together. The sooner you agree what your data means, the sooner you can deliver integrations, analytics and agentic workflows.

    Read the Knowledge page

    See Neuroplastiq working on sample sources.

    We will walk you through the solution and understand your systems and goals to ensure we can deliver value for you.

    Book a demoSee how it works