Does Neuroplastiq replace dbt?

No. Neuroplastiq works alongside dbt, your ingestion tools and your warehouse layers. It helps your team agree what the data means; your existing tools keep doing the transformation work.

Does Neuroplastiq move data?

Neuroplastiq focuses on understanding source systems and building the common data model. Moving data is usually handled well by the ingestion and transformation tools you already run. We walk through how Neuroplastiq connects to your sources and warehouse in the demo.

How are suggestions reviewed?

Each recommendation shows why it was made and the suggested action. A person implements or dismisses it. Items that need a business decision are flagged as needing review, and the model only changes when someone approves the change.

Which platforms are supported?

Coverage depends on your source systems and warehouse. Tell us what you run when you request a demo, and we will confirm what the current release supports for your stack.

How do we evaluate fit?

Book a demo. We show Neuroplastiq proposing a common data model from sample sources, then discuss your systems, your analytics and AI goals, and whether the product fits.

How it works

From fragmented sources to a common data model your team has approved

Neuroplastiq works in five steps. People review and approve every change to the model.

Neuroplastiq's Common Data Model screen showing entity, relationship, domain and source system counts, a searchable model explorer and an AI modelling panel with recommendations needing review.

Step 1

Connect your sources

Point Neuroplastiq at the source systems you want to understand.

Neuroplastiq scans the structure of your connected source systems: their objects, attributes and the relationships between them.

We confirm which of your source types are covered, and the access Neuroplastiq needs, during the demo.

The person_records entity with attributes and types such as email_address string, created_on temporal and source_confidence decimal. — Attributes and types identified from connected sources.

Step 2

Review the suggestions

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

Each proposed entity comes with a plain-language definition and its attributes, so your team can check that the model matches how the business talks about its data.

Recommendations explain why they were made and what action is suggested, such as composing two related objects into one. Items that need a decision, like which attribute identifies a record, are flagged for review.

Duplicate or inconsistent data shows up here, along with opportunities to simplify your systems.

Entity cards with proposed plain-language definitions: activity, a time-stamped customer, vendor or system action against a marketplace; business_users, a business or vendor participant linked to a person; catalog_items, a sellable catalogue item; health, with no source business description available yet; merchant_outlets; and payout_batches. — Proposed definitions for each entity. Gaps, like an object with no source description, are shown plainly.

Step 3

Build your common data model

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

Every suggestion is a proposal. People decide whether to implement or dismiss it, and the model only changes when approved.

The result is a common data model your team has inspected and agreed, rather than a document that drifts away from how systems behave.

A recommendation to compose activity into purchase, explaining that both share user and purchase identifiers, with Implement and Dismiss buttons. — Reviewers implement or dismiss each recommendation.

Step 4

Connect your platforms

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

The common data model establishes shared definitions. The semantic layer makes that agreed business meaning available to the analytics and AI tools that consume your data.

We show the semantic model and the interfaces supported by the current release in the demo.

Step 5

Keep it up to date continuously

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

Source systems keep changing. Neuroplastiq helps your team see what changed and what it affects.

Proposed updates go to your team for review. Changes are not applied to the model without someone approving them.

Where it fits

Alongside the tools you already run

Neuroplastiq works alongside the tools you already have, including ingestion and ELT tools, dbt and your warehouse layers.
It focuses on what your data means: the shared definitions your integrations, analytics and AI tools rely on.
A common data model establishes shared definitions. A semantic layer makes agreed business meaning available to analytics and AI tools.

Source systems
CRM, billing, wallet, marketplace and other applications
Neuroplastiq
Scans sources and proposes a common data model for your team to review
Data warehouse
Where the agreed model is used by your existing tools
Integration, analytics and AI
Consumers that rely on the shared definitions

In words: your source systems feed Neuroplastiq, which proposes a common data model for your team to review. The agreed model is then used in your data warehouse by the integration, analytics and AI tools that depend on shared definitions.

Security and control

Your team stays in control of the model

Suggestions do not change your common data model. A person implements or dismisses each recommendation, and the model only changes when approved.
Recommendations show their reasoning, so reviewers can check the evidence before acting.
Questions that need business judgement are flagged as needing review rather than decided automatically.
We walk through deployment options, what Neuroplastiq can access and how AI is used, for the release being demonstrated, during your demo.

FAQ

Common questions

Does Neuroplastiq replace dbt?: No. Neuroplastiq works alongside dbt, your ingestion tools and your warehouse layers. It helps your team agree what the data means; your existing tools keep doing the transformation work.
Does Neuroplastiq move data?: Neuroplastiq focuses on understanding source systems and building the common data model. Moving data is usually handled well by the ingestion and transformation tools you already run. We walk through how Neuroplastiq connects to your sources and warehouse in the demo.
How are suggestions reviewed?: Each recommendation shows why it was made and the suggested action. A person implements or dismisses it. Items that need a business decision are flagged as needing review, and the model only changes when someone approves the change.
Which platforms are supported?: Coverage depends on your source systems and warehouse. Tell us what you run when you request a demo, and we will confirm what the current release supports for your stack.
How do we evaluate fit?: Book a demo. We show Neuroplastiq proposing a common data model from sample sources, then discuss your systems, your analytics and AI goals, and whether the product fits.

Fuller answers on 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 demo Read the Knowledge page