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Data & AI

Data integration. The foundation to automate, analyze and apply AI.

We define your company's data model and unify online and offline information (ecommerce, ERP, CRM and marketing) in a secure and well-governed platform. A reliable foundation for your processes, your AI agents and your decisions.

Let's sort your details

The starting point.

Each system has its own truth.

Ecommerce, ERP, CRM, email, advertising... Each system tells a part of the story, and none completely coincides with the others.

  • The same customer appears three times, with different data in each system.
  • Each department has its own sales and customer numbers.
  • To prepare a report you have to export and cross-reference spreadsheets.
  • Automation or AI projects slow down because the data is not ready.

02 · What do we do

From dispersed data to reliable data.

Data integration starts with a clear data model and ends with information the entire team can trust.

  1. Layer 01

    Data model

    What information your business needs, where it comes from and how it relates to each other.

  2. Layer 02

    Extraction and integration

    We connect sources, online and offline, through APIs or custom developments, and transform the data so that it can be managed.

  3. Layer 03

    Data platform

    A secure, scalable and well-governed environment where information is unified and accessible.

  4. Layer 04

    Quality and governance

    Rules to avoid duplicates, validate data and define who is responsible for each source. AI Governance

03 · The single view of the customer

A client. A single token.

When it adds value, we build a single view of the customer: a single profile that brings together what each system knows about them, with proprietary data obtained with consent.

Illustrative Example

04 · What is it for?

Data ready for what's coming.

01

Automated processes

Flows that are fed with correct data, without chain errors.

Process Automation
02

AI Agents

Assistants who consult real information from different systems to respond well.

AI Agents
03

Data analytics

Dashboards and analysis that management can trust.

Data analytics
04

Agentic Commerce

Catalog, stock and prices structured and accessible so that AI agents who search and buy on behalf of clients can find and operate with you.

New uses

05 · Data integration or integrations and APIs

Connecting systems is not the same as unifying data.

They usually complement each other: integrations move data, and data integration orders data.

Appearance Integrations and APIs Data Integration This Page
AimLet systems exchange informationThat the information is reliable and useful
What are you doingSynchronize orders, stock, prices and customers between systemsModel, unify and govern data across the enterprise
So thatThe day to day operationAnalyze, automate and apply AI

06 · How we work

Step by step, starting with what matters most.

  1. 01

    Inventory sources

  2. 02

    Define the data model

  3. 03

    Integrate and unify

  4. 04

    Validate quality

  5. 05

    Incorporate new sources

What is built on your data

FAQs

About data integration.

What is data integration?

Unify the information that is distributed between different systems into a common model, so that it is reliable and can be used to analyze, automate and apply AI.

What is the difference with integrating systems via API?

An API integration connects two systems so they can exchange data. Data integration organizes and unifies the information from all of them.

Do I need a data warehouse or a CDP?

It depends on your sources, your volume, and what you want to do with the data. We define the appropriate architecture for your case.

What is the single customer view?

A profile that brings together what each system knows about a customer: online and offline purchases, contacts, conditions and behavior.

What does it have to do with Agentic Commerce?

AI agents purchasing on behalf of customers need clear and accessible catalog, stock and pricing data. Without a good database, they cannot operate with you.

How many versions of your data are there in your company?

We review your data sources and suggest how to unify them on a reliable basis.

Data Talk