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CogniverseAI

Technology · Trusted data foundation

Cogni-Data

Build the trusted data foundation that reliable analytics and AI require.

Overview

Your data is fragmented, and nobody fully trusts it.

Sales lives in the point-of-sale system, costs in the ERP, customers in three spreadsheets. Reports disagree, reconciliation eats analyst time, and any AI built on top inherits every gap.

Every decision rests on data, and most enterprise data is spread across systems that were never designed to agree with each other. Cogni-Data is how CogniverseAI brings that data together, makes it consistent and governed, and gives it the business context a decision needs.

The question it answers: Can we trust the data?

How it works

How Cogni-Data works.

Build the trusted data foundation that reliable analytics and AI require.

ERPPoint of saleFiles & APIsOperational systemsIoT & devicesPipelinesETL · ELT · reconciliationwarehouse · lakehouseRawCleanedBusiness-readyQuality rulesCatalog & lineageMaster dataReporting, AIand decisions

What Cogni-Data covers

Inside Cogni-Data.

Trusted data foundation.

  1. 01

    Integration and pipelines

    Connect operational systems, ERPs, point-of-sale and files into one governed flow, on a schedule the business can rely on.

  2. 02

    Warehouse and lakehouse

    A layered store that separates raw, cleaned and business-ready data, so every number has a traceable origin.

  3. 03

    Quality and governance

    Rules that catch missing, duplicated or inconsistent records before they reach a dashboard or a model, with clear ownership.

  4. 04

    Master data and business context

    One definition of a customer, a product, a site or a supplier, and the metadata that tells a person or a model what a field means.

For architects: how it is built
  • Dimensional and lakehouse modelling (bronze, silver, gold layers) on SQL Server, cloud warehouses or open-table formats
  • ETL and ELT pipelines from SAP, point-of-sale, ERP and flat-file sources with idempotent loads and reconciliation checks
  • Data quality rules, lineage capture and a governed data dictionary that the semantic layer and CogniGraph consume
  • Deployment in the client's own cloud or on-premise environment; the client owns the data and the platform

In short

  • Dimensional and lakehouse modelling (bronze
  • ETL and ELT pipelines from SAP
  • Data quality rules

Services

Services that build Cogni-Data.

The layer is delivered inside an engagement, in your environment, and handed over to your team.

What changes

Reports that agree with each other, analysts who spend their time on analysis, and an AI programme that starts from data it can trust.

Ready to turn enterprise intelligence into better decisions?

Let's identify where data, AI and orchestration can create measurable value in your organization.

  1. 01

    Send a message

    Tell us what you are trying to decide and what your data looks like today.

  2. 02

    A 60-minute conversation

    Where your decisions are made today, what they rest on, and where the gaps are.

  3. 03

    A written summary you keep

    What we heard, what we would look at first, and what an engagement could look like.