Data readiness
Prepare your data for artificial intelligence
We turn fragmented spreadsheets, documents and business systems into a governed foundation for AI, analytics and automation.
Discuss your project →What this service solves
AI does not automatically repair inconsistent data. We identify sources, owners, critical fields, quality rules and permitted use cases before implementation.
- Source and data-flow audit
- Cleaning, deduplication and standardisation
- ETL/ELT pipelines and integrations
- Catalogue, access roles and quality controls
What your team receives
You get a clear data map, remediation priorities and a technical foundation for agents, BI or predictive models without recurring manual consolidation.
How we start
We assess the challenge and available sources, agree quality criteria, select one practical pilot scenario and scale only after it has been validated.
Fit before scope
Is this the right starting point?
Use these criteria for an initial orientation. The final recommendation follows a review of your context, data and constraints.
A good fit when
- A specific AI, analytics or integration use case exists
- At least the main sources and accountable roles are known
- The team can validate quality and agree control rules
Resolve this first when
- There is no lawful basis or permission to access the data
- The decision the data should support is undefined
- Only a one-off file correction is required without an ongoing control process
A verifiable first stage
What you can use to make the next decision
The exact scope is agreed before work begins. These are typical decision artefacts, not promised business results.
Source and ownership map
Systems, datasets, accountable owners, access paths and critical dependencies.
Data-quality profile
Observed completeness, consistency, freshness and duplication issues.
Preparation roadmap
Prioritised fixes, control rules and a readiness decision for an AI pilot.
Five questions · no datasets or credentials
Online tool
Assess your data readiness in a few minutes
Five questions identify priority actions without sending your answers to a server.
Start assessment →Frequently asked questions
Frequently asked questions
Do all data need to be migrated?
No. The architecture follows the audit: some sources can remain in your environment and connect through agreed interfaces.
Can we start with one process?
Yes. A bounded pilot tests both data quality and business value before a larger implementation.
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