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Data Readiness for AI / Plan

Good numbers in, good answers out.

AI is only as good as the data it reads. We clean up and structure your data, with a warehouse and a reporting layer where needed, so AI answers from numbers your finance team already trusts.

Book an AI Strategy CallHow it works
Laptop showing a reporting dashboard built on clean data
BEST FOR

Teams whose reports disagree, or whose data lives in exports and spreadsheets nobody fully trusts.

The short answer

What is data readiness for AI?

Data readiness for AI is the work of cleaning up and structuring company data so AI can answer from it reliably. It usually means pulling data from your systems into a data warehouse, building a reporting layer with agreed definitions, and checking the results against known numbers before AI uses them.

What you get

Data AI can answer from, and your team can trust.

Data source review

Which systems hold the numbers that matter, and how clean they are.

Data warehouse

Data pulled from your systems into one structured place, refreshed on a schedule.

Reporting layer

Agreed definitions for the figures people ask about most.

Checked against the books

Results tied to known numbers before AI or anyone relies on them.

How it works

Four steps, and a person signs off.

  1. 01

    Review the sources

    We look at where the data lives, how it is used and where it disagrees.

  2. 02

    Build the pipeline

    We move the data into a warehouse on a schedule, without touching how your systems run.

  3. 03

    Model and define

    We build the reporting layer and agree definitions with the people who own the numbers.

  4. 04

    Check and hand over

    We test results against known figures, then open them to reporting and AI.

By industry

How Data Readiness for AI looks in your sector.

Professional services

Bring hours, tickets and billing into one place for client reporting.

See the full workflow
Construction and specialty contractors

Structure past tenders, pricing and job costs so estimates draw on real history.

See the full workflow
Finance teams

Build a reporting layer on the ERP, tied to the trial balance before anyone uses it.

See the full workflow
FAQ

Questions about Data Readiness for AI.

Can't find your question? Ask it on your strategy call.

Do we need a data warehouse to use AI?

Not always. For simple workflows AI can read your files directly. A warehouse helps when answers need numbers from several systems or a lot of history.

Will this disrupt our current systems?

No. We read from your systems on a schedule and build the warehouse alongside them.

How do we know the numbers are right?

We check results against known figures, such as the trial balance, before anyone or any AI relies on them.

Is this a one-off project?

The build is a project. Keeping the pipeline running and adding sources can move to the monthly retainer.

Ready when you are

Ready to get your data ready for AI? Book a strategy call.

A free 30-minute AI Strategy Call with an AI adoption specialist. No sales pitch, just a clear look at the one workflow worth starting with.

Book an AI Strategy CallStart your AI Assessment
Free, no commitment. We reply within one business day.