Service · Data readiness
G5Data Readiness for AI.
Every AI build depends on data. Most fail because the data isn't ready. In three to five weeks we assess quality, access, structure, and residency, and hand you the fix plan that unlocks the build.
Outcomes
What changes when the engagement lands.
Honest data readiness read
Whether the data supports the AI use cases you have in mind. Yes, no, or with fixes.
Prioritised fix plan
The specific data fixes required. Ranked by which use cases they unlock.
Residency and access clarity
Where the data lives, who can touch it, and what that means for build options.
A defensible position for the AI investment
The CFO can see whether the build is worth committing to given the data state.
Deliverables
What's in the engagement.
A three- to five-week assessment of whether your data is ready for the AI you're planning to build or buy. Quality, access, structure, and residency all assessed, with a defended fix plan.
Readiness assessment
Data quality, access, structure, and residency scored against the planned AI use cases.
Fix plan
Prioritised data fixes with effort and expected outcome.
Residency and access review
Detailed picture of where data lives, ownership, and access constraints.
Go / no-go recommendation
Whether the planned AI investment is currently feasible given data state.
How we deliver
Fixed scope. Named phases. Duration on the cover.
The engagement is priced against the outcome, not open-ended hours. Every phase has a duration, a named deliverable, and a check-out.
Total duration3 to 5 weeks
Sales cycle3 to 6 weeks
- 01Week 1
Scope
Planned use cases reviewed. Data sources identified.
- 02Weeks 2 to 4
Assessment
Data samples analysed. Access mapped. Residency clarified.
- 03Week 5
Fix plan and read-out
Fix plan documented. Read-out delivered.
Built for
Buyers this engagement fits.
Typical buyer
Chief Data Officer, CTO, Head of Analytics
Chief Data Officers planning an AI build
Before the build starts, the data has to be ready. Confirm it before you commit.
CTOs whose team is optimistic about training data
The team says the data's fine. This gives you the outside opinion before the pipeline starts.
Businesses whose last AI build was blocked by data quality
You know the pattern. Don't repeat it. Start with the readiness read.
Related services
Where this leads next.
Fine-Tuning Feasibility & Data Readiness
Fine-tune vs RAG vs prompting. Data audit. Base model shortlist. Costed build proposal.
Document & Dataset De-identification
Batch de-identify a corpus. Key management. Validation sampling. Safe for analytics, RAG, or training.
AI Roadmap
Sequenced build, buy, or train plan tied to return and readiness. Phased with costs.
Talk to us.
45 minutes on your operation and the engagement you have in mind. No pitch, no deck.
Lead intake
Request a briefing
A 45-minute call. No pitch, no deck. We ask the questions we'd ask a Discovery client and tell you honestly whether this is the right next move.