Use-case map
Tasks, users, current cost, expected outcome and constraints.
04 / AI AUDITAI audit before hardware procurement
AI audit before hardware procurement
and major development.
We identify where AI can create measurable value, what data and integrations are required, and whether private infrastructure is justified.
01 / WHEN IT FITSUse cases that need
Use cases that need
an engineering approach
- 01
There are many AI ideas but no clear starting point
- 02
GPU procurement or platform selection is being considered
- 03
Enterprise data quality and availability need assessment
- 04
A pilot needs a defensible investment case
02 / DELIVERABLESWhat is included
What is included
in the outcome
Data assessment
Sources, quality, permissions, sensitivity, owners and readiness.
Architecture options
Private, cloud and hybrid alternatives for selected use cases.
Prototype plan
Hypothesis, examples, metrics, timeline, roles and decision gates.
03 / PROCESSFrom a hypothesis
From a hypothesis
to a verifiable system
- 01
Interviews
Meet process owners, IT, security and future users.
- 02
Process map
Record volumes, bottlenecks, error cost and available metrics.
- 03
Data review
Inspect examples, sources, accessibility, quality and constraints.
- 04
Prioritisation
Balance impact, feasibility, risk and validation cost.
- 05
Plan review
Deliver findings, requirements and an evidence-based roadmap.
04 / QUESTIONS
The essentials
Must an audit lead to implementation?
No. It provides evidence for a decision, including the option to postpone or solve a problem without AI.
Do you need all company data?
No. Representative samples and source descriptions are normally enough for the first assessment.
What makes a good first use case?
A clear owner, measurable baseline, available examples and a limited process scope.
05 / START A PROJECTStart with the task,
Start with the task,
data and outcome
In the first meeting we will review the use case, constraints and a realistic path to a measurable prototype.
Discuss a project ↗