AI readiness assessment
In an AI readiness assessment, we look at your data, processes, systems and risks to find the use cases that are both valuable and feasible today. You get a prioritised shortlist with the reasoning, dependencies and risks behind each item.
What it is and when it fits
An AI readiness assessment is a short, structured engagement. We interview people across the business, review the processes where time goes, inspect the systems and data those processes depend on, and look at security, privacy and compliance constraints. The result is a ranked set of use cases, each with expected value, feasibility, data gaps and risks spelled out.
It suits organisations that feel pressure to do something with AI but lack a shared view of where to start, or that have many ideas and no way to compare them. If you already know the process you want to automate and the data is in place, you can go straight to building. We will say so in the first conversation.
What we build
Process and pain point inventory
A map of where time, errors and delays sit in your key processes, based on interviews and real work samples.
Data and systems review
An assessment of data quality, accessibility and APIs in the systems each use case would depend on.
Risk and compliance scan
Privacy, security and EU AI Act considerations per use case, including where human oversight is required.
Prioritised use case matrix
Use cases scored on value, feasibility and risk, with a short description of what each would involve to build.
Leadership readout
A session with your management team to walk through findings, challenge the ranking and agree next steps.
How it works
- 01
Interviews and discovery
We talk to people in operations, IT, finance and leadership to understand goals, workloads and constraints.
- 02
Hands-on review
We look at real documents, data exports and system access, because feasibility depends on details that slides do not show.
- 03
Score and prioritise
We rate each use case on value, feasibility and risk together with your team, so the ranking reflects shared judgement.
- 04
Report and readout
You receive a written report and a working session to agree which use cases move forward and what they need.
Built with
All technologiesA guide to start with
Further reading
Human-in-the-loop AI agents: design patterns for real operations
How we keep a human in the loop when AI agents run on live systems: approval checkpoints, confidence thresholds, tool permissions, audit trails and fallbacks.
5 min read
RAG vs fine-tuning: which one do you need?
RAG gives a model your knowledge at answer time; fine-tuning shapes its behaviour. How to choose, when to combine them and what each costs.
4 min read
Common questions
Mostly interviews of an hour or so with a handful of people per department, plus someone in IT who can give us access to data samples and system documentation. We plan the sessions around your calendar.
No. Part of the assessment is finding out which data is usable today, what needs cleaning and which use cases can start with the data you already have.
No. The report is yours and written so any capable team can act on it. If you want us to build the first use case, we already know the context.