Leadership wants an AI plan and nobody owns it yet
There is pressure to have a position on AI, but no agreed process for turning that into a funded piece of work.
Enterprise engineering
Find the one AI use case worth building.
Kritical turns an AI idea into a clear decision: what it should do, what information it needs, and how you will know whether it worked. Start with a business task and the cost or constraint you want to change, and leave with a scoped, priced next step.
On this page
Choose where to start.
Jump to the part that matches the problem or decision in front of you.
Use the arrows or scroll to see every card.
The landscape, in plain words.
Microsoft frames Microsoft 365 Copilot as an assistant that works with permitted Microsoft Graph data inside Microsoft 365 applications, with agents and automations available for additional use cases. Azure AI Foundry, a custom model or an on-premises deployment may suit different requirements. Kritical explains the trade-offs, confirms the applicable current product capabilities and proposes a bounded path for the workload in scope.
Three situations bring people to this page.
A demo impressed everyone and now needs to become real
Someone built a proof of concept and the gap to a production system is bigger than expected.
A vendor is pushing a platform decision
Before committing to a specific AI product or licence, you want an independent view of whether it fits the actual task.
What you get: a use case worth funding.
Start with the process, the people involved and the cost of getting the result wrong. We identify where AI can save time, where a person still needs to decide, and how you will know whether the first use case is worth expanding.
Data and delivery constraints, examined honestly.
Useful discovery considers data access, quality, permissions, system interfaces and the people who will operate the result. We compare hosted, on-premises and hybrid approaches against those constraints. Cost assumptions include integration, evaluation, support and usage growth, not just model or infrastructure charges.
Why Kritical: we decide what the pilot must prove.
A pilot needs representative tasks, expected outputs and a way to recognise unacceptable behaviour. We define the test set, human review points and the conditions for continuing, changing direction or stopping. Where the system uses tools or changes records, its permitted actions and recovery path are explicit from the beginning.
Representative tasks
Choose representative tasks that reflect the work, data and consequences the pilot must handle.
Expected outputs
Describe the expected outputs and what makes them useful enough for the next step.
Human review points
Put human review points where judgement, approval or correction is still required.
Conditions for continuing, changing direction or stopping
Agree the conditions for continuing, changing direction or stopping before the pilot begins.
Permitted actions and recovery path
Bound permitted actions and recovery path when the workflow uses tools or changes a record.
How it is priced, and what happens next.
Leave with prioritised use cases, a recommended approach, the data and integration work required and a practical pilot or implementation step, quoted in writing. We make the assumptions and open questions visible so you can decide what to fund, change or stop next.
Choose the use case
Start with a business problem, the people affected and the decision or task that should become easier.
Prepare data, access and controls
Identify the information, systems, permissions, risks and owners the work depends on before selecting an approach.
Pilot, measure and decide
Test a bounded use case, compare the result with agreed acceptance criteria and decide whether to improve, scale or stop.
Get a quote
Send the systems and constraints involved and we quote the work.
Questions before you enquire
Do we need to know which AI platform we want?
No. Start with the task and your constraints. Platform selection can form part of the assessment rather than being a prerequisite.
Can you help if we already have a pilot?
Yes. We can scope a review of its intended outcomes, architecture, evaluation and operating requirements, then identify the work needed for the next decision.
Are you selling a finished AI governance product?
This page offers consulting. Any software product, managed service or specialist governance engagement requires its own confirmed scope and readiness assessment.
Is Copilot the right starting point for us?
Sometimes. It is a credible option when the work already lives inside Word, Excel, Outlook and Teams. We check that against your actual task before recommending it.
What does AI consulting deliver if there is no code at the end?
A prioritised use case, a data and integration plan, and a scoped next step with acceptance criteria attached. Where implementation follows, that is a separate, explicitly quoted piece of work.
Let’s define the next step.
Tell us what you want to achieve, what you have today and when it matters.