A demo that only works when the demo-giver drives it
It looked great in the meeting; it falls over the moment a real user tries an edge case.
Enterprise engineering
Build the AI workflow your team can operate.
When an AI idea is stuck between a promising demo and the real systems, information and decisions it has to support, Kritical engineers a working implementation with clear human approval and operating control, then hands it over with the documentation to run it.
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.
Three situations bring people to this page.
A workflow that needs to write to a business system
The moment AI output touches a real record, the consequences of a mistake change completely.
A pilot that needs an owner for incidents
Something is already running, and nobody has agreed who gets paged when it misbehaves.
What you get: a defined process, not a bigger demo.
A working demonstration is a useful starting point, but delivery needs a defined process. We identify who initiates the work, what information is used, which systems can change and who reviews the result. Assistants, retrieval workflows or tool-using automation are scoped around those requirements, with responsibility for each step recorded.
Initiator
Identify who initiates the work.
Information
Define what information is used.
Systems and actions
Define which systems can change and the responsibility for each step.
Human review
Identify who reviews the result.
Access and actions, made explicit.
The implementation uses your organisation's existing access model and keeps credentials out of prompts and client-side code. We define tool permissions, data boundaries and approval points according to the consequences of the action. For workflows that write to business systems, we include validation, duplicate prevention and a way to reconcile the result with the source record.
Why Kritical: an acceptance test for the job.
We test the workflow with representative inputs, missing data, ambiguous instructions and unavailable tools. We agree what a useful answer looks like, when a person must step in and how failures become visible.
We connect AI to your actual applications
Not a generic connector: we assess the available APIs, permissions and data model for your specific systems, including Business Central and Shopify.
Explicit approval points, not blanket automation
What can run automatically and where a person must approve is a design decision tied to the consequence of getting it wrong.
A fallback when the AI-dependent step fails
The operating model includes a way to disable or fall back from the automated step.
How it is priced, and what handover looks like.
Implementation is quoted in writing before it starts. Handover can include deployment instructions, test cases, monitoring, cost assumptions and support procedures, along with how prompts, models, retrieval sources and software are versioned and updated. The operating model needs a named owner for incidents and change approval.
First call
We confirm the workflow, the systems it touches and the consequence of a wrong answer.
Get a quote
Send the systems and constraints involved and we quote the work.
Questions before you enquire
Can you connect AI to our existing applications?
We assess the available APIs, permissions and data model. Integration scope depends on what the target systems expose and the actions you want to permit.
Will the AI make decisions without approval?
That is a design decision based on the task and its consequences. The scope identifies what can run automatically and where a person must approve or review.
Does the project include ongoing support?
Only where agreed. Implementation and operational responsibility are scoped separately, including monitoring, updates, escalation and usage costs.
What happens when the model or platform changes underneath us?
The handover documents how prompts, models and retrieval sources are versioned, so a vendor change is a planned update.
Can this write directly into Business Central or Shopify?
Yes, where the platforms' interfaces support it. We scope validation, duplicate prevention and reconciliation before anything writes to a live business record.
How is this different from just buying more Copilot licences?
Copilot is a strong starting point for tasks that already live inside Word, Excel, Outlook and Teams. Engineering work is what you need once the task involves a bespoke workflow, a business system write, or logic Copilot's built-in features don't cover.
Do you support the workflow after it's live, or is it a one-off build?
Ongoing support is a separate, explicit decision. We scope it if you want it, including who monitors the workflow, who approves changes, and what the response looks like when something breaks.
Let’s define the next step.
Tell us what you want to achieve, what you have today and when it matters.