AI-assisted engagement & delivery
AI carries the work between the conversations. A named nVisionIT person owns every commitment we make to you.
Our engagement model has not changed: a conversation about the outcome you want, a Sprint 0 that puts something real in front of you, delivery in two-week milestones, and a relationship that continues past go-live. What has changed is the engine underneath it. Three systems we built and own now carry the work that used to consume the weeks between those conversations, which is why Sprint 0 ends with a running prototype in weeks rather than a document pack in months.
The slow part of a project was never the building
It was the months spent discovering what the requirement actually was, and the change requests that arrived once the gap surfaced. We put AI to work on exactly that part, and left the human judgement where it belongs.
What it fixes
- Requirements that look complete until month three → gaps surfaced in the first conversation
- A discovery phase that produces documents → a working prototype at Sprint 0
- Change requests as the default commercial model → milestone acceptance, then invoice
- AI used quietly, with no one accountable → a named human owner on every deliverable
Three systems we built, own and run
You are entitled to know what is doing the work on your engagement, and to ask what it was allowed to touch.
Intelligence Hub
Our governed knowledge and decision engine. It checks your stated objectives against best practice and against our own delivery record, and every answer it gives cites its source. Where an answer came from AI, it is labelled as such. The Hub informs a decision; it never makes one.
The Hive
Our AI delivery orchestrator. It turns confirmed objectives into user stories, surfaces the requirements the conversation missed, and drives the build inside the sprint discipline. It is how we add delivery capacity without adding headcount, and without adding the coordination cost that usually comes with it.
nVisionIT.Framework
Our build platform. It generates the working proof of concept you approve at the end of Sprint 0 on a base we already own and maintain. The prototype you sign off becomes the foundation production is built on.
What happens, and what you sign
The shape of the engagement is the same one we have always run. Each phase below shows what the engine does, and the point at which a person, yours or ours, puts their name to something.
- Initial discovery, made rigorous
A conversation about the outcome you want. Behind it, the Hub checks every stated outcome against best practice and our governed delivery record, and the Hive turns the picture into user stories and flags what the conversation missed. The loop runs until the requirements are stable. You sign the confirmed objectives before anything is built. - Sprint 0, ending in something that runs
The Framework builds a working proof of concept from the signed requirements, alongside the costed roadmap, prioritised backlog, target architecture and success metrics. Our engineers review and shape it before you ever see it. You approve the prototype, and that approval is the exit from Sprint 0. - Iterative delivery in two-week sprints
Plan, build, demo, deploy, retro. The Hive drives development, AI-written tests ride every build, and our QA reviews each milestone before it is demonstrated. You accept each milestone demo, and only accepted milestones are invoiced. Pivot at any milestone boundary. - Ongoing value review
Go-live is not a handover. The Hub tracks outcomes against the objectives you signed at the start, and what we learn feeds back into the governed record for the next engagement. You sign user acceptance and go-live before anything reaches production.
The non-negotiables
No AI output crosses a commitment boundary without a named human act. A skipped gate is logged and investigated as an incident.
You sign the requirements
Before a line of the solution is built, you approve the confirmed objectives in writing.
You approve the prototype
Sprint 0 does not end, and delivery does not start, until you have used the working proof of concept and said yes.
You accept each milestone
Acceptance precedes invoicing, every sprint. Rejections and the rework they cause are visible in the next sprint record.
We review before you see it
A standing internal rule: every AI-generated artefact is reviewed and approved by a named engineer or consultant before it leaves nVisionIT.
You sign go-live
User acceptance testing is yours to run and yours to sign, before anything reaches production.
One named owner, always
Every deliverable carries the name of the person who reviewed it, approved it and is accountable for it. You can ask who, at any point.
Three layers, three different owners
Self-testing delivery is a claim worth being specific about, so here is what it actually means on your engagement.
Tests written with the code
AI generates tests alongside every build and they run in the pipeline on every commit. Our engineers review them. A generated test only counts once it executes and passes.
Human QA before the demo
Our QA reviews each milestone before it is shown to you. This is a person, every sprint, and it happens whether or not the pipeline is green.
Your acceptance testing
You test against the objectives you signed, before go-live. Test suites, review records and UAT results are filed on your engagement record.
What governs the AI on your engagement
Our Responsible AI Use Policy applies to every stage above. The short version is on this page; the policy itself sets out the controls, and we will share it with you.
See it on your own problem
Bring us an outcome you want and we will run the first conversation properly: your objectives checked against best practice and our delivery record, with the gaps surfaced while you are still in the room.