The AI product you keep talking about, in your users’ hands in eight weeks.
Bring us the one you're considering spending millions on. We build a working version on your data, put it in front of the people it's for, and you decide on evidence: scale it, fix it, or stop.
Say an insurer brings us claims triage. By week five, this is what their handlers are working in. A worked example; yours would be your product.
Policy active, peril covered under §4.2. Reported cause consistent with the photos and the plumber's report. Recommend settlement at £3,120 less excess. Two anomalies flagged for the handler: prior claim on the same fixture in 2024, and an invoice dated before the reported loss.
From the team behind Scene, whose client work includes
From a paragraph to a decision.
The claims build above, followed through a cycle. Your problem will be different; the shape won't.
It starts as a paragraph
You bring the idea. Together we turn it into a brief with one problem, a success measure and a stop rule, agreed in writing before anyone builds. If we can't write the stop rule, we don't start.
Then it becomes software
Working software in your environment, on your data, inside your security rules. Built like a product, not a demo: something a person can do their whole job in by week five.
Then it meets its users
Not a demo room, not a survey. We sit with the handlers, watch where it breaks, and measure what they do. The product earns its place in their working day or it doesn't.
You get numbers, not opinions
Who used it, what changed in their work, what it costs per task at volume, and what would break at scale. The evidence pack is the same shape every cycle, so decisions stay comparable.
Scale it, fix it, or stop
You decide with evidence, and everything we made is yours whichever way it goes: code, research, evaluation harness. If the numbers say stop, we say stop. It pays us the same, and the contract says a clean stop is a finished cycle. Whichever way it goes, you walk into the board with data instead of a bet.
We build AI products for a living. This is the same team, pointed at your idea.
Scene is our own AI platform, used by growth teams at enterprise companies. We carry its scars into your build.
The data that isn't what anyone said it was. The workflows nobody wants to change. The costs that only show up at volume. The features people quietly stop opening. We've hit all of it on our own product, so we know where to look first.
And we'd rather be the team you call for the next build than one you can't get out of. A stop pays us the same as a scale, so ours is the one recommendation you can take at face value.
Product
People who have owned a roadmap and a number, not a workstream.
Design and research
Adoption gets designed. We test with users, not with stakeholders.
Applied AI
Model selection, evaluation, guardrails and cost control in production.
Engineering
Built to be secured and extended, not rebuilt after the pilot.
Next to the suppliers you already use.
| Dimension | Strategy consultancy | PoC factory | Software agency | Scene.studio |
|---|---|---|---|---|
| What you get | A roadmap and a business case | A demo | The thing you specified | Working software and the evidence to judge it |
| Time to use | Months | Weeks, but not usable | Quarters | About six to eight weeks |
| Who uses it | A steering group | A room of stakeholders | UAT at the end | Your users, doing their own work |
| Built on | Benchmarks and interviews | Sample data | A requirements document | Your data and your constraints |
| What it proves | That a case can be made | That the model can do it | That it can be built | Whether it is worth scaling |
| A stop verdict | Kills phase two | Kills the next demo | Kills the build | A completed cycle, paid the same |
The deal.
Common questions
Our vendor onboarding takes longer than eight weeks.
A single fixed-fee cycle usually fits a pilot-sized purchase order or an existing framework agreement rather than full supplier onboarding, and security questionnaires run while scoping runs. If your process genuinely needs a quarter, we say so before you sign and plan the start date around it.
What happens after the cycle?
You take it in-house with a full handover, we help you industrialise it, or you stop. We'd rather be the team you call for the next build than one you can't get out of.
Our consultancy says they do validation too.
Ask them what a stop verdict costs their business. For a strategy firm it ends phase two, for an agency it ends the build, so their validation tends to conclude that building is the answer. Our fee is the same whichever way the evidence points.
Why not our internal team?
If they can ship a production-minded build in eight weeks with honest kill criteria, they should. Most internal teams are staffed for the roadmap, not for a sprint with a mandate to say no to their own executives. We're outside the politics, and that's most of the value.
We are not right for everything.
Saying so early saves us both a quarter.
Works well when
- You are weighing a significant AI investment and the case rests on untested assumptions
- There is a defined problem and a defined user group behind the idea
- Someone senior can make the call on the evidence
- A small team can get to your data and your users within a few weeks
Not for us
- The decision is made and you need it supported on paper
- You want an enterprise wide AI strategy or an operating model design
- You want a fixed spec build of something already agreed
- Nobody is able to stop it if the evidence says stop
Tell us the one you'd most like to know the truth about.
One paragraph: the idea, who it's for, roughly what it's worth. We'll tell you within a week whether it's worth a cycle, and if it isn't, we'll say that too.