Pluscode
Sprint

Prove your AI use case in 2 weeks

Two weeks on one use case with your real data: feasibility tested, a working prototype, and a costed roadmap. You commit budget to evidence, not to a pitch.

2 weeksRemote, embedded with your teamFixed scope, fixed feeTeams ready to prove one use case
Book the sprint

What the sprint is

The sprint takes one use case and answers the only question that matters before you fund a build: will this work on our data, and what will it cost in production? Senior engineers work on it full-time for two weeks, from data audit to working prototype, with a few hours a week from your domain expert.

Week one is evidence: we map your data, access, and constraints, test the risky assumptions first, and design the production architecture. Week two is the prototype: built on your real data against agreed success criteria, demoed as it grows rather than revealed at the end. You see progress midway, not just at the finish.

You end the sprint with a decision, not a feeling. Go means a prototype that already works, an architecture, and a costed roadmap the next phase executes. No-go means you saved the build budget and know exactly why: which data, constraint, or accuracy bar failed, and what would have to change.

What you leave with

A technical feasibility assessment grounded in your data, not in benchmarks
A working prototype on your real data, demoed and in your repo
Agreed success criteria and how the prototype scored against them
A production architecture proposal with model and hosting choices
A costed delivery roadmap for the build phase
A clear go or no-go recommendation with the reasoning
Sprint

How the sprint runs

01

Scope and success criteria

Day one fixes the scope: one use case, the data it needs, and what 'it works' means in numbers. Everything in the sprint is measured against that definition.

02

Data deep-dive

We map your data sources, access paths, quality, and constraints, including privacy and compliance. Most AI projects die here, so we go here first.

03

Kill the risks

We test the riskiest assumptions before building anything polished: retrieval quality, model accuracy on your edge cases, latency, cost per query. Cheap experiments first.

04

Build the prototype

We build a working prototype on your real data against the agreed criteria, and demo it during the sprint so course corrections happen early, not after the fact.

05

Decision and roadmap

We close with the evidence: how the prototype scored, the production architecture, a costed roadmap, and a clear go or no-go recommendation you can take to your board.

Who it's for

You have one use case worth proving, ideally from a workshop shortlist
You want evidence before funding a production build
You have data and can grant access within days
You have a decision-maker who will act on the result

How to prepare

The sprint starts fast when access and people are lined up before day one.

Read access to the relevant data before day one
One decision-maker for scope calls and the final decision
A domain expert for a few hours each week
NDA and data-processing agreement signed, if you need them

Questions, answered

What do you need from us to start?

Access to the relevant data, one decision-maker, and a few hours a week from a domain expert. We handle infrastructure, tooling, and the build. An NDA and a data-processing agreement are standard before day one.

Is two weeks really enough?

For one scoped use case, yes. We go deep on a single problem, not broad across many. The prototype proves feasibility and cost, not the full product: that is what the build phase is for.

What if the prototype shows it will not work?

That is a valuable result, and the cheapest possible way to learn it. You keep the analysis, know exactly which constraint failed, and get alternatives worth testing. The build budget stays in your pocket.

Do we own the prototype and code?

Yes. All code, findings, evaluation results, and the roadmap are yours, in your repositories. If you proceed to build, with us or in-house, it is your starting point.

What does the sprint cost?

A fixed fee for a fixed scope, agreed before we start. No day rates and no running meter. The proof-of-concept phase, if you go there, is quoted in the roadmap, so you see the full cost picture before committing.

Do you have an incentive to recommend go?

The recommendation comes with the evidence attached: eval scores, costs, failure cases. You can check it yourself. A no-go costs us a build project, a wrong go would cost us the relationship, and the second is worth more.

Where this leads

A go decision deserves production proof. The GenAI proof-of-concept turns the prototype into a production-grade pilot on your data, measured on real evals, ready for rollout.

GenAI Proof-of-Concept

Book your Discovery Sprint

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What you're booking
2 weeks · Remote, embedded with your team · Fixed scope, fixed fee
  • A technical feasibility assessment grounded in your data, not in benchmarks
  • A working prototype on your real data, demoed and in your repo
  • Agreed success criteria and how the prototype scored against them
  • A production architecture proposal with model and hosting choices
  • A costed delivery roadmap for the build phase
  • A clear go or no-go recommendation with the reasoning
What happens next
  1. 1We match you with the right engineer.
  2. 2You hear back within one business day.
  3. 3A 30-minute call to scope it.
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