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AI Services · Build & strategy

AI POC

An AI proof of concept exists to answer one question quickly: does this idea work well enough on our real data to justify building it properly? We scope, build and evaluate it in a short, fixed effort.

Illustration of AI POCACTUAL · FORECASTSuccess criteriaWorkingEvaluationGo / no-go
Focus
A tightly scoped proof of concept that answers whether the idea works.
Suits
Teams who need evidence before funding a build

Built around your business.

A good POC is deliberately narrow. We agree the success criteria up front, so at the end there's a clear decision rather than a demo that is hard to judge.

What we deliver.

  1. 01

    Success criteria

    The metric, the sample data and the threshold that would count as a pass, agreed before work starts.

  2. 02

    Working prototype

    The smallest end-to-end version that runs on your data, without production polish.

  3. 03

    Evaluation report

    Results against the criteria, failure examples and where the approach breaks down.

  4. 04

    Go / no-go recommendation

    A plain recommendation, with the effort and risks of taking it to production.

Where it's used.

Testing a document-understanding idea

Checking whether extraction from your real invoices, forms or contracts is accurate enough.

Validating an assistant before rollout

Seeing how a chat assistant answers real questions from your knowledge base.

De-risking a vendor decision

Comparing an approach on your data before signing a long contract.

How we work.

  1. 01

    Discover

    We agree the problem, the data available and how success will be judged.

  2. 02

    Prove

    A small, testable version on your own data shows what works before larger spend.

  3. 03

    Build

    Production engineering: integrations, safeguards, review steps and monitoring.

  4. 04

    Improve

    We measure real usage, fix what falls short and keep quality and cost in check.

Best fit.

  • Teams who need evidence before funding a build
  • Leaders comparing two or three approaches
  • Projects with uncertain data quality

Why Q3 Labs.

Senior people on the work
You work with the specialists doing the project, not a hand-off to a junior team.
Marketing and engineering together
Design, development, data and growth sit in one team, so a solution is built with adoption in mind.
Plain reporting, no lock-in
Clear progress reporting and no long-term contracts. You keep ownership of your assets and accounts.

Frequently asked questions

Talk to us about AI POC.

Tell us what you're trying to achieve. We'll tell you how we'd approach it, and whether Q3 Labs is the right fit.

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