Grapefruit

Fixed-scope offer · 3 to 4 weeks

AI Prototype Sprint: a working AI proof of concept in 4 weeks

The AI Prototype Sprint is a 3 to 4-week, fixed-scope AI proof of concept. Grapefruit agrees success metrics and an evaluation set with you, builds a working prototype on your own data in your cloud tenant, and measures accuracy and hallucinations. You get a go/no-go recommendation and a production estimate.

No obligation to continue. We reply within 1 business day, usually the same day.

The promise

A working AI prototype on your own data in 4 weeks, so you decide with evidence, not slides.

Duration
3 to 4 weeks
Scope
Fixed, agreed before we start

Who it is for

Is the AI Prototype Sprint right for you?

Product owners, heads of digital and innovation teams who already picked a use case and need proof before funding a build.

A good fit when

  • You picked a use case and need evidence before funding a build
  • A previous pilot looked good in a demo but nobody measured whether it was accurate
  • Legal, security or IT need to see how data flows before they approve

Not the right first step when

  • You are still deciding where AI fits: start with the AI Opportunity Scan
  • You want a production system in 4 weeks without evaluation

Week by week

How the work runs

  1. Week 1

    Frame and measure

    We define the use case, the users, what good looks like and the evaluation set of real examples the prototype must pass. Access to data and cloud is set up.

  2. Week 2

    Build the first version

    A first working version runs on your data in your tenant. We review it with the people who will use it.

  3. Week 3

    Evaluate and harden

    We run the evaluation set, measure accuracy and hallucinations, add guardrails and decide where a human reviews output.

  4. Week 4

    Decide

    Test report, security and data flow note, production estimate and a go/no-go recommendation presented to your decision makers.

What you get

  • Use case framing, evaluation set and success metrics agreed up front
  • Working prototype in your cloud tenant (assistant, agent, content model or document extraction)
  • Accuracy and hallucination test report
  • Security and data flow note
  • Production estimate and go/no-go recommendation

Every document is yours to keep and to use with any partner.

What you need to prepare

  • A chosen use case and one product owner on your side
  • Access to a representative data sample or document set
  • A cloud tenant or sandbox we can deploy into (Azure, AWS or Google Cloud)
  • 2 to 4 hours a week from the people who will use the result

What happens after

No obligation to continue

If the prototype hits the agreed metrics, the next step is an AI Solution Build that takes it to production, followed by an AI Operations Partner plan that keeps it accurate after launch. If it does not, you have spent weeks, not months, and you know why.
  1. Project2 to 6 months

    AI Solution Build

    From validated prototype to a production AI system your team trusts and runs.

    • Architecture and secure deployment in your cloud tenant
    • Evaluation suite, guardrails and human-in-the-loop design
    • Integration with your systems, monitoring and cost controls
    • EU AI Act documentation pack
    Start a project
  2. OngoingOngoing, monthly

    AI Operations Partner

    Your AI keeps working, stays compliant and keeps improving.

    • Monitoring and evaluation re-runs on every model update
    • Prompt and model upgrades, cost optimisation
    • EU AI Act and GDPR documentation upkeep
    • Quarterly use-case review
    Book a 30-min call

FAQ

AI Prototype Sprint: common questions

What kind of prototypes can you build in a sprint?

Typical sprints build a customer or employee assistant over your documents, an agent that completes a workflow step, a brand-voice content model, or document extraction. The use case must be narrow enough to evaluate in 4 weeks. We confirm feasibility in the first scoping call.

How do you handle hallucinations?

We agree an evaluation set of real examples in week 1 and measure the prototype against it, including how often it invents answers. We then add guardrails, source citations and human review where errors are costly. The accuracy and hallucination report is a named deliverable, not a promise of zero errors.

Where does our data go?

The prototype runs in your cloud tenant or an EU region we agree on. Your data is not used to train public models, access is limited to the named team, and a data processing agreement covers the work. The security and data flow note documents every flow.

Who owns the prototype?

You do. Code, prompts, evaluation sets and documentation are handed over at the end of the sprint, so you can continue with us, with your internal team or with another partner.

Do we have to build with Grapefruit after the sprint?

No. The sprint ends in a go/no-go recommendation and there is no obligation to continue. If the answer is go, the production estimate is detailed enough for your procurement to compare offers.

What drives the cost of a prototype sprint?

The sprint has a fixed scope agreed before we start. What moves the fee is the number of data sources and integrations, how sensitive the data is, and whether the prototype must run on-premises. We confirm scope and fee after a 30-minute call.

Plan a prototype sprint

A working AI prototype on your own data in 4 weeks, so you decide with evidence, not slides. Tell us a little about your context and we will confirm scope and timing.

We reply within 1 business day, usually the same day. Not ready to talk? Take the free AI assessment.