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Engagement Model

Start with clarity

A focused 2-week sprint that turns an AI ambition into a validated plan — feasibility, data readiness, architecture, ROI and a roadmap — before you commit to a build.

The problem

Most AI projects fail before they start

Not because the technology can't do it — but because the wrong idea got funded, the data wasn't ready, or the scope was never truly understood.

?Everyone has AI ideas, but no one's certain which one will actually move a number.
?You're not sure your data is ready — or even that the problem is a fit for AI at all.
?Estimates swing wildly because the scope and architecture haven't been thought through.
?Leadership wants an ROI case before committing budget to a build.
What you get

Six concrete deliverables

You walk away with artefacts you can act on and defend — not a slide deck of buzzwords.

Feasibility assessment

A clear-eyed verdict on whether AI is the right tool for the problem — and which approach (classical ML, RAG, agents or fine-tuning) actually fits.

Data readiness audit

An honest review of the data you have: quality, volume, labelling, access and gaps — with a plan to get it production-ready.

Solution architecture

A reference architecture for the system: models, pipelines, infrastructure, integrations, evals and guardrails, designed to scale.

ROI model

A grounded business case — costs, expected impact and payback — so you can defend the investment to stakeholders with numbers, not hope.

Delivery roadmap

A phased plan from prototype to production, with milestones, effort estimates and a recommended engagement model.

A go / no-go recommendation

Our candid recommendation on whether — and how — to proceed. Sometimes the most valuable outcome is a confident no.

The sprint

How the two weeks run

Two tightly focused weeks, from alignment to a clear decision.

Week 1

Align & investigate

  • Kickoff: goals, constraints and success metrics
  • Stakeholder interviews and problem framing
  • Data discovery and readiness assessment
  • Feasibility and approach exploration
Week 2

Design & decide

  • Solution architecture and model strategy
  • Rapid concept prototype or spike where useful
  • ROI model and phased delivery roadmap
  • Findings readout and go / no-go recommendation
Who the AI Discovery Workshop is for
Who it's for

Built for the moment before you commit

Product & engineering leaders who need a defensible plan and estimate before committing a team to an AI build.

Founders exploring an AI idea who want to de-risk feasibility and data before raising or spending on it.

Enterprises with an AI mandate sitting on data and pressure to deliver, but unsure where the real value is.

Teams stuck at proof-of-concept with a demo that impressed but no clear path to a production system.

FAQ

Questions, answered

How long does it take and what does it cost?

The sprint runs over two weeks with a fixed, transparent fee. You know the price and the deliverables before we begin — no open-ended engagement.

What do we need to prepare?

Access to the right stakeholders for a few interviews, and a representative sample of your data if it's available. We handle the rest. The more openly you share context, the sharper the output.

What if the recommendation is not to build?

Then the workshop just saved you a far larger investment. A confident 'no' — or 'not yet' — is a genuinely valuable outcome, and you keep every artefact either way.

Do we have to build with you afterwards?

No. You own all the deliverables and are free to take them to any team. That said, most clients continue with us because we already understand the problem deeply.

How does this fit with your other engagement models?

The workshop is the ideal on-ramp. From here you can move into a Fixed-Price build for a defined scope, or a Dedicated Team for an evolving roadmap.

De-risk your AI idea in two weeks

Come out the other side with a validated plan, an ROI case and a clear next step — or the confidence to walk away.