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Engagement models

Five ways to work with us, none of them vague

Senior people, small teams and fixed scopes where the work allows it. Pick the model that matches how much you already know, then we write it down before anyone starts.

  • Written scope before code
  • Fixed price where possible
  • Start within weeks
The models

Choose by how much is already known

If the outcome is clear but the solution is not, start with discovery. If both are clear, fix the scope. If the roadmap keeps moving, bring in a team. If you need leadership more than hands, take a fractional CTO. If it is already live, let us run it.

Start here

Discovery sprint

For deciding what to build and whether it is worth building. Use-case selection, data readiness, architecture and an estimate.

  • Written specification and risk list
  • Architecture and platform choices
  • Evaluation plan for AI features
  • Prototype where it reduces risk
  • Milestone estimate you can take anywhere

Typically 1–3 weeks · fixed fee

AI strategy and consulting
Defined scope

Fixed-scope build

For a system with clear outcomes and acceptance criteria, usually following discovery. Priced per milestone.

  • Working software demonstrated every two weeks
  • Automated tests and evaluation sets
  • Security review before launch
  • Documentation and handover
  • Warranty period after go-live

Typically 6–16 weeks · fixed price per milestone

AI implementation
Moving roadmap

Dedicated team

For product companies and programmes where the backlog is yours and the capacity is ours. A named lead and two to six engineers.

  • Stable team, your tools and rituals
  • Named technical lead accountable to you
  • Monthly capacity, adjusted with notice
  • Direct access to every engineer
  • Quarterly review of outcomes

Typically 3 months or more · monthly

Custom software development
Leadership

Fractional AI CTO

For organisations that need senior AI judgement a day or two a week: strategy, vendor decisions, governance, hiring and architecture review.

  • Roadmap and investment cases
  • Model and platform decisions
  • Governance and risk register
  • Hiring and team design
  • Review of suppliers, including us

Typically 1–2 days a week · monthly retainer

Fractional AI CTO
In production

Managed services

For live systems that need monitoring, upkeep and small improvements: AI applications, Salesforce orgs, event platforms and custom software.

  • Agreed response and resolution targets
  • Monitoring, evaluation and model upkeep
  • Release management and admin
  • Monthly improvement allowance
  • Quarterly health check

Ongoing · monthly

Salesforce managed services
Not sure?

Start with a conversation

Thirty minutes with a practice lead is usually enough to say which model fits. If none does, we will say so and suggest who might be better placed.

Book a call
Side by side

How the models compare

CriteriaDiscovery sprintFixed-scope buildDedicated teamFractional AI CTOManaged services
Best forDeciding what to buildClear scope, clear acceptanceEvolving roadmapSenior judgement, part-timeLive systems
Typical duration1–3 weeks6–16 weeks3+ months3+ months12-month terms
Commercial modelFixed feeFixed price per milestoneMonthly capacityMonthly retainerMonthly, with allowance
Team shapeLead + architectLead + 2–5 engineersLead + 2–6 engineersOne senior personShared support team
Who owns the backlogSharedFixed in the SOWYouYou, with our inputShared
Change requestsNot applicableChange controlRe-prioritise freelyNot applicableWithin allowance
Ending itEnds with the deliverablesEnds at acceptanceNotice periodNotice periodNotice period
Fixed price availableYesYesNoNoYes, per term
The lifecycle

How an engagement moves from idea to running system

Engagement lifecycle: discovery sprint, statement of work, build in sprints, acceptance and hardening, launch, then run; change requests loop back from build to the statement of work, and a fractional AI CTO can span every stage 1 · Discovery sprint spec · architecture · risks 1–3 weeks, fixed fee estimate 2 · Statement of work scope · milestones · acceptance signed before sprint 1 3 · Build in sprints demo every two weeks tests · evals · security review change request → re-estimate → written addendum final milestone delivered 4 · Acceptance & hardening your testing against the criteria load, security, rollback plan sign-off 5 · Launch go-live support · monitoring warranty period 6 · Run managed services or dedicated team quarterly review → next discovery Fractional AI CTO: senior oversight across every stage, including of our own work
Every arrow is a written artefact: an estimate, a signed statement of work, a demo, a sign-off. Changes go back through the statement of work rather than around it.
How we estimate

Ranges, assumptions and the people who will do the work

  1. Pin the outcome

    What will be true when this is done, and how will we measure it? If we cannot answer, we are not ready to estimate.

  2. Break into deliverables

    Each with acceptance criteria you could hand to a tester. Vague deliverables are where estimates die.

  3. Size with the builders

    The engineers who will do the work give optimistic, likely and pessimistic figures. Sales does not estimate.

  4. Add explicit allowances

    Integration unknowns, data quality, model evaluation and your availability are listed as separate lines, not hidden in a margin.

  5. Present options

    A range with the assumptions that drive it, and usually a smaller version that proves the idea sooner.

When we say no

We decline fixed prices for work that has not been through discovery, AI features with no evaluation plan, and timelines that depend on a third party we cannot influence. A smaller, honest scope beats a large, hopeful one. Our AI readiness assessment is a quick way to see whether you are at the discovery stage or the build stage.

The paperwork

What a statement of work contains

Every engagement, however small, has a statement of work. It is short, written in plain English and designed to be read by the people doing the work as well as the people paying for it.

  • Objectives and success criteria
  • Scope, including what is explicitly out of scope
  • Deliverables with acceptance criteria
  • Milestones, timeline and demo cadence
  • Team, named lead and escalation route
  • Your responsibilities and dependencies
  • Commercial terms and payment schedule
  • Change-control procedure
  • Intellectual property and confidentiality
  • Data handling, security and access
  • Warranty and post-launch support
  • Assumptions behind the estimate
What we need from you

A decision-maker who can attend a demo every two weeks, access to the systems and data in scope within the first week, and a single place for questions. Most delays we have seen were waiting, not building.

Our delivery process

Workshops, sprints, QA and support, as we have run them since 2006.

How we work

See the results

Six engineering case studies from the products we run ourselves.

Case studies
FAQ

Frequently asked questions

Can we switch from one engagement model to another?

Yes, and most clients do. A discovery sprint usually leads to a fixed-scope build, which becomes a dedicated team or managed services once the system is live. Each change is a new statement of work, not a renegotiation of the old one.

Do you work on a time-and-materials basis?

Dedicated teams and fractional AI CTO work are billed monthly for agreed capacity. Builds are fixed price per milestone where the scope is clear enough; where it is not, we run a discovery sprint first rather than guess.

What is the smallest engagement you take on?

A discovery sprint of one to three weeks. It produces a written spec, an architecture and an estimate you can take to anyone, including another supplier.

Who owns the intellectual property?

You own the deliverables and the code we write for you, on payment. We retain our pre-existing tools and know-how, and we tell you up front if a proposal includes licensed components such as Eventify.

What happens when the scope changes mid-build?

Small changes are absorbed within a sprint. Anything that moves a milestone goes through change control: we re-estimate, you decide, and the statement of work is amended in writing. No surprises on the invoice.

Ready to make AI work in production?

Tell us about your systems, your data and your constraints. We reply within one business day with a straight answer and a suggested next step.