// Fixed-fee sprint

From zero to working AI in 30 days.

A four-week sprint that takes your organization from no AI use to one live, governed, measurable use case.

Most small and mid-market AI spend ends up as shelfware. This sprint inverts that pattern. By day 30 you have governance, data clarity, a working pilot in production, trained champions, and a roadmap for what comes next. The deliverable is workflow change, not just training.

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Why this exists

Most AI pilots stall for the same three reasons.

Teams often buy tools before they know what should be governed, which data is ready, and who owns adoption after the pilot ends. The result is usually the same: a lot of activity, little operating change, and no clear way to prove value.

The 30-Day AI Foundation sprint runs the sequence in the right order, with a real outcome at the end: governance first, then data readiness, then one live use case, then a measured expansion plan that people can actually adopt.

Skip governance
Unmanaged risk, shadow AI use, and a policy vacuum that legal and the board start asking about later.
Skip data readiness
Models trained on fragmented, duplicate, or stale data return sophisticated-looking outputs that are quietly wrong.
Skip literacy
Tools land in the org with no shared vocabulary, no use-case backlog, and no idea what "good" looks like.
Skip adoption
A pilot that two people log into once is not adoption. Without a champion network, a KPI baseline, and a deliberate rollout, it dies on the vine.
What happens in 30 days

Four weeks. One working pilot.

Each week has a defined outcome. Each outcome stacks onto the next. By the final week, AI is in production for a real team and the org has a playbook for what to do next.

  1. Week 1

    Govern & assess

    Acceptable Use Policy drafted and reviewed. Data inventory across systems. Risk register and vendor review process. Leadership alignment session on what success looks like.

    Outputs
    • AI Acceptable Use Policy
    • Data readiness scorecard
    • Risk register
    • Leadership alignment memo
  2. Week 2

    Literacy & discovery

    All-hands AI literacy session built for your org, not generic. Manager workshops to identify high-volume manual work. Interviews across teams to surface a candidate use-case list and the change impacts around it.

    Outputs
    • All-hands literacy session
    • Manager workshops
    • Use-case backlog ranked by ROI and feasibility
    • Pilot selection
  3. Week 3

    Pilot build

    Configure the tooling for the chosen use case (Copilot, ChatGPT Enterprise, or a domain platform). Build the prompts, workflows, and integrations. Train the pilot team in working sessions.

    Outputs
    • Configured tooling
    • Workflow and prompt library
    • Pilot team trained
    • Baseline KPIs captured
  4. Week 4

    Deploy & measure

    Roll the pilot into daily work. Two internal champions trained to run it after we leave. KPI baseline locked, workflow change documented, and a 90-day expansion roadmap delivered to leadership.

    Outputs
    • Live pilot in production
    • Two trained champions
    • Measured ROI baseline
    • 90-day expansion roadmap
Day 30 deliverables

What you walk away with.

Live use case
One AI use case in production for a real team, with a measured baseline and a clear way to expand it.
AI Acceptable Use Policy
A signed, board-ready policy covering acceptable use, prohibited data, vendor review, and incident response.
Data readiness scorecard
An honest inventory of where your data is ready for AI, where it isn't, and what to fix first.
Trained champions
Two internal people who can run the pilot, expand it, and onboard the next team without us.
90-day roadmap
A ranked, sequenced list of the next use cases with effort, ROI, and dependencies called out.
Literacy baseline
A common vocabulary across the org so leaders, managers, and operators are talking about AI the same way.
Who it's for

Built for organizations starting from zero.

If you've been holding off on AI because nobody can tell you where to start, this sprint is for you.

Right fit

  • You have between 25 and 500 employees
  • No formal AI strategy or governance yet
  • Leadership wants real AI value, not vanity pilots
  • You have at least one repeatable, document-heavy or analysis-heavy workflow
  • You can dedicate a small pilot team for four weeks

Not the right fit

  • You already have a CAIO and a governed AI program
  • You want to build a customer-facing AI product (talk to Foundry instead)
  • Your data is on paper or sits exclusively in one person's head
  • You need a research project, not an operating outcome
  • No executive sponsor available for the alignment session
FAQ

Common questions.

How much does it cost?
Fixed fee, scoped to the size of your organization and the chosen use case. We share pricing on the discovery call once we understand fit. The sprint is designed to cost less than waiting another quarter to figure it out yourselves.
What kind of use case do you usually pick?
Common Week 1 outputs: contract or document review, quote and proposal drafting, customer-support triage, internal knowledge search, financial variance commentary, RFP response, and inspection report generation. The pilot is chosen for ROI and feasibility, not novelty.
Do we need to buy software?
Usually you'll already have something that fits (Microsoft Copilot, ChatGPT Enterprise, or a domain platform you already license). If a new license is needed we'll quantify it up front and only recommend it if the pilot ROI clears the bar.
What happens after day 30?
Three paths. You can run the playbook yourselves with the champions we trained. You can move into a fractional CAIO retainer with us to expand systematically. Or you can engage EdgePoint Foundry to build custom integrations or models when the next use case demands it.
How much of our time do you need?
Roughly: an executive sponsor for a few hours total, a pilot team of three to five people for two to four hours per week in Weeks 3 and 4, and one IT contact for data and tooling questions throughout.
Is this just a workshop?
No. By day 30 there is a working pilot doing real work, not a slide deck. The literacy session and workshops are part of it, but the deliverable is operating AI, not training certificates.
EdgePoint Foundry

When the next use case needs custom build.

The Foundation sprint almost always leans on configured tools rather than custom code. When the next step demands a custom integration, pipeline, or model, EdgePoint Foundry, our development division, builds it on top of the foundation the sprint laid down.

Explore Foundry
EdgePoint Foundry
Related

What comes after the sprint.

Fractional CAIO

Ongoing AI leadership after the sprint: governance, use-case pipeline, adoption measurement, and change management.

Learn more

EdgePoint Foundry

Custom integrations or models when a configured tool is no longer enough.

Learn more

Case studies

See the operating change and measurable results that follow once the foundation is in place.

Learn more
// Start the conversation

Ready to start the 30-day clock?

A 30-minute discovery call. We'll talk about your current AI use (or lack of it), your data, your change readiness, and whether the sprint is a fit. If it is, we can schedule the start date on the call.

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