AI Strategy & Delivery

Find where AI creates value. Prove it works. Ship it.

Four fixed-scope engagements that take AI from open question to production capability. Each targets a specific stage: finding the right opportunity, validating it with real data, shipping it into production, or mapping the AI tools your team is already using without approval.

01Sprint1 week

AI Opportunity Sprint

Find the highest-value AI opportunity in your business. In one week.

Most companies know AI matters. Few know where it matters most for them. We spend a week inside your operations, product, and workflows. You get a ranked list of AI opportunities with estimated ROI, complexity, and a clear recommendation on where to start.

Opportunity map ranking AI use cases by business value and feasibility
Recommended first build with estimated cost, timeline, and expected ROI
Data readiness assessment for your top opportunities

Best for: Companies that know they should be using AI but haven't found the right starting point, or have tried one initiative that didn't go anywhere and want a structured second look.

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02Sprint2–4 weeks

AI Prototype & Validation

See it work before you commit to building it.

You've identified an AI opportunity. Before committing to a full build, you need proof it works with your data, your workflows, your users. We build a working prototype in two to four weeks. Real data, real users, measurable results. The prototype either validates the business case or saves you from a six-month mistake.

Working prototype tested against your actual data and workflows
Validation report with measured results and user feedback
Production roadmap: architecture, cost model, timeline, and build-or-buy recommendation

Best for: Companies with a specific AI use case in mind that need to validate it before committing budget, or companies coming out of an Opportunity Sprint ready to test the top recommendation.

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03Delivery4–8 weeks

AI Build & Integration

From validated prototype to production capability.

The prototype worked. The business case is solid. Now it needs to run in production: reliable, monitored, integrated with your systems, and maintainable by your team. We design the architecture, build the data pipeline, deploy the AI capability, and hand it off with documentation your engineers can work from on day one.

Production-deployed AI capability integrated with your existing systems
Architecture documentation and operational runbook
Team handoff with knowledge transfer so your engineers own it going forward

Best for: Companies with a validated AI opportunity that need it built and deployed into production, or companies ready to add AI capabilities directly into their product.

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04Assessment1–2 weeks

Shadow AI Assessment

Your employees already wrote the AI roadmap. Let's read it.

More than half your employees are using AI tools you haven't approved. Every spreadsheet uploaded to ChatGPT, every document pasted into Claude, is a feature request. We map the workflows your people are routing around your systems, rank them by business value, and deliver specs for the top three. The shadow AI landscape is your automation roadmap.

Shadow AI heatmap showing which tools are being used for which workflows
Build-vs-buy analysis for the top three highest-value workflows
Engineering-ready specifications to convert shadow usage into sanctioned capabilities

Best for: Companies where employees are using ChatGPT, Claude, Copilot, or other AI tools without formal approval, and leadership wants to get ahead of it rather than shut it down.

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