Service

AI Implementation Strategy

Separate the AI investments that earn their keep from the demos burning your team's afternoons — and roll out the ones that fit.

Most AI conversations start with the model and end in a Slack channel of half-deployed pilots. We start with the work — where the time is actually leaking, where the judgment calls don't need to be human, and where the brand voice does. Then we cost the options against each other: build, buy, or skip. The deliverable is a short list of pilots with success criteria and a kill date attached, plus the policy and training to put them in your team's hands. Sometimes the right answer is "not yet" — and that still beats the wrong rollout.

Typical deliverables

AI use-case audit across operations, marketing, and customer-facing workflows
Build-vs-buy-vs-skip scorecards for each candidate (foundation models, vertical SaaS, open-source)
Vendor selection and procurement guardrails (data residency, contract terms, exit ramps)
Pilot scopes with success metrics and a kill criterion before any rollout
Internal-policy drafting: data handling, prompt hygiene, acceptable-use guidelines
Training and change management for the teams whose work changes most

Ready to scope this out?

The 30-minute fit call is where we figure out whether this is the right engagement — and what the first sprint would look like.

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