We help CIOs, CTOs, and operating leaders decide where AI will create real value, design systems that can survive production, and get them shipped.
Most organizations don't have an AI technology problem — they have an AI decision problem. The right call requires a partner who understands the boardroom, the data, and the code that has to run under both.
You're being asked to commit budget, org structure, and a public narrative to AI — without a defensible view of where the real value is, which bets are serious, and which are theater.
Legacy systems, inconsistent data models, and in-flight cloud migrations have created a foundation that can't reliably support the AI initiatives leadership has already announced.
Promising pilots keep stalling at the hand-off to engineering, frontline adoption, or compliance review. You need a partner who has shipped end-to-end — not a deck factory.
Two days. Fixed scope. You walk away with a value model, architecture brief, risk assessment, and a three-option recommendation — before committing a dollar to development. No downstream obligation.
Map the current process, identify data and constraints, and run the Economic Readiness Model against your numbers.
Sketch the system, identify risks, and produce three options: build, partner, or wait — with rationale for each.
Value model, architecture brief, risk assessment, and recommended roadmap. Written for both technical teams and leadership.
Every engagement is structured as a custom Statement of Work — scoped to the outcome, not the template.
Board-ready AI strategy with prioritized initiatives, quantified business cases, and a sequenced roadmap with decision gates.
Map how work actually happens, identify where AI adds value, model the economics, and define a production-safe pilot.
Make your systems and data usable for AI — canonical models, entity mapping, and migration alignment.
A senior operator inside your team, carrying a named outcome — not a deliverable list, but a result.
We don't hand off a strategy deck and walk away. The same team that designs the approach can build the system, deploy it, and stay embedded through production.
We build and operate our own AI-powered systems daily. The patterns and architectures we bring to client work have been tested under real operational pressure — not just theorized.
See Squire →145 patent claims across three U.S. provisional filings and peer-reviewed published research. The methods behind our work are original, defensible, and field-tested.
See the Platform →30-minute call to pressure-test the problem. If there's a fit, the usual next step is a 2-day Rapid Assessment. If there isn't, we'll tell you that directly.
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