We pinpoint the AI use-cases that move your metrics, score each one on value, effort and model-risk, and hand you a sequenced, governed roadmap with the first build already scoped. We're the team that ships it - so the plan is built to be executed, not admired.
The hard part isn't ideas for AI. It's choosing the few that pay off, knowing what to build versus buy, and having a plan that survives a security and compliance review. That's where most AI efforts quietly stall.
Use-cases get picked because they look impressive in a room, not because they move a number that matters to the business.
Teams over-build what they could have bought, or buy a tool that can't do the job. Both are expensive to unwind later.
The work stalls in procurement and security review because model-risk and compliance were never designed in from the start.
Proofs of concept that impress in a demo and then quietly die before they ever reach production.
Four moves, one engagement. Find the use-cases that pay off, score them honestly, ground them in your stack - and sequence them into a roadmap you can actually run.
We find where AI moves your numbers - not where it looks good in a demo. Workshops and a review of your products, operations and data produce a longlist mapped to the metrics you care about.
Every opportunity scored on value, effort and model-risk, with a clear build, buy or partner call and a business case for each priority use-case.
A pragmatic blueprint for your stack, data and integrations - honest about what's ready now and what has to be fixed first.
A sequenced plan with governance and compliance built in, and a first build scoped tightly enough to start the week the sprint ends.
Not an open-ended retainer - a fixed-scope, fixed-fee engagement with a clear path from first call to handover. Tap through each stage, or let it play.
We learn your product, your goals and your constraints, and confirm the sprint is the right first step - before anyone commits to a scope.
Workshops and stakeholder interviews, plus a working review of your product, data and architecture - so the longlist is grounded in how you actually operate.
Longlist becomes a scored shortlist - every use-case rated on value, effort and model-risk, with build-vs-buy calls, the target architecture and a candid data-readiness read.
The governed roadmap, the first build scoped to start immediately, and a working session that leaves your team aligned and moving - artifacts, not impressions.
No use-case makes the roadmap on a hunch. Each one enters from your product, operations and data, gets scored on the three axes that decide whether AI is worth it - value, effort and model-risk - and comes out with a build, buy or partner call. What survives is sequenced into a governed roadmap and a first build, ready to start.
Scored against your metrics and your compliance bar - every call is evidence-backed, never a hunch.
One engine, three axes - value, effort and model-risk decide what gets built, bought or partnered.
The scoring is the point. The same rubric that finds your highest-value first move also tells you honestly when not to build - and every score carries the evidence to defend the call in a security or board review. That's what separates a roadmap that ships from a strategy that stays on a slide.
By the end of the engagement you hold six concrete deliverables - each one built to be executed, and to survive the reviews it has to pass.
Every opportunity scored on value, effort and model-risk - ranked, not just listed.
A clear build, buy or partner call plus a business case for every priority use-case.
A pragmatic blueprint for your stack, with a candid data-readiness assessment.
Aligned to US frameworks like the NIST AI RMF, the EU AI Act and the reviews you must pass.
A phased plan your team can act on - ordered by value, governed from day one.
The highest-value first move, scoped tightly enough to start the week the sprint ends.
The roadmap is costed and sequenced by the people who'll ship it - not theory from a team that hands off and leaves.
Model-risk and compliance are scored into the strategy from day one, not bolted on when procurement starts asking.
Pattern recognition from real builds across regulated and high-growth software - not frameworks borrowed from a slide library.
We've shipped AI across regulated software and the enterprise - finance, insurance, healthcare, manufacturing - so we know the bar it has to clear before it goes live.
We'll tell you when not to build. And when you should, we bring the partner stack to do it right - Member of the Claude Partner Network, Snowflake and Databricks - under ISO 27001 controls.
Usually a CTO, CIO, VP of Engineering, Head of Data, or a technical founder.
The EU AI Act's high-risk rules are in force and US frameworks are arriving fast. Wherever AI starts making or shaping decisions that carry real consequences, governed AI is becoming a condition of doing business - and the risk reviews you face, from customers or your own auditors, already demand it. Your roadmap should be built around that from the start, which is why every sprint includes a governance and model-risk track, not a compliance scramble later.
More on this: AI Governance→Most engagements start here and move into a first build with the same team - an agentic copilot in your product or your internal tools, custom agents on your data, or a full build through our AI-Powered SDLC. A small first step, governed from day one, expanding as the value compounds.
About four weeks for the sprint, after a 30-minute discovery call. Fixed scope, fixed fee - no open-ended retainer.
No. The roadmap is yours to keep. Most clients continue with us because the same team can ship it, but there's no lock-in.
The earlier you get the build-vs-buy and governance calls right, the less you waste later. The sprint is sized for exactly that moment.
Then we'll say so. We score honestly and we're not afraid to recommend not building something.
An NDA up front, ISO 27001 controls throughout, and your data and IP stay yours.
Yes. Model-risk and compliance are part of the roadmap, not a separate engagement, and aligned to frameworks like the NIST AI RMF and the EU AI Act. See our AI Governance page for the full lifecycle.
Book a 30-minute discovery call. We'll point to the highest-value first step - and the governance to ship it with confidence.