Approach
We start from your needs, your process, and your data, then recommend the smallest change that moves the number. Sometimes that is AI. Often it is not.
Our process
Some of the highest-return fixes are a cleaner data feed, a better test, or a simpler process.
The decisions, outcomes, and constraints that matter most.
How work and decisions happen today, and where they break.
Current and future first- and third-party data, and the privacy rules on each.
Short- and long-term goals sized to budget and business continuity.
A phased path your stakeholders agree to before anything is built.
How we work with you
We improve the workflow, use, and governance of what you already have, without upending what already works.
Engagement model
Stop after any stage. Starting fresh? Begin with the audit. AI already in production? Begin with course correction.
For AI already in production that nobody has audited. We trace outputs to source, test whether they reproduce, check what data goes where and under what terms, and build the accuracy baseline that should have existed. Ends with a ranked stop, fix, and keep list, so wasted spend stops before any rebuild starts.
Your business needs, your current process, and an audit of your first- and third-party data: what it can and cannot support today, and the privacy rules on each. Ends with a build-or-wait recommendation, including where a non-AI fix is the better answer.
Built in working sessions with your stakeholders and refined until they agree. Short- and long-term target states, use cases sized against spend and margin, and the first build scoped and costed.
The agreed roadmap, implemented on your existing stack: first models in production, governance and review paths defined, and your team set up to run it after we leave. Governance is designed while the first models are still in flight.
Standing counsel to the CMO: vendor and agency oversight, and a quarterly roadmap refresh with the same stakeholders, without adding a permanent seat.
What a roadmap looks like
Every use case is placed by the value it moves and whether your data, privacy, and review paths can support it in the next two quarters.
Illustrative. Your placement comes out of the audit, reviewed with your stakeholders until they agree.
Operating principles
Constraints we accept on ourselves. Hold us to them.
01
Every recommendation traces to a source you can check.
02
One clean test beats a clever model that answers nothing.
03
One page for the board, full detail for the builders. Both agree.
04
No media buying, no vendor fees. Our advice is ours alone.
05
Not every solution needs AI. Cutting scope is a deliverable.
06
Scope is set up front. No surprise change orders.
Get started
A first conversation is a working session, not a pitch. Bring the number you cannot currently defend and you will leave with a point of view on it, whether or not we work together.
