CONSULTING / AI STRATEGY & READINESS
AI worth putting into production
We help you choose the AI use cases worth doing and get your data, controls and teams ready to run them.
Many AI pilots stall between demo and production: the data is not ready, nobody owns the risk, and no one can say how the system will be checked. We start from the workflows where AI would change the outcome, test readiness honestly and design governance in from the start: evaluation before go-live, an audit trail, and a person who approves what matters. We are model-neutral, with a dedicated Claude practice, and we recommend the model that fits.
Questions we help leaders answer
Where should we use AI first?
We rank candidate use cases by value, feasibility and risk, and pick the ones with a real route to production.
Is our data ready?
We check access, quality, ownership and residency for the data each use case depends on.
Which model should we use?
We compare models on fit for the task, cost, data handling and where they can run, without a reseller bias.
How do we keep AI under control?
We design evaluation, audit trails and human approval steps before anything goes live.
Why did our pilot stall?
We review what was built, what blocked it and what it would take to get it into production, or to stop it.
What happens to our data?
It stays in your cloud and your region. We do not use client data to train or fine-tune models, unless a client asks us to in writing for their own dedicated model.
How we engage
Blueprint
One named problem, 2–4 weeks. You get a solution design, a delivery plan and a risk register from the team that would build it.
Advisory retainer
Senior architects on call as your plans meet reality. We review decisions, challenge vendor proposals and keep the roadmap current as the business changes.
What you get
- A ranked portfolio of AI use cases with value, feasibility and risk for each
- A data and platform readiness assessment
- A model recommendation with the reasoning behind it
- A governance design: evaluation, audit trail and human approval points
- A costed plan to take the first use case into production
Questions
Do you only work with Claude?
No. We are model-neutral and recommend the model that fits each use case. We also run a dedicated Claude practice for organizations that choose it.
Do you use our data to train models?
We do not use client data to train or fine-tune models, unless a client asks us to in writing for their own dedicated model.
Can you build what you recommend?
Yes. The team that shapes your AI strategy is the team that builds, evaluates and runs the system inside your cloud.