AI consulting from people who also ship the build
We do AI consulting as engineers, not analysts. That means the recommendation comes with a cost model, an integration plan, and someone willing to build it, and occasionally with the advice not to build it at all.
No sales script. You talk to the engineers who'd build it.
Our team works a shifted day so you get real-time standups and same-day turnarounds in your time zone, not next-morning replies.
Every line of code, model weight, and prompt is yours from day one. NDAs and clean IP assignment are standard, not an upsell.
You work directly with the engineers building your system. No account managers sitting between you and the people writing code.
We move from scoping to a working system in production in weeks. Most engagements ship something usable inside the first month.
What we build
Concrete systems we ship, tuned to your data and your stack.
Use case selection
Which process, in what order, with the baseline numbers written down. Most cancelled AI projects failed this step and nobody noticed until month six.
Build vs buy analysis
An honest comparison including the integration work and the parts of the vendor product you will end up building yourself.
Architecture and cost review
A second opinion on a design or a running system, with the failure modes and the unit economics laid out.
Vendor evaluation support
We sit in on demos and ask the questions that separate an agent from a workflow tool with new labels.
How we work
Scope & evals
We pin down what success means and build the evaluation set before writing the feature, so quality is measured, not guessed.
Build in the open
Weekly demos against real data. You see progress every week and can change direction before it gets expensive.
Ship & instrument
We deploy with logging, cost tracking, and guardrails in place, then tune against production traffic.
Hand off or stay
Take the keys with full docs, or keep us on for iteration. Either way you're never locked in.
Questions, answered
Do you do strategy work without a build attached?
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Yes, and it is usually a short engagement measured in weeks. We would rather give you something you can act on than produce a document that gets filed.
What does an AI readiness review cover?
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Data access and quality, integration surface, permission model, evaluation capability, and the operating model question of who will own the thing once it is live. The last one is the most commonly missing.
Can you help us pick between vendors?
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Yes. Ask each of them to run your input live on the call, show a failed run with their real failure rate, and export a full trace. Two evaluations we have sat in on ended in the first fifteen minutes.
Will you recommend not doing AI?
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When it is right, yes. A process with a fixed path is a workflow problem, and a language model on top of it is expense without benefit.
Let's scope your build.
Tell us what you're trying to ship. We'll tell you honestly whether AI is the right tool and what it would take.