Services / AI consulting
AI strategy, architecture & delivery
Most organizations don't have an AI-model problem — they have a "which workflow, with what architecture, under what controls" problem. That's the problem we take on.
What does an engagement look like?
Engagements start with a fixed-scope opportunity & architecture sprint. It answers three questions with evidence, not slideware:
- Where does AI actually pay off? We map your high-value, knowledge-intensive workflows and rank them by value, feasibility, and risk — against your real data, not a demo dataset.
- What should be built? A concrete architecture: model choices, data flows, evaluation criteria, human-review points, and the failure modes that matter — plus what we'd explicitly not build.
- What are the controls? Data handling, retention, deployment options (your cloud, your accounts), and how outputs get verified before anyone relies on them.
The sprint produces a buildable architecture and a decision memo. If the right answer is "you don't need AI here," the memo says so — that conclusion is cheaper in week two than in month eight.
Then we build it
The same engineer who designed the architecture delivers it — no handoff to a junior team. Delivery follows our standard model: prototype against real inputs with evaluation criteria defined up front, then production hardening in your infrastructure, then documented handoff. See how we work for the full engagement model.
What we don't do
- We don't train foundation models from scratch.
- We don't sell a platform, and we don't create lock-in to one.
- We don't staff-augment: we take responsibility for outcomes, not seats.