What we do

Three disciplines, one team.

Strategy and execution split apart in most AI programs. We keep them on the same team — so the advisor knows what's worth building and the builder knows what's possible to ship.

A · Build

Products & solutions.

Working AI systems shipped inside your workflows — never a notebook or dashboard demo.

We design, ship, and operate AI products against a metric we agreed to move. The output is a system your team uses on Tuesday morning, not a slide deck about what could be.

What you get

  • Architecture proposal & data design
  • Production MVP within 8–12 weeks
  • Telemetry & evaluation harness
  • Runbook + on-call handoff

Good fit when

  • A specific decision or workflow you want to automate or augment
  • Data already exists — even if messy
  • Internal owner who'll use the system once it ships
B · Advisory

Strategy with execution.

Find the decisions worth changing, sequence them, and lock the metric before any code is written.

Most AI strategies stall because they treat AI as a portfolio question instead of an operational one. We walk your workflows, shortlist the candidate decisions by feasibility and value, and pick the one or two we'd put real money behind.

What you get

  • Use-case backlog ranked by value × feasibility
  • Metric definitions & success criteria
  • Sequenced 6–12 month roadmap
  • Build-vs-buy recommendations per workflow

Good fit when

  • Leadership wants AI in the plan but not as theatre
  • Multiple candidate use-cases with no clear prioritization
  • A budget that needs to defend itself in two quarters
C · Enablement

Training for adoption.

Programs calibrated by role and built around the systems your team already uses every day.

AI adoption fails on the human side more often than on the technical side. Our enablement programs are role-specific, hands-on, and tied to the systems your team already touches — so the new tool earns its place in the workflow instead of competing with it.

What you get

  • Role-mapped curriculum
  • In-person + async content library
  • Champion certification track
  • Pre/post adoption measurement

Good fit when

  • A system has shipped but usage is low
  • Multiple teams, varied AI fluency
  • An exec sponsor who wants this measured, not vibes

Start with a discovery session.

We'd rather scope a focused engagement around a single decision than promise a transformation. The second use case finds itself.