Services
Four ways to rebuild.
Every engagement starts from reality: what the function actually does today, and the smallest change that proves the thesis. Scope and pricing are discussed openly after a diagnostic — never invented here.
01
AI-Native Opportunity Diagnostic
Find the function where the thesis pays first.
- Who it is for
- CEOs, founders and function leaders who suspect AI should change more than the tooling.
- Symptoms
- AI pilots that demo well and change nothing; disagreement about where to start; strategy decks with no operating model behind them.
- What you get
- Current-state map of one function, a latency and routing scorecard, a recommended pilot with explicit assumptions, and what evidence would falsify it.
- What is NOT promised
- No ROI projections, no vendor selection, no fixed timeline commitments before evidence.
- How it runs
- Two to three working sessions with your operators, analysis of how decisions and context actually move, and a readout you can act on without us.
02
Rebuild One Function
One function, redesigned end to end around humans and agents.
- Who it is for
- COOs and function owners ready to change how one function actually runs — support, reporting, sales operations, knowledge work.
- Symptoms
- The function is drowned in routine; every improvement evaporates in onboarding; measurement is an afterthought.
- What you get
- A redesigned operating model for the function (workflows, decision rights, knowledge state), an implemented scoped pilot where mutually agreed, and a measurement plan.
- What is NOT promised
- No headcount-reduction claims, no guaranteed savings, no rollout beyond the agreed scope without evidence.
- How it runs
- Map → redesign → build the domain brain and governed agents → instrument → learn → decide whether to expand.
03
Agent & Intelligence Infrastructure
The governed machinery: brain, agents, routing, evaluation.
- Who it is for
- CTOs and engineering leaders who need agents that inherit procedure, respect authority, and stay observable.
- Symptoms
- Agent experiments that cannot be governed; context that evaporates between sessions; no evaluation story.
- What you get
- System design plus engineering implementation scope: company brain with epistemic state, governed agent runtime, model routing, evaluation and observability.
- What is NOT promised
- No black-box autonomy, no unsupervised production authority, no lock-in to any single model vendor.
- How it runs
- Architecture against your real systems, staged implementation with verification gates, handover your engineers can own.
04
AI Transformation Partnership
Strategic and operational ownership, case by case.
- Who it is for
- Leadership teams that want a partner who has both restructured organizations and built the machinery.
- Symptoms
- The board wants an AI-native operating model; nobody internally owns both the org and the systems side.
- What you get
- Embedded leadership where appropriate: operating-model ownership, function-by-function rebuild sequencing, and the infrastructure to support it.
- What is NOT promised
- Explicitly case-by-case — no standing retainer structure, no interim-executive packaging, no team-of-consultants illusion.
- How it runs
- Begins only after a diagnostic or a rebuilt function proves the working relationship.
These are services scoped per engagement — not packaged products with fixed outcomes.