Bespoke, at the pace of intent.
Rebuild your business AI‑native.
Most enterprises are AI‑first: agents and tools layered onto foundations built before any of it existed. We are AI‑native — the foundation itself, redrawn for the company in front of us.
Example target operating model · Retail & Distribution
Zone · 01 Customer & Channels
Zone · 02 Operations
Zone · 03 Foundations
Each function maps to one of three levels of AI involvement — see the legend.
Building with AI, not just using it.
Most enterprises today are using AI rather than building with it — tools licensed, copilots deployed, vendor APIs called, third-party chatbots adopted department by department. Each one a layer between the company and the model that does the work. The agents are generic. The data leaves the perimeter. The dependency compounds.
AI-native is a different posture. The operating layer is your own. The agents are designed for the work you actually do. The model can sit inside your perimeter if the regulator or your competitive instinct says so. No middleman between the work and the intelligence doing it. HBS, Nov 2025.
What is usually sold as AI transformation is AI-first with a roadmap attached. The substrate work is harder, slower from the outside, and the only kind that compounds.
Agents designed for the work in front of us, integrated with the data that runs through it, deployed inside your perimeter or on the infrastructure of your choosing. The system is yours; the methodology travels with us; the rigour holds where vendor demos do not. We engage one client at a time, deeply.
Three engagement types. One narrative.
Honest answers, decision-grade.
Senior diagnostic engagements run end-to-end by the practitioners doing the work. Technical due diligence, operational and business-model assessment, AI-readiness, operating-model audits, landscape reviews. Each engagement is shaped to the question that actually needs answering. Deliverables read at every level — the desk that acts on them, the executive who decides, the board that signs off.
AssessStrategy, written to be executed.
Vision, strategy, roadmap, moat discovery, requirements engineering, product discovery, target operating model. Sequenced to fit — months when the constraints allow, weeks when the situation calls for it. Captured in a form that the executive team can decide against and the engineering team can build from — and that survives contact with the agents that will work alongside them.
DesignTwo flagships, one philosophy.
Agent-Native Operations sits underneath both. The Target Operating Model for operations-heavy businesses: the way the work itself is redesigned. The AI-SDLC for tech-delivery-heavy businesses: from business intent to code, end to end. Sovereign LLM for organisations that need the whole stack inside their perimeter. Plus Digital Employee, agentic process redesign, and continuing development.
Build & TransformA sustained engagement, when that’s the right shape.
Some situations call for a strategic conversation rather than a delivery — board-level questions, CTO-shaped questions, AI questions that need to be answered before the work can be scoped. The shape is bespoke. The cadence, the scope, and the outcome are agreed before anything starts. Advisory →
The business that runs itself, supervised.
An operating layer that turns a function chart into a working fleet of agents. Roles, decision rights, handoffs, audit trails — explicit, visible, editable by the people who own them. The work that used to live across seven meetings lives in one surface.
Stylised view. Your real surface is built for your operating model.
The pricing engine SHALL apply competitor-aware adjustments to assortment SKUs
within CHF 50,000 daily impact without human approval. Above threshold:
hand off to the merchandising lead with a one-page rationale.
TDD drafting · technical design awaits approved BRD
Build · tests-first, PRD-driven
Review · PR queue and human gates
Deploy · release manifest & rollback
Stylised view. Your real pipeline runs on your repo, your reviewers, your gates.
Business intent. Specifications. Working code.
The pipeline begins with a short prompt from the business and ends with code in production. Between those, an agentic loop reads, clarifies, designs, writes, reviews, tests, documents, and maintains — drawing on a comprehensive understanding of the company. The agents do the lifting; the humans set direction and weigh trade-offs.
Your model. Your data. Your premises.
A complete vertical, end to end. The hardware on which the model runs. The open-weight model selected to fit the work. The agentic orchestration layer above it. The tools and integrations the agents touch. The AI-SDLC that builds on top. The Digital Employee that uses it. The company chatbot that runs on it.
No vendor lock-in. No token bill that grows with usage. No data that leaves the jurisdiction. Independent of OpenAI, Anthropic, anyone else.
For organisations whose regulators, customers, or boards have already decided that this is the only acceptable shape — and for those whose constraints will arrive at the same conclusion eventually.
Wherever the work happens.
Agents that meet your team in Slack and Teams. Workflows that run inside your AWS, GCP, Azure, or sovereign environment. Connectors to the systems of record you already operate — and to the ones you would rather replace. The agent fleet lives where the work lives.
A set of capabilities that matter — each one done to the highest standard, bespoke.
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I
DiagnosisTechnical Due Diligence Operating Model Audit Landscape Assessment AI-Readiness Audit
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II
StrategyVision & Strategy Roadmap Target Platform Moat Discovery Product Discovery
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III
Operating ModelTarget Operating Model Agentic Process Redesign Requirements Engineering
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IV
DeliveryAI-SDLC Development Digital Employee Sovereign LLM
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V
AdvisorySustained executive engagement
The Team.
A senior practice across systems engineering, product management, architecture, development, and AI specialism. The work has included state-of-the-art trading platforms with ultra-low-latency performance, institutional-scale programmes and roadmap design and execution, strong product implementations, complex automation, and full operating-model and AI-native transformations inside heavily regulated environments — Switzerland, the European Union, and the Middle East. Long-horizon engagements measured against precision and durable business growth, not slideware.
Technical excellence is the starting point. We have always built — the AI-native moment changed the tools and accelerated the work. The same people who designed and shipped those systems now design and ship the agent fleets that run alongside them. Builders, not users.
We make AI legible to founders, owners, boards, and executive teams. We make it real for the engineering and operations teams who will use it every day.
Headquartered in Switzerland, with a global delivery network. The core team is small by design; named senior partners across geographies are activated when an engagement calls for additional capacity — sub-contracted under one brand, one accountability, one point of contact.
You can outsource the thinking to AI, but not the understanding.
How the work actually runs.
An engagement isn’t a single delivery — it’s a layered sequence of parallel and dependent tracks. Audits run in parallel; design depends on what they surface; rollout sequences against the operating-model decisions made during design; sovereign infrastructure is delivered alongside the transformation, not after it. The diagram below maps a typical engagement shape. Every engagement is its own.
- Technical Due DiligenceW1–W3
- Codebase AnalysisW1–W3
- Stakeholder InterviewsW1–W2
- Landscape AssessmentW2–W4
- AI-Readiness AuditW3–W5
- Vision & StrategyW4–W6
- Target Operating ModelW6–W9
- RoadmapW8–W10
- Target Platform ArchitectureW9–W11
- Hardware procurementW6–W12
- On-premise model deploymentW12–W14
- Agentic orchestration layerW14–W17
- Tools & integrationsW16–W19
- Company chatbotW18–W20
- AI-SDLC on sovereign stackW19–W22
- Agentic Redesign — Function 1W10–W14
- Agentic Redesign — Function 2W12–W16
- Agentic Redesign — Function 3W14–W18
- AI-SDLC enablementW14–W20
- Digital Employee deploymentsW18–W24+
Tell us what you’re working on.
A short note about what you are trying to do, what is stuck, and what success would look like.