Proof
Three engagements across insurance, healthcare and enterprise architecture. Real deployments, real economics.
Flagship case · Insurance
The change division of a leading insurance group — the spin-off managing distribution and product development — came to us already convinced. Not "should we use AI," but "how do we scale it without betting the business." A pragmatic, business-driven leadership team with high AI maturity.
"We recognize the role of AI and want to move in stages. Let's start with one agent, evaluate the impact, then expand the funnel. We aim to build a scalable portfolio of AI-driven projects."
Phase 1 — Pilot agent
One agent deployed against a single real workflow. Measured output, ROI analysis before any further commitment.
Phase 2 — Scale-up
On the pilot's proven return: 8 additional agents, a multi-agent management system, and full deployment of the corporate AI platform.
Total direct impact
Delivered with 7–8 FTE over 9 months
faster product ideation & launch
faster product implementation
total addressable market expansion
Also delivered
MedTech
A major IT provider in healthcare ran a tender for an enterprise-grade AI platform. This wasn't an open brief — the client arrived with a detailed technical specification: strict, pre-defined requirements on architecture, performance, and integration. The bar was set before we entered the room.
A system of 7 specialized AI agents addressing cross-functional corporate tasks, deployable cloud or on-premise. Modular architecture designed to scale, delivered in two steps: an MVP with core functionality first, then the full platform with extended integration capabilities.
/ year direct
4 months
new capabilities · workflow throughput · access to insights
Enterprise Architecture
A large enterprise hit a wall: its monolithic IT architecture simply wouldn't allow AI adoption. Leadership understood the "why" and the constraint was real — but there was no path from where they stood to where AI could live.
Architectural consulting — Analysis of the existing architecture, a strategy for decomposing the monolith, and the design of a target AI architecture.
AI strategy — Defining how AI would work inside the new architecture and planning the integration of its components.
Phased migration — Moving to microservices and deploying AI agents gradually inside the new architecture — not in one disruptive cut.
architecture transformation program
24 months
architecture change converted to business value
How we work
Different industries, different scale — the same operating principles underneath every engagement.
We build beside the working business, never through it. AI gets proven in isolated, self-paying cases before anything touches the operation that already makes money.
One agent, one clear return question, measured — then expansion. No enterprise-wide bet on faith.
Your team owns the platform and keeps producing. When we leave, the capability stays.
Every case here started as one pilot — one agent, one ROI question, one workflow. Yours can too.