Most AI projects don't fail at the model. They fail at the platform underneath — access, evidence, cost, on-call, governance. We build the foundation so production stops being the bottleneck.
Out2Move B.V. 
We don't bundle. The infrastructure foundation, the engineering capabilities, and the packaged solutions are three discrete ways in. Same engineers across all three.
Landing zone, identity, security, observability baseline. Terraform-first, AI-ready by default.
Nine practices, named owners, written outcomes. Pick the one you need or the operating model that ties them together.
Fixed scope, fixed timing, fixed price where it applies. For when you want to start now without scoping for weeks.
Engineers patch. The patches stack. The stack carries the AI initiative. Every year compounds the last, until the platform stops being something you ship from and starts being something you fight.
Cash recovered. Engineer time returned. Audit risk closed. The same operating model returns all three; you don't pick one and lose the other two.
Across the 18 AI pilots we shipped between 2024 and 2026, 83 percent reached production on first attempt when the engagement included a real platform substrate. The remaining 17 percent were paused at the team's request, not because the AI failed.
The pattern is the same in every engagement: the model works in the demo, the rollout exposes the platform underneath. Identity, observability, cost attribution, runbook discipline. When those exist, AI in production is a paperwork problem, not a research problem.
[AI ENGAGEMENTS · 2024–2026 · EU MID-MARKET]We listen. You answer three questions. You get a written summary either way.
⏱ 45 minWe map your constraints onto a paved-road template. Documented, costed, signed off by your security lead.
⏱ 1 weekSix engineers. Daily standup if you want it, weekly written update either way.
⏱ 4–6 wksRunbook, onboarding docs, IaC repo, the next ten things to do. We leave when you can fire us painlessly.
⏱ 1 weekWe don't promise vendor neutrality. We name the tools, why we picked them, and what we'd swap them for. Across cloud foundation, AI services, observability and security.
WE PICK ON DATA RESIDENCY · TOTAL COST OVER THREE YEARS · EXIT RISK. WE SWAP WHEN ONE OF THOSE CHANGES.
An EU mid-market fintech had outgrown a single-account AWS setup three years prior, and DORA was nine months out. We rebuilt the foundation in eight weeks with no platform-team headcount, then handed the keys back.
Read the case→We stopped firefighting. We can finally hire the team we wanted, not the one our last vendor needed.
They wrote ADRs we still use two years later.
First vendor that named what they didn't do.
FinOps savings paid for SecOps inside two quarters. We didn't believe it until we saw the invoices.
The hand-off runbook is the cleanest doc we own.
Six on the engagement, with names and engineering profiles. Named owners on both sides. No project manager standing between you and the team that ships.
Twenty years in cloud platforms. Built the first AWS landing zone for an EU fintech in 2014. Writes the strategy ADRs.
ProfileEx-CISO at a mid-market scale-up. Writes DORA evidence packs that auditors actually read.
ProfileCut 31 percent off three different EU mid-market cloud bills in 2025. Will write the savings line by line.
ProfileBuilt observability stacks for two unicorns. Deletes more alerts than he writes.
ProfileProduction AI shipping since 2022. Cares more about guardrails than about benchmarks.
ProfileRuns the engagements. Holds the team to the written runbook. Calls the trade-offs early.
ProfileLanding zone, security baseline, monitoring, documentation. Ready for adoption in 4–6 weeks.
The operating model. Roles, RACI, governance, FinOps practices. Connected to delivery — not a steering committee.
Two AI use cases with guardrails. Discovery, secure pilot environment, success metrics. 4–8 weeks.
Most DORA evidence packs are PDF graveyards. Here's the minimum your auditor actually needs, generated from the platform itself.
READ →Most mid-market cloud bills have 40% waste. Most of it is in three line items. None of them are EC2.
READ →The pilot worked. The rollout didn't. Three failure modes we keep seeing, and what to design for instead.
READ →All three, in one model. We help with strategy, we implement, and we run parts of the platform afterwards. Knowledge transfer is built into every engagement.
Yes, both. We go deep on each rather than claiming equal depth on every cloud. GCP on request, with honesty about depth.
Two places. We make cloud platforms AI-ready — secure data access, secure compute, observability, cost control, governance. And we help teams adopt AI in engineering itself, including agentic development, with guardrails.
No. We work with AWS, Azure, Kubernetes, Terraform and other modern cloud-native tools. We don't push a vendor unless it's the right fit for the problem.
Coaching, workshops, certification paths and pairing. We measure ourselves by how capable your team is when we leave.
45 minutes, three questions, one written page within 24 hours. Free either way.