Your legacy systems get analyzed, documented, and modernized with AI-assisted methods — while operations of the old systems continue uninterrupted during migration. One partner, one plan, no double team. AI Operating System path when legacy systems block AI adoption.
A modernized stack is the artefact. A live workflow on top of it is the proof.
Event-sourced, model-agnostic, EU-resident. Replayable. Instrumented for AI consumption.
The 6-component model rebuilt into operating primitives. Composable. Audit-traced.
DSGVO + sectoral. DPIA, model registry, rollback ≤24h, supervisory-ready.
Production by month 06, on the new stack — same delivery commitment as the Accelerator.
Your ops team's pane of glass. Shadow-mode, switch, rollback — without engineering.
The 60–80% defensible. CFO sign-off. Tied to instrumentation in the new stack.
No 9-month replatform that lands in one cutover. Each slice runs in shadow against the old stack first.
Workflow + stack audit. Methodology applied. Slice plan locked.
Data + workflow planes for one workflow. Shadow mode against legacy.
Switch traffic. Legacy retires. Cost-out starts compounding.
Slices 02–04 land on the same plane. Each is faster + cheaper than the last.
Most Modernization engagements surface during Plan 2 or Plan 3 of the unified path — when legacy systems block AI adoption. It runs in parallel with the build, or as a follow-on after the OS is live.
● Not sure which plan you're on? Take the 10-min Diagnostic → ● Already on the path? See the AI Operating System page →
Most engagements start with the Audit — a clear recommendation, migration plan, and cost frame in 2–3 weeks. Stabilization keeps the legacy running while the AI-native rebuild begins.
Replatforms fail because they ship at the end. This ships every slice.
Every slice runs in shadow against the legacy system before traffic switches. Cutovers are anti-climactic on purpose.
The data + workflow planes are written so swapping models or providers is a config change, not a project.
BaFin, FINMA, sectoral regulators — your filing pack is a deliverable, not an afterthought. Supervisory language built in.
If after M06 you don't want slices 02–04, you walk with a working stack and a live workflow. No vendor handcuffs.
No 9-month replatform. The slice plan means your production cutover happens in month 06 — on a narrow workflow — and the rest compounds on a stack that's already live.
Then they should. Our pod can run alongside as senior reviewers and pair-ship instead of leading. Pricing flexes downward; KPIs and guarantees don't.
No. Proven across AWS, Azure, GCP, Hetzner, OVH, on-prem, and air-gapped environments. The data + workflow planes are built so provider swaps are a configuration change, not a project.
Yes — that's a common pattern. Several engagements have replaced 7-figure annual SaaS / managed-service contracts with the new stack. The cost-out memo accounts for it.
The governance plane is the deliverable here. You get a bundled DPIA, model registry, audit log spec, pen-test scope, and supervisory filing kit. Your auditors get a single binder.
If you're already in Plan 2 or Plan 3, the Audit slot is reserved. If you're approaching Modernization standalone, the Diagnostic tells you whether it's the right next move.
Enterprises are deploying AI agents faster than they can govern them. Only a minority operate centralised governance, and Gartner expects 40% of agentic projects to be cancelled by 2027. The governance gap — not the technology gap — separates production-scale agents from expensive experiments.
Jun 10, 2026Data sovereignty is no longer a policy debate — it is an architecture decision. How DACH enterprises should design AI infrastructure that balances sovereignty, performance, and cost without overbuilding.
Jun 6, 2026SAP is acquiring Prior Labs and investing more than one billion euros to build AI purpose-built for structured enterprise data. Here is why tabular foundation models matter and what DACH enterprises running SAP should do now.
Jun 5, 2026Enterprise teams are building AI agents with software practices designed for deterministic systems. The Agent Development Lifecycle is the missing methodology for probabilistic, agentic systems at scale — and the discipline that separates the firms scaling from the ones stuck in the pilot.
Jun 3, 2026AutoGen, LangGraph, CrewAI and the Claude Agent SDK each have real strengths. But five architectural decisions — orchestration, memory, governance, model routing and observability — determine whether your multi-agent system creates enterprise value. Not the framework you pick.
May 29, 2026A practitioner assessment of Microsoft Copilot Studio's multi-agent capabilities in 2026 — built-in RAG, orchestration patterns, model choice, licensing realities, and the architectural ceiling that decides whether it is enough for your enterprise.
May 28, 2026