AI migration: making existing software AI-ready, step by step
Most companies do not start from a green field. They have grown systems, databases and processes — and want to use AI there without rebuilding everything. We guide SMBs and enterprises through AI migration: from system architecture consulting to the ongoing migration of legacy systems.
Legacy system AI migration without a big bang
A legacy system does not have to be replaced to become AI-ready. Usually it is enough to create interfaces in the right places: make data accessible, break workflows into events, add a layer where models and agents can work safely. We migrate step by step — each step runs in production before the next one starts.
That reduces risk and keeps daily business running. And it shows early whether migrating software to AI systems delivers the expected value, before large parts are rebuilt.
AI system architecture consulting: target architecture first
Before we migrate, we clarify the target: where should models and agents sit in your architecture? Which data do they need, and in what quality? What stays deterministic, what does AI take over? This AI system architecture consulting produces a target architecture and a migration path with clear stages.
- Inventory: systems, data flows, interfaces, pain points
- Target architecture with clearly defined places for models and agents
- Data integration: APIs, events, vector stores, permissions
- Migration path in stages, each usable in production on its own
Cloud AI migration in the EU or Switzerland
AI workloads often need different infrastructure than the existing software: GPU capacity, model APIs, vector databases. We plan the cloud AI migration so that data protection under GDPR and the Swiss FADP is preserved — with hosting in the EU or Switzerland when your data requires it — and so that operating costs are transparent from the start.
AI agent migration pipeline: from scripts to agents
Many companies already have automations: scripts, RPA bots, workflows in low-code tools. Often they are brittle and hard to maintain. We migrate such automations into an AI agent pipeline — with agents that understand exceptions instead of stopping at every deviation. Existing logic is not thrown away but kept as the deterministic core.
Frequently asked questions about AI migration
Do we have to replace our existing system?
In most cases, no. We create interfaces and an AI layer next to the existing system. Only what truly cannot be integrated in a meaningful way gets replaced.
How long does an AI migration take?
That depends on your system landscape. Because we migrate in stages, you see the first production results early — the total duration is agreed together after the inventory.
Can our data stay in Europe?
Yes. We plan hosting and model selection so that data can stay in the EU or Switzerland when your requirements demand it — including self-hosted models.
What happens to our existing automations?
Proven logic is kept as the deterministic core. AI agents are added where exceptions are handled manually today or where scripts break regularly.
How AI-ready is your system landscape?
Tell us about your systems — in the intro call we give you a first assessment of where a migration would start.