Cloud-to-on-prem AI migration
Already built on OpenAI, Anthropic or Azure endpoints? We migrate your workloads to self-hosted open-source models behind an API-compatible gateway — usually with zero changes to your application code.
Migration without disruption
Workload audit
We inventory your prompts, traffic patterns and quality requirements, and flag which workloads are safe to move first.
Shadow testing
Candidate open models run in parallel with your current provider on live traffic samples, scored on your quality criteria.
Gateway cutover
An OpenAI-compatible endpoint inside your network takes over routing — bulk workloads to local models, with optional API fallback for edge cases during transition.
Decommission
Once quality and cost targets hold, external API dependencies are removed or reduced to a controlled minimum.
Frequently asked questions
Will quality drop when we leave the frontier APIs?
For many enterprise tasks — summarisation, extraction, drafting, internal Q&A — current open models match cloud quality. Shadow testing on your real traffic tells you exactly where the gaps are before you commit.
Do we have to migrate everything at once?
No. Hybrid is the normal end-state for many clients: high-volume routine work runs locally, while rare hard cases can still route to an external API under policy controls.
What does migration typically save?
It depends on volume. Above several million tokens per day, self-hosting usually wins clearly. Run your numbers in our TCO calculator, then have us validate the assumptions.
Will our developers need to rewrite integrations?
Usually not. The self-hosted gateway exposes an OpenAI-compatible API, so most applications only change a base URL and key.