Platform Migration to Claude
Move the workload without losing what works.
What it is
Moving an existing AI workload from another model or provider onto Claude without losing quality or breaking what already works.
Who it's for
Teams consolidating vendors, hitting quality or cost ceilings elsewhere, or standardizing on Claude after an evaluation.
What we deliver
Four phases, no surprises.
Discovery
We map your workflows, identify what is worth doing, define success metrics, and audit what we will be working with. No assumptions.
Design
We design the approach in full — including model selection, integrations, and controls — before a line of code is written.
Delivery
We build with regular demos and continuous feedback. You see progress, you give input, we adjust.
Handover
Documentation, training, and a clean handover to your team — with ongoing support available if you want it.
Every engagement is scoped to your situation, so timelines and investment depend on what you actually need. We will tell you honestly what we think makes sense — including when a smaller scope is the right answer.
Frequently Asked Questions
How do you migrate an AI workload to Claude without breaking it?
Nisco AI Systems audits the existing workload, ports prompts and workflows, then runs a side-by-side quality evaluation against the current baseline before anything is switched. Cutover is phased with a rollback plan, so quality regressions are caught against measured evidence rather than discovered by users.
Which platforms do you migrate from?
Nisco AI Systems works across the major foundation models including GPT and Gemini alongside Claude, so migrations typically move workloads from one of those providers onto Claude. The evaluation step is model-agnostic and measures output quality on the client’s own tasks rather than on public benchmarks.
Does migration reduce our AI costs?
Often, though it depends on the workload. Nisco AI Systems includes a before-and-after cost comparison in every migration, and pairs migration with consumption and FinOps optimization where the numbers justify it. Cost is measured after quality is verified, not instead of it.
Talk to an Anthropic-credentialed team.
30 minutes, no sales pitch. Bring the problem, not a feature list.