Model-Agnostic AI Orchestration — Any LLM, No Lock-In | aamp

Use cases Model freedom

Model agnosticism and infrastructure freedom

Plug in any model or provider without rewriting your workflows.

Side-by-side model testing, native cloud connectivity, and no vendor lock-in.

Local open weights and commercial frontier models run side by side, so you can compare accuracy, latency and cost on your own workloads. Connect the enterprise cloud accounts you already have — AWS Bedrock, Azure OpenAI, Google Vertex AI — to satisfy compliance and use existing credits without changing the pipelines underneath.

  • Local + frontier, side by side
  • Bedrock · Azure · Vertex
  • Per-agent model choice
  • No rewrite to switch
01 · What you get

Why teams run this on aamp.

The workflow outlives the model

Models change every quarter. Swapping the model behind an agent is a configuration change, not a migration.

Compare on your workloads, not a leaderboard

Run the same task against a local open weight and a frontier API and read the real accuracy, latency and cost difference.

Use the cloud accounts you already have

Bedrock, Azure OpenAI and Vertex AI connect directly, which keeps procurement and existing credits intact.

02 · How it works

Three steps, one perimeter.

01

Register the providers

Local engines and cloud endpoints sit in the same model registry.

02

Assign per agent

Data classification decides which model each agent is allowed to call.

03

Measure and move

Token accounting per call makes the cost of a switch visible before you make it.

Illustration to come
Platform teams · AI leads · Architecture · Procurement Same perimeter, same audit trail.

Run it where you can defend it.