Together provides a framework for enterprises to migrate from closed-source AI models to open-source models (OSM) using managed services, aiming to reduce complexity and accelerate adoption. The process involves discovering suitable models through benchmarks, evaluating them via traffic replay, adapting prompts or weights, and calculating ROI to justify the switch.

  • Discovery relies on defining use cases and filtering candidates using benchmarks like LMArena and FrontierCode.
  • Evaluation prioritizes real-data traffic replay over generic leaderboards to assess accuracy and performance metrics such as cost per task.
  • Adaptation involves iterative tuning of system prompts, sampling parameters, or fine-tuning model weights to match closed-source quality.
  • ROI calculations can show up to 70% cost reduction, helping stakeholders approve the migration based on quantifiable value.
  • Production rollout often starts with canary deployments of 10% traffic to validate stability before full adoption.

This approach allows companies to bypass traditional slow migration cycles by leveraging managed services and iterative testing to achieve faster, lower-risk transitions.