AWS Transform now supports model-to-model migration assessment for generative AI workloads

AWS Transform now provides a model-to-model migration custom transformation for generative AI workloads. This transformation assesses workloads and produces a comprehensive migration plan for moving from third-party providers to Amazon Bedrock. An AI-powered agent scans the codebase, identifies all AI SDKs and models in use, gathers migration requirements through interactive questions, and maps models to Bedrock equivalents with transparent cost comparisons and production-ready code changes. This managed custom transformation helps organizations consolidate AI workloads on AWS, gaining IAM-based security, VPC endpoint isolation, prompt caching, Amazon Bedrock Guardrails, and unified operational tooling via Amazon CloudWatch. The transformation supports migrations from OpenAI, Google Gemini, direct Anthropic SDK usage, and open-source models via LiteLLM or Ollama. It handles direct SDK integrations, framework-wrapped patterns such as LangChain and LlamaIndex, agentic architectures including CrewAI and LangGraph, and multi-provider routing layers-preserving application architecture while swapping only the model layer. The agent includes intelligent cost optimization with tiered model routing recommendations, prompt caching analysis, and model lifecycle awareness that excludes models within 90 days of end-of-life from all recommendations. For some workloads, it recommends Amazon Bedrock's OpenAI-compatible endpoints as a zero-code-change migration path. AWS Transform model-to-model migration is available in all AWS Regions where AWS Transform is offered, at no additional charge beyond standard AWS Transform pricing. To get started, install the ATX CLI and run the mke-genai-model-migration custom transformation against your codebase.