Enterprise Embedding Infrastructure — Multi-Model Management

I will build an enterprise embedding infrastructure — supporting multiple embedding models for different use cases (domain-specific models per department, multilingual models for international content, multimodal models for mixed content), with a unified embedding API abstracting model selection, centralised cost and usage tracking, model versioning for safe model updates without re-indexing, and a management dashboard for embedding operations. Enterprise organisations with multiple AI use cases frequently need different embedding models for different content types — a legal department may need a legal-domain fine-tuned model, an international team needs a multilingual model, and a product team needs CLIP for image-text retrieval; a unified infrastructure serving all models from a single API reduces duplication and provides cross-use-case visibility.

The infrastructure covers multi-model serving, a unified API with model routing by content type, usage and cost tracking per model and team, model version management, A/B testing for model comparison, and a management dashboard.