do I need a managed platform for embeddings?

Not necessarily.

You don’t need a managed platform for embeddings if:

• you’re generating embeddings with a model/API and storing them yourself,
• you have a relatively simple app,
• you’re okay managing the vector database, indexing, updates, and scaling.

You may want a managed platform if:

• you want faster setup,
• you don’t want to run your own vector store/infrastructure,
• you need scaling, backups, monitoring, and reliability handled for you,
• your app has lots of documents/users or frequent embedding updates,
• you want built-in retrieval/search features and easier ops.

Common setup options

1. DIY

   • Use an embeddings model/API
   • Store vectors in Postgres + pgvector, Pinecone, Weaviate, Milvus, etc.
   • Best if you want control and lower cost

2. Managed vector DB / platform

   • Provider handles hosting, scaling, availability
   • Best for speed and less ops work

3. Full managed AI platform

   • Embeddings + retrieval + sometimes RAG pipelines and evaluation tools
   • Best if you want an end-to-end solution

Rule of thumb

• Prototype or small app: probably no
• Production with growth and low ops tolerance: probably yes

If you want, I can help you choose based on your stack, data size, and expected traffic.