Question 1

Does a RAG Starter Kit include a vector database integration?

Accepted Answer

Yes, every RAG Starter Kit ships with a vector database integration (Pinecone, pgvector, or similar depending on the product) for storing and querying document embeddings. Check the individual product's Technical tab for the exact vector store it uses.

Question 2

Can I swap the LLM provider (OpenAI, Anthropic, etc.)?

Accepted Answer

Most RAG kits are built with a provider-agnostic LLM layer, so switching between OpenAI, Anthropic, or a self-hosted model is typically a config change. See the "AI & Integrations" tab on each product page for its exact supported providers before buying.

Question 3

What document formats does document ingestion support?

Accepted Answer

Ingestion pipelines vary by product: some handle PDFs and DOCX out of the box, others focus on plain text or web pages. Check the Technical tab on each listing for the exact supported file types.

Question 4

How is a RAG starter kit different from an AI chatbot boilerplate?

Accepted Answer

A RAG (Retrieval-Augmented Generation) kit focuses on the retrieval pipeline: chunking, embedding, and querying your own documents so the model answers from your data. An AI chatbot boilerplate is more about the conversational UI and session handling; some products combine both.

RAG Starter Kits Boilerplates.

RAG Starter Kits FAQ

Explore other categories