Skip to content

Trelis Endpoints

Upload your documents -> Get an Open-AI style endpoint for queries

Who/What is this for?

  • You want to save time setting up RAG/embeddings/retrieval/databases.
  • You want to quickly prototype an AI app that includes document retrieval.
  • You are building a chatbot and need an LLM endpoint that is grounded in a set of your documents.

What do you get?

  • An API endpoint for your documents in just a few clicks.
  • Responses that include verified citations.

What’s in it for you?

  • Save hours of developer time.
  • Mitigate hallucinations from language model responses.
  • Very fast responses.

How does it work?

  • Documents are cleaned and chunked.
  • Retrieval is done for each query using both BM25 (advanced key-word search) and cosine-similarity on document chunks.
  • Relevant chunks are injected into the prompt template.
  • A large language model (Llama 70B on Groq) is prompted to return an answer with citations.
  • Citations are verified against the underlying documents.
  • A response is provided, including citations.