Quick Links
Features
- 🔒 Self-Hosting in your VPC or on-prem: We have full self-hosting guides for AWS, GCP, Kubernetes generally, and docker compose available on our documentation page here.
- 🧠 Semantic Dense Vector Search: Integrates with OpenAI or Jina embedding models and Qdrant to provide semantic vector search.
- 🔍 Typo Tolerant Full-Text/Neural Search: Every uploaded chunk is vector'ized with naver/efficient-splade-VI-BT-large-query for typo tolerant, quality neural sparse-vector search.
- 🖊️ Sub-Sentence Highlighting: Highlight the matching words or sentences within a chunk and bold them on search to enhance UX for your users. Shout out to the simsearch crate!
- 🌟 Recommendations: Find similar chunks (or files if using grouping) with the recommendation API. Very helpful if you have a platform where users' favorite, bookmark, or upvote content.
- 🤖 Convenient RAG API Routes: We integrate with OpenRouter to provide you with access to any LLM you would like for RAG. Try our routes for fully-managed RAG with topic-based memory management or select your own context RAG.
- 💼 Bring Your Own Models: If you'd like, you can bring your own text-embedding, SPLADE, cross-encoder re-ranking, and/or large-language model (LLM) and plug it into our infrastructure.
- 🔄 Hybrid Search with cross-encoder re-ranking: For the best results, use hybrid search with BAAI/bge-reranker-large re-rank optimization.
- 📆 Recency Biasing: Easily bias search results for what was most recent to prevent staleness
- 🛠️ Tunable Merchandizing: Adjust relevance using signals like clicks, add-to-carts, or citations
- 🕳️ Filtering: Date-range, substring match, tag, numeric, and other filter types are supported.
- 👥 Grouping: Mark multiple chunks as being part of the same file and search on the file-level such that the same top-level result never appears twice