9 posts
The AI-native open-source vector database — built for semantic search, RAG, and embedding storage with a developer-friendly API.
Converting complex PDFs, tables, and multi-column layouts into structured Markdown for AI processing — all with a permissive MIT license.
The most popular LLM application framework — building RAG pipelines, agent chains, and LLM-powered applications with 700+ integrations.
The leading data framework for LLM applications — connecting LLMs to your data with advanced indexing, retrieval, and query engines.
The most scalable open-source vector database managing trillion-scale vector datasets with GPU-accelerated indexing and hybrid search.
Adding AI-powered search to your existing Postgres database with no separate infrastructure — a PostgreSQL extension for vector similarity search.
A high-performance vector search engine written in Rust with filtering, quantization, and horizontal scaling for production RAG.
Extracting and chunking text from PDFs, HTML, Word docs, and images for RAG pipelines — the enterprise document preprocessing library.
An AI-native vector database with built-in vectorization modules, hybrid search, and seamless integration with any LLM.