Agent Infra

An open-source, serverless, and scalable search infrastructure for AI products supporting vector, full-text, regex, and metadata search.

Open-source framework that orchestrates multiple autonomous AI agents through role-playing collaboration, using intuitive crew/agent/task abstractions. CrewAI Cloud and Enterprise add hosting and operational tooling.

Agent-native analytics engineering toolkit: point it at your warehouse and dbt project and it learns the structure, writes transformations, and pinpoints exactly what to fix when schemas drift. Built for analytics and data engineers who want coding agents to do more of the data work.

An open-source LLM application development platform for building, testing, and deploying agentic workflows, RAG pipelines, and AI assistants.

An open-source, visual developer platform for building and orchestrating AI agents, chatbots, and retrieval-augmented generation workflows using a drag-and-drop interface.

Declarative language and toolchain for AI agents: define agents, tools, and prompts in HCL, then compile to a framework or manage them with plan/apply semantics on a hosted platform. Billed as "Terraform for AI agents".

Low-level orchestration framework for stateful, long-running agents, built by LangChain. Provides state management, persistence, and controllable graph execution; used in production by Klarna, Replit, and Elastic. LangGraph Platform adds managed deployment.

LlamaIndex provides document parsing, indexing, and orchestration workflows for AI agents and RAG pipelines. Its suite includes LlamaParse, a VLM-powered cloud parser for complex layouts, and LiteParse, a local open-source alternative for parsing PDFs, Office docs, and images.

A fully managed vector database designed for building AI applications, agent memory, semantic search, and recommendation systems.

Qdrant is a high-performance, open-source vector search engine and database written in Rust. It supports native hybrid search (dense and sparse vectors), built-in multivector support, advanced metadata filtering, and real-time indexing for AI applications like RAG and recommendation systems.

An ingestion and pre-processing platform designed for GenAI that extracts, parses, chunks, and embeds unstructured data from over 64 file types into structured formats ready for AI models and analysis.

Weaviate is an open-source vector database and AI development platform that enables developers to store, index, and search high-dimensional vectors. It includes built-in embeddings generation, a natural language Query Agent, and features for building Retrieval-Augmented Generation (RAG) and personalized AI experiences.