Free AI tools for Build a RAG pipeline or LLM app

The most widely adopted framework with composable chains, agents, retrievers, and hundreds of integrations. Battle-tested for production RAG pipelines.

Abstraction layer can be verbose. simpler apps may not need the full framework.

Visual graph editor for building LangChain pipelines without writing Python. Prototype complex RAG flows and export to code.

UI tool for prototyping. production deployments often require direct LangChain code.

Monitors and evaluates RAG pipeline performance with detailed trace logging.

Best value when already using LangChain or LangGraph.

Managed RAG platform with grounded generation and built-in hallucination reduction.

Less flexible than self-hosted stacks for custom retrieval logic.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Extends PostgreSQL with vector capabilities.

When you need separate vector databases.

Provides integrated functionality within the platform ecosystem.

When you need specialized tooling outside scope.

RedisGraph adds graph database capabilities to Redis. Fast in-memory processing.

Skip if the workflow above is not a close match. compare the rest of this list first.

Netdata collects 1000+ metrics per second per node. Single daemon with no dependencies.

Skip if the workflow above is not a close match. compare the rest of this list first.

Prometheus Remote Write sends time-series to external backends. Write to remote_write for long-term storage.

Skip if the workflow above is not a close match. compare the rest of this list first.

BOM Generator creates a bill of materials from your schematic automatically. Quantities, part numbers, and suppliers are listed.

Skip if the workflow above is not a close match. compare the rest of this list first.