LlamaIndex

Free Tier, PaidAgentic Process Automation

Framework for building LLM applications by connecting data sources to language models.

Founded by: Jerry Liuin 2022

Use LlamaIndex to build applications that connect custom data to large language models (LLMs). It provides data connectors, indexes, retrieval tools, and agents that make it easy for developers to build retrieval-augmented generation (RAG) workflows. LlamaIndex simplifies chunking, embedding, and querying data so you can feed relevant context into LLMs for accurate, cost-effective answers. Ideal for startups and enterprise teams creating custom AI products.

Use Cases

Building AI search over proprietary documents

Powering chatbots with organization-specific knowledge

Creating RAG workflows for customer support

Developing AI copilots for internal tools

Integrating private databases into LLM applications

Prototyping and deploying scalable AI services quickly

Integrations

Claude by Anthropic

Microsoft Azure

Weaviate, Milvus, Chroma ,Databricks,

Standout Features

Data connectors for ingesting structured and unstructured data

Advanced chunking and embedding management

Query engine with semantic retrieval capabilities

Integrations with leading vector databases

Cloud-hosted RAG endpoints for production use

Built-in support for building AI agents and toolchains

Who is it for?

Software Engineer, Machine Learning Engineer, AI Engineer, Data Scientist, Product Manager, CTO

Tasks it helps with

Ingest data from diverse sources like PDFs, SQL, Notion, and APIs

Create vector indexes for fast retrieval of relevant chunks

Integrate with vector databases for scalable storage

Enable retrieval-augmented generation with context-aware prompts

Chain tools and agents for complex workflows

Deploy cloud-hosted endpoints for production apps

Overall Web Sentiment

People love it

Time to value

Quick Setup (< 1 hour)

Tutorials

Reviews

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