LlamaIndex delivers the world's most accurate agentic OCR and document-specific AI workflows, powering complete enterprise automation
Our free plan Includes:
LlamaIndex agents adapt seamlessly to dozens of industry-specific domains and scale effortlessly across hundreds of millions of documents.
faster purchase decisions with brand assistant answering product queries
daily active users of internal company knowledge base
accuracy boost for customer support agents
developer time saved building investment analysis agents
human productivity with AI agents in customer support
From high-accuracy parsing to a fully open agent framework — LlamaIndex gives you fully modular components to build document agents tailored to your data, your workflows, and your infrastructure.
LlamaIndex is a developer-first agent framework that rapidly accelerates time-to-production of GenAI applications with trusted low and high-level abstractions. Optimized for agents, RAG, custom workflows, and integrations.
Start building with core components like state, memory, human-in-the-loop review, reflection, and more.
Fully-featured Python and Typescript SDKs that easily embed into your existing tech stack.
Pre-built third party connectors for LLMs, data sources, vector DBs, and more.
LlamaIndex is a developer-first agent framework that rapidly accelerates time-to-production of GenAI applications with trusted low and high-level abstractions. Optimized for agents, RAG, custom workflows, and integrations.
Start building with core components like state, memory, human-in-the-loop review, reflection, and more.
Fully-featured Python and Typescript SDKs that easily embed into your existing tech stack.
Pre-built third party connectors for LLMs, data sources, vector DBs, and more.
LlamaIndex is a developer-first agent framework that rapidly accelerates time-to-production of GenAI applications with trusted low and high-level abstractions. Optimized for agents, RAG, custom workflows, and integrations.
Start building with core components like state, memory, human-in-the-loop review, reflection, and more.
Fully-featured Python and Typescript SDKs that easily embed into your existing tech stack.
Pre-built third party connectors for LLMs, data sources, vector DBs, and more.
From financial research and due diligence to automated invoice processing, leading banks, hedge funds, and fintechs are transforming workflows with AI.
Risk and protection leaders are turning unstructured data into action—streamlining underwriting, audits, and claim processing.
Leading manufacturers are using AI to extract insights from specs, manuals, and inspection reports—faster and more accurately.
From medical records and handwritten doctor notes to insurance claims, healthcare providers are using AI to streamline clinical and administrative workflows.
We've helped leading AI teams go from prototype to production with real-world results.
As an Applied AI Data Scientist at one of the world's largest Private Equity Funds, I can attest that LlamaIndex's LlamaParse stands out as the premier solution for parsing complex documents in Enterprise RAG pipelines. Its exceptional handling of nested tables, complex spatial layouts, and image extraction is crucial for maintaining data integrity in advanced RAG and agent-based model development.
LlamaIndex’s framework gave us the flexibility we needed to quickly prototype and deploy production-ready RAG applications. The state of the art document parsing capabilities of LlamaParse have been particularly valuable – it handles our complex documents, including tables and hierarchical structures, with remarkable accuracy. The active community support and responsiveness of the LlamaIndex team meant we could quickly troubleshoot and optimize our implementations. What really stands out is how seamlessly we could customize the retrieval pipeline for our specific use cases while maintaining enterprise-grade performance. Salesforce Agentforce team has been leveraging LlamaIndex heavily.
LlamaParse’s ability to efficiently parse and index our complex enterprise data has significantly bolstered RAG performance. Prior to LlamaParse, multiple engineers needed to work on maintenance of data pipelines, but now our engineers can focus on the development and adoption of LLM applications.
LlamaIndex gets you from raw data to real automation — fast.
