{"schemaVersion":1,"profileUrl":"https://nowen.ai/agents/llamaindex-ai","markdownUrl":"https://nowen.ai/agents/llamaindex-ai.md","jsonUrl":"https://nowen.ai/agents/llamaindex-ai.json","name":"LlamaIndex","legalName":"LlamaIndex, Inc.","website":"https://llamaindex.ai","location":"San Francisco","address":{"city":"San Francisco"},"industry":"AI Infrastructure","deliveryModel":"software","marketCategories":{"primary":{"name":"AI Agent Orchestration Software","url":"https://nowen.ai/category/ai-agent-orchestration-software"},"others":[]},"status":{"trust":"unclaimed","text":"Unclaimed: compiled by Nowen from public sources, not reviewed by the company"},"updatedAt":"2026-11-12T14:49:47.655Z","summary":"LlamaIndex builds AI models and tools that help developers and enterprises transform complex documents into structured data for automated workflows.","description":"LlamaIndex is an applied AI lab that builds frontier models and tools for enterprise document parsing and extraction. It helps developers and organizations turn complex, multimodal documents into structured, reliable data for AI agents and automated workflows.","mission":"Our mission is to automate knowledge work, beginning with the hardest frontier: documents.","directory":{"industryName":"AI Infrastructure","agentCount":11,"indexable":true,"hubUrl":"https://nowen.ai/industry/ai-infrastructure"},"categoryDirectory":{"name":"AI Agent Orchestration Software","agentCount":27,"indexable":true,"url":"https://nowen.ai/category/ai-agent-orchestration-software"},"aiReaderFamilies":[],"products":[{"name":"LlamaParse","anchor":"product-llamaparse","type":"Platform","url":"https://www.llamaindex.ai/llamaparse","summary":"Turn complex documents into reliable, structured content that AI agents and applications can use.","description":"LlamaParse is an agentic document processing platform that turns complex documents into AI-ready content and structured data. Parse converts documents into formats such as Markdown, HTML tables, and JSON while handling layouts, tables, charts, images, handwriting, and other content. Extract returns fields and records according to user-defined schemas, with citations and confidence scores. The platform also includes tools to classify documents, split files into logical sections, and index content for search and retrieval. Developers can use its APIs, SDKs, web app, CLI, and MCP server. Deployment options include managed and single-tenant SaaS, customer cloud environments, and on-premises hosting. OCRia-1, a vision-language model powering LlamaParse, is designed for accurate parsing of complex documents, including tables and charts, and can be deployed in a customer's environment.","pricing":{},"features":[{"name":"Complex document parsing","value":"Convert Complex Documents Into AI-Ready Content","valueDescription":"Transform complex or unstructured files into content that downstream AI applications and agents can use, while retaining important document structure and information."},{"name":"Schema-based data extraction","value":"Extract Structured Data With Custom Schemas","valueDescription":"Specify the fields and records your workflow needs, then receive structured JSON that can be used in downstream applications and processes."},{"name":"Benchmark-reported parsing accuracy","value":"Parse Complex Documents Accurately","valueDescription":"OCRia-1's reported benchmark results highlight its ability to parse varied document content, including text, formatting, tables, and charts."},{"name":"Complex table reconstruction","value":"Preserve Complex Table Relationships","valueDescription":"Retaining table structure and connections between values and labels helps make complex tables interpretable for downstream document workflows."},{"name":"Extraction citations and confidence scores","value":"Trace Extracted Fields To Their Sources","valueDescription":"Use citations and confidence scores to inspect the source and certainty of extracted fields, supporting verification and human review."},{"name":"Parsing cost and accuracy controls","value":"Balance Processing Cost And Accuracy","valueDescription":"Choose parsing settings to suit document requirements and budgets, or use automatic page-level tier routing. OCRia-1 is presented as an economical parsing option, with a stated cost of less than half a cent per page."},{"name":"Indexing for search and retrieval","value":"Prepare Document Content For Search And Retrieval","valueDescription":"Organize parsed content with chunking and embeddings so it can be used in search, retrieval, and RAG workflows."},{"name":"Developer and agent integrations","value":"Integrate Document Processing Into Existing Workflows","valueDescription":"Access Parse and Extract through developer tools and agent integrations, and connect document processing to existing applications and workflows."},{"name":"Flexible deployment","value":"Deploy In The Environment That Fits Your Needs","valueDescription":"Choose a managed service or deploy in a dedicated, customer-controlled cloud or on-premises environment. OCRia-1 is available through LlamaParse or for deployment in a customer's environment."},{"name":"Broad file format support","value":"Process Documents Across 130+ File Formats","valueDescription":"Bring varied document and media formats into a common processing workflow, including scanned documents and files containing handwriting."},{"name":"Automated parsing error correction","value":"Detect And Correct Parsing Errors Automatically","valueDescription":"Use recursive checks to identify and correct parsing errors, supporting processing of challenging scans and multimodal documents."},{"name":"Chart parsing","value":"Turn Charts Into Structured Data","valueDescription":"Convert chart and graph content into structured data for use in downstream document workflows."},{"name":"Document classification","value":"Categorize Documents Using Natural-Language Rules","valueDescription":"Apply natural-language rules to categorize documents as part of document processing and workflow automation."},{"name":"Document splitting","value":"Separate Combined Files Into Logical Documents","valueDescription":"Turn combined files into individual documents or meaningful sections to prepare them for subsequent processing."},{"name":"Multilingual parsing","value":"Process Documents In 100+ Languages","valueDescription":"Support document processing across a broad range of languages with out-of-the-box multilingual compatibility."},{"name":"Low-latency parsing","value":"Process Documents With Low Latency","valueDescription":"OCRia-1 is positioned for low-latency document parsing, supporting faster processing of document workloads."}]},{"name":"LiteParse","anchor":"product-liteparse","type":"Product","url":"https://www.llamaindex.ai/liteparse","summary":"Parse documents locally and quickly into AI-ready text and structured output, without cloud services, API keys, or LLM tokens.","description":"LiteParse is an open-source document parser from the team behind LlamaParse. It processes PDFs, Office documents, and images locally, without cloud services or API calls, and produces text and structured output for AI agents and programmatic workflows. Its local parsing combines embedded-text extraction with OCR for scanned content, and provides positional data such as bounding boxes. LiteParse is available through a CLI and developer libraries, with browser-based parsing also offered through a WebAssembly demo.","pricing":{},"features":[{"name":"Local document processing","value":"Keep Document Processing On Your Machine","valueDescription":"Parse documents locally without a cloud dependency or API calls, keeping document data on the machine."},{"name":"Multi-format parsing","value":"Parse Documents With One Tool","valueDescription":"Handle PDFs, Office documents, and images through one interface and a consistent parsing pipeline."},{"name":"Text extraction and OCR","value":"Extract Text From Scanned Documents","valueDescription":"Combine embedded-text parsing with OCR for scanned content. Use built-in Tesseract.js or connect an external OCR server."},{"name":"Spatial text and bounding boxes","value":"Locate Text In Source Documents","valueDescription":"Use bounding boxes and page positions to identify where parsed text appears in its source document, supporting citations and downstream workflows."},{"name":"Programmatic output formats","value":"Send Parsed Content To Downstream Tools","valueDescription":"Choose Markdown, plain text, or JSON output and use parsed content in programmatic workflows, including pipelines that send it to LLMs or vector stores."},{"name":"Developer and automation interfaces","value":"Integrate Parsing Into Developer Workflows","valueDescription":"Run LiteParse from the CLI or use its developer libraries and Python wrapper in scripts, CI/CD pipelines, agent workflows, and batch processing."},{"name":"Open-source availability","value":"Use An Open-Source Parser","valueDescription":"Access the open-source parser and its repository on GitHub."},{"name":"Screenshot capture","value":"Capture Pages For Visual Analysis","valueDescription":"Pair extracted text with page screenshots when an agent needs visual context for deeper multimodal reasoning."},{"name":"Browser-based WebAssembly parsing","value":"Parse PDFs Directly In Your Browser","valueDescription":"Use the browser demo to parse PDF bytes locally with WebAssembly, without requiring a server."}]},{"name":"LlamaIndex framework","anchor":"product-llamaindex-framework","type":"Platform","url":"https://www.llamaindex.ai/llamaindex","summary":"Build context-aware AI applications and agents faster with reusable components, flexible integrations, and support for retrieval-augmented generation.","description":"LlamaIndex is an open-source framework for building context-aware AI applications and agents. It provides extensible building blocks such as memory, state management, and human-in-the-loop capabilities, plus Python and TypeScript SDKs and integrations with LLMs, tools, and data sources. Developers can use it to create retrieval-augmented generation pipelines and production-ready AI applications, with control to customize components and workflows.","pricing":{},"features":[{"name":"Agent building blocks","value":"Customize Agent Components","valueDescription":"Use and adapt core agent components such as memory, state management, and human-in-the-loop capabilities to fit specific application workflows."},{"name":"LLM, tool, and data integrations","value":"Connect Models, Tools, And Data","valueDescription":"Build applications with connections to LLMs, tools, and data sources, including support for new releases and integrations."},{"name":"Retrieval-augmented generation support","value":"Build Context-Aware RAG Applications","valueDescription":"Create and customize retrieval-augmented generation pipelines that bring data into AI applications as relevant context."},{"name":"Agent workflow orchestration","value":"Orchestrate Multi-Step Agent Workflows","valueDescription":"Coordinate steps, loops, parallel paths, and multiple agents with control over state transitions and execution flow."},{"name":"Python and TypeScript SDKs","value":"Build With Python Or TypeScript","valueDescription":"Use supported Python and TypeScript SDKs to develop applications and integrate the framework into an existing development stack."},{"name":"Open-source framework","value":"Build And Deploy Without Restrictions","valueDescription":"Use the open-source framework to build applications with control over implementation and without restrictions on production or commercial use."},{"name":"RAG pipeline development tools","value":"Develop And Debug RAG Pipelines","valueDescription":"Use framework resources and components to create, trace, and debug retrieval-augmented generation applications."}]},{"name":"Workflows","anchor":"product-workflows","type":"Platform","url":"https://www.llamaindex.ai/workflows","summary":"Build controlled, stateful AI workflows that coordinate agents, human review, and application logic across multi-step processes.","description":"Workflows is an open-source framework for building controlled, multi-step agentic systems. Developers can chain steps, add loops and parallel paths, and combine multiple agents in workflows that can start, pause, and resume statefully. Workflows also supports asynchronous execution, type-safe control over data passed between steps, and human-in-the-loop review. It can be used with Python and TypeScript applications.","pricing":{},"features":[{"name":"Multi-step orchestration","value":"Coordinate Complex AI Processes","valueDescription":"Developers can orchestrate multiple steps, agents, loops, and parallel paths in a single workflow, supporting more complex applications than isolated steps."},{"name":"Type-safe step control","value":"Control Data Across Workflow Steps","valueDescription":"Type-safe programs let developers specify how arguments and data pass between steps, providing precise control over workflow behavior."},{"name":"Asynchronous execution","value":"Run Workflows Asynchronously","valueDescription":"Asynchronous execution supports fast workflow runs and integration with Python applications, including FastAPI."},{"name":"Event-driven state management","value":"Pause And Resume Stateful Workflows","valueDescription":"Start workflows on demand, pause them, and resume them while maintaining state across the process."},{"name":"Human-in-the-loop workflows","value":"Include Human Review In Workflows","valueDescription":"Developers can incorporate human-in-the-loop review alongside document processing and other workflow steps."},{"name":"Open-source framework","value":"Build And Deploy Open-Source Applications","valueDescription":"Developers can use the open-source framework to build applications with control over their implementation, including production and commercial applications."}],"marketCategories":[{"name":"AI Agent Orchestration Software","url":"https://nowen.ai/category/ai-agent-orchestration-software"}]},{"name":"LlamaAgents","anchor":"product-llamaagents","type":"Product","url":"https://www.llamaindex.ai/contact","summary":"Build and deploy document agents that automate reliable workflows from document ingestion and extraction through reasoning and action.","description":"LlamaAgents is a low-code builder for developing and deploying document agents from natural-language instructions. It enables developers and enterprises to build reliable document workflows spanning ingestion, extraction, reasoning, and automation.","pricing":{},"features":[{"name":"Document workflow automation","value":"Automate Document Workflows","valueDescription":"Connect document ingestion, extraction, reasoning, and automation in workflows built around documents."},{"name":"Natural-language agent development","value":"Build Agents From Natural Language","valueDescription":"Create document agents using natural-language instructions with a low-code builder."},{"name":"Document agent deployment","value":"Deploy Document Agents","valueDescription":"Deploy document agents developed with the builder to support document workflow automation."}]}],"audiences":[],"segments":[],"faq":[],"comparisons":[],"sources":[{"url":"https://llamaindex.ai","text":"LlamaIndex"},{"url":"https://www.llamaindex.ai/llamaparse","text":"LlamaParse"},{"url":"https://www.llamaindex.ai/liteparse","text":"LiteParse"},{"url":"https://www.llamaindex.ai/llamaindex","text":"LlamaIndex framework"},{"url":"https://www.llamaindex.ai/workflows","text":"Workflows"},{"url":"https://www.llamaindex.ai/contact","text":"LlamaAgents"}]}