LlamaIndex

About LlamaIndex

LlamaIndex provides a flexible data framework that connects unstructured enterprise data sources to large language models, enabling the rapid development of context-augmented AI agents. This technology streamlines the parsing and indexing of complex documents, allowing businesses to efficiently extract insights and automate workflows without extensive engineering resources.

```xml <problem> Enterprises struggle to connect unstructured data sources to large language models (LLMs), hindering the development of context-aware AI agents. Parsing and indexing complex documents requires significant engineering resources, slowing down insight extraction and workflow automation. </problem> <solution> LlamaIndex is a data framework designed to bridge the gap between unstructured enterprise data and LLMs, enabling the rapid creation of context-augmented AI agents. It streamlines the parsing and indexing of complex documents, allowing businesses to efficiently extract insights and automate workflows. LlamaIndex offers tools to build, deploy, and productionize agentic applications over data, including the core framework for orchestrating single and multi-agent workflows. LlamaCloud provides a secure and seamless way to connect unstructured data to LLM agents, handling data formatting with text, tables, diagrams, and charts correctly for LLM understanding. </solution> <features> - LlamaParse for accurately parsing complex documents with nested tables, spatial layouts, and images - Connectors for file-based data sources like Microsoft SharePoint, Box, and S3 with native access controls and incremental syncing - LlamaCloud for indexing unstructured knowledge bases of PDFs, PowerPoints, Excel sheets, and more - Orchestration framework for single and multi-agent workflows - Support for building full-stack applications with multi-modal retrieval - Integrations with over 40 vector stores, 40+ LLMs, and 160+ data sources - Community-contributed connectors, tools, and datasets via LlamaHub </features> <target_audience> LlamaIndex targets enterprises across finance, manufacturing, IT, and professional services seeking to build custom knowledge assistants and automate workflows using LLMs. </target_audience> ```

What does LlamaIndex do?

LlamaIndex provides a flexible data framework that connects unstructured enterprise data sources to large language models, enabling the rapid development of context-augmented AI agents. This technology streamlines the parsing and indexing of complex documents, allowing businesses to efficiently extract insights and automate workflows without extensive engineering resources.

Where is LlamaIndex located?

LlamaIndex is based in San Francisco, United States.

When was LlamaIndex founded?

LlamaIndex was founded in 2023.

How much funding has LlamaIndex raised?

LlamaIndex has raised 8500000.

Location
San Francisco, United States
Founded
2023
Funding
8500000
Employees
45 employees
Major Investors
Greylock
Looking for specific startups?
Try our free semantic startup search

LlamaIndex

Score: 100/100
AI-Generated Company Overview (experimental) – could contain errors

Executive Summary

LlamaIndex provides a flexible data framework that connects unstructured enterprise data sources to large language models, enabling the rapid development of context-augmented AI agents. This technology streamlines the parsing and indexing of complex documents, allowing businesses to efficiently extract insights and automate workflows without extensive engineering resources.

llamaindex.ai50K+
cb
Crunchbase
Founded 2023San Francisco, United States

Funding

$

Estimated Funding

$8.5M+

Major Investors

Greylock

Team (40+)

Jerry Chen

Jerry Chen

Company Description

Problem

Enterprises struggle to connect unstructured data sources to large language models (LLMs), hindering the development of context-aware AI agents. Parsing and indexing complex documents requires significant engineering resources, slowing down insight extraction and workflow automation.

Solution

LlamaIndex is a data framework designed to bridge the gap between unstructured enterprise data and LLMs, enabling the rapid creation of context-augmented AI agents. It streamlines the parsing and indexing of complex documents, allowing businesses to efficiently extract insights and automate workflows. LlamaIndex offers tools to build, deploy, and productionize agentic applications over data, including the core framework for orchestrating single and multi-agent workflows. LlamaCloud provides a secure and seamless way to connect unstructured data to LLM agents, handling data formatting with text, tables, diagrams, and charts correctly for LLM understanding.

Features

LlamaParse for accurately parsing complex documents with nested tables, spatial layouts, and images

Connectors for file-based data sources like Microsoft SharePoint, Box, and S3 with native access controls and incremental syncing

LlamaCloud for indexing unstructured knowledge bases of PDFs, PowerPoints, Excel sheets, and more

Orchestration framework for single and multi-agent workflows

Support for building full-stack applications with multi-modal retrieval

Integrations with over 40 vector stores, 40+ LLMs, and 160+ data sources

Community-contributed connectors, tools, and datasets via LlamaHub

Target Audience

LlamaIndex targets enterprises across finance, manufacturing, IT, and professional services seeking to build custom knowledge assistants and automate workflows using LLMs.

LlamaIndex - Funding: $7M+ | StartupSeeker