LlamaIndex

LlamaIndex

Connects data sources to large language models

About LlamaIndex

Simplify's Rating
Why LlamaIndex is rated
B
Rated C on Competitive Edge
Rated A on Growth Potential
Rated B on Rating Differentiation

Industries

Data & Analytics

Enterprise Software

AI & Machine Learning

Company Size

51-200

Company Stage

Series A

Total Funding

$27.5M

Headquarters

San Francisco, California

Founded

2023

Overview

LlamaIndex.ai provides a data framework that enables businesses to connect their custom data sources to large language models (LLMs), which are AI systems capable of understanding and generating human-like text. The framework supports various types of data, including structured data from sources like Excel and SQL, semi-structured data from APIs such as Slack and Salesforce, and unstructured data like web pages and images. This versatility allows businesses of all sizes to gain insights from their data. Operating on a business-to-business (B2B) model, LlamaIndex.ai likely uses a subscription-based revenue model, offering clients ongoing access to its services. The company's goal is to empower businesses to leverage their data effectively, facilitating data-driven decision-making.

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Simplify's Take

What believers are saying

  • LlamaIndex's involvement in AGNTCY boosts its AI agent interoperability leadership.
  • The $19M Series A funding supports team expansion and product development for LlamaCloud.
  • Partnership with NVIDIA enhances AI solutions and market reach for enterprise automation.

What critics are saying

  • Competition from Microsoft's AutoGen framework challenges LlamaIndex's market position.
  • NVIDIA's Nemotron models may attract LlamaIndex's potential customers.
  • AGNTCY's industry standards may require costly adaptations for LlamaIndex.

What makes LlamaIndex unique

  • LlamaIndex offers a unique data framework connecting custom data sources to LLMs.
  • It supports structured, semi-structured, and unstructured data integration for diverse business needs.
  • LlamaIndex's Agent Document Workflow enhances AI agents' decision-making in complex processes.

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Funding

Total Funding

$27.5M

Above

Industry Average

Funded Over

2 Rounds

Notable Investors:
Series A funding typically happens when a startup has a product and some customers, and now needs funding to scale. This money is usually used to grow the team, expand marketing, and improve the product. Venture capital firms are frequently the main investors here.
Series A Funding Comparison
Above Average

Industry standards

$15M
$8.2M
Discord
$15M
Canva
$19M
LlamaIndex
$30M
Kalshi

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Unlimited Paid Time Off

Company Equity

Meal Benefits

Growth & Insights and Company News

Headcount

6 month growth

↓ -11%

1 year growth

↑ 0%

2 year growth

↑ 17%
VentureBeat
Mar 6th, 2025
A Standard, Open Framework For Building Ai Agents Is Coming From Cisco, Langchain And Galileo

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. One goal for an agentic future is for AI agents from different organizations to freely and seamlessly talk to one another. But getting to that point requires interoperability, and these agents may have been built with different LLMs, data frameworks and code.To achieve interoperability, developers of these agents must agree on how they can communicate with each other. This is a challenging task. A group of companies, including Cisco, LangChain, LlamaIndex, Galileo and Glean, have now created AGNTCY, an open-source collective with the goal of creating an industry-standard agent interoperability language. AGNTCY aims to make it easy for any AI agent to communicate and exchange data with another.Uniting AI Agents“Just like when the cloud and the internet came about and accelerated applications and all social interactions at a global scale, we want to build the Internet of Agents that accelerate all of human work at a global scale,” said Vijoy Pandey, head of Outshift by Cisco, Cisco’s incubation arm, in an interview with VentureBeat. Pandey likened AGNTCY to the advent of the Transmission Control Protocol/Internet Protocol (TCP/IP) and the domain name system (DNS), which helped organize the internet and allowed for interconnections between different computer systems. â€śThe way we are thinking about this problem is that the original internet allowed for humans and servers and web farms to all come together,” he said

LlamaIndex
Mar 5th, 2025
Announcing our Series A and LlamaCloud General Availability — LlamaIndex - Build Knowledge Assistants over your Enterprise Data

LlamaIndex is a simple, flexible framework for building knowledge assistants using LLMs connected to your enterprise data.

WowTale
Mar 4th, 2025
LlamaIndex Secures $19M for AI Agents

LlamaIndex, a startup founded in 2023 by former Uber researchers Jerry Liu and Simon Suo, has raised $19 million in a Series A funding round led by Norwest Venture Partners, with participation from Greylock. This brings their total funding to $27.5 million. The company focuses on developing custom agents using unstructured data. The funds will be used to expand their 20-member team and enhance product development, particularly for their enterprise service, LlamaCloud.

TechCrunch
Mar 4th, 2025
LlamaIndex launches a cloud service for building unstructured data agents

In part to help fund LlamaCloud's development, LlamaIndex recently raised $19 million in a Series A funding round that was led by Norwest Venture Partners, and saw participation from Greylock as well.

VentureBeat
Jan 15th, 2025
Microsoft’S Autogen Update Boosts Ai Agents With Cross-Language Interoperability And Observability

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Microsoft has updated its AutoGen orchestration framework so the agents it helps build can become more flexible and give organizations more control. AutoGen v0.4 brings robustness to AI agents and solves issues customers identified around architectural constraints. â€śThe initial release of AutoGen generated widespread interest in agentic technologies,” Microsoft researchers said in a blog post. â€śAt the same time, users struggled with architectural constraints, an inefficient API compounded by rapid growth and limited debugging and intervention functionality.” The researchers added that customers are asking for stronger observability and control, flexibility around multi-agent collaboration and reusable components. AutoGen v0.4 is more modular and extensible, with scalability and distributed agent networks. It adds asynchronous messaging; cross-language support, observability and debugging; and built-in and community extensions. Asynchronous messaging means agents built with AutoGen v0.4 support event-driven and request-interaction patterns. The framework is more modular, so developers can add plug-in components and build long-running agents. It also enables users to design more complex and distributed agent networks. AutoGen’s extension module simplifies the process of working with multi-agent teams and advanced model clients

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