LlamaIndex Secures $19M Funding and Launches LlamaCloud for AI Agent Development

AI agent knowledge development platform LlamaIndex raises $19M - SiliconANGLE

AI agent knowledge development platform LlamaIndex raises $19M LlamaIndex, an artificial intelligence agent development platform that automates knowledge ingestion and work for enterprise data, today announced it has raised $19 million in an early-stage funding. The Series A round was led by Northwest Venture Partners with participation from existing investor Greylock. The company also announced the launch and general availability of its cloud-based managed platform LlamaCloud, a software-as-a-service offering for AI knowledge management that can enhance accuracy for AI agents. LlamaCloud can parse, extract and index large volumes of unstructured data, including PDFs, PowerPoints, images and charts, and turn them into workable knowledge for large language models. Founded in 2023, LlamaIndex began as an open-source project that offered developers a jumpstart for building AI agents over any data. It includes tools such as data connectors, indexes to structure that data and advanced retrieval techniques. AI agents are powered by vast amounts of data and systems such as retrieval-augmented generation. RAG enhances large language model responses by retrieving relevant information from external sources and incorporating that data into the prompt before generating responses. The system depends on highly curated data and well-structured knowledge. "One of the most valuable use cases for large language model agents is automating all knowledge work over unstructured data," said LlamaIndex Chief Executive Jerry Liu. "Because only fragmented tools around data connectors, storage and agent orchestration have been available, developers struggle finding the right techniques and achieving high accuracy for production-grade agents." LlamaCloud is available now as SaaS or in private cloud deployments. It acts as an out-of-the-box solution for building RAG applications from data ingestion through agent deployment. Enterprise customers can secure their data using role-based access controls and single sign-on and protect data access by gating it to development teams and end users. The company also offers commercially available self-serve application programming interfaces for open-source users to access its LlamaParse product, which helps companies ingest and transform unstructured data into a structured format used in RAG applications. In less than two years, LlamaIndex's open-source library has grown to more than 3 million monthly downloads across multiple packages and has more than 38,000 stars on GitHub. The company has also taken on customers such as Rakuten Group Inc., The Carlyle Group Inc. and Salesforce Inc. "LlamaCloud's ability to efficiently parse and index our complex enterprise data has significantly bolstered RAG performance," said Yusuke Kaji, general manager of AI for business at Rakuten. "Prior to LlamaCloud, multiple engineers needed to work on maintenance of data pipelines, but now our engineers can focus on the development and adoption of LLM applications." Earlier this year, LlamaIndex announced a collaboration with Nvidia Corp. on the design and release of an Nvidia AI Blueprint for a multi-agent system that researches, writes and refines any topic using agent-driven RAG. It can be used to write blog posts based on natural language queries, which can then be critiqued and modified by the end-user until the final output has been refined to their liking. The agent system can be customized based on vast amounts of documents and other unstructured data from any source, including enterprise data, making industry research writing easier for knowledge workers.

LlamaIndex launches a cloud service for building unstructed data agents | TechCrunch

Agents are the next big thing in AI. Some define these "agents" differently from others, but the general idea is, they're AI-powered tools that can perform tasks autonomously. The agent hype has reached a fever pitch, but one startup was relatively early to the game: LlamaIndex. Founded by former Uber research scientists, Jerry Liu and Simon Suo, in 2023, LlamaIndex allows developers to build custom agents over unstructured data. "LlamaIndex started as a toy open-source project in November 2022," Liu told TechCrunch. "I became deeply interested in understanding how large language models (LLMs) could be used on top of proprietary data outside their training set, and built an initial set of tools enabling developers to index and include data in their LLM apps." Using LlamaIndex's open-source software, which has racked up millions of downloads on GitHub, developers can create custom agents that can extract information, generate reports and insights, and take specific actions. LlamaIndex provides data connectors and utilities like LlamaParse, which transforms unstructured data into a structured format that can be used for particular AI applications. While there are other open-source frameworks to build AI agents out there, LlamaIndex is differentiated by its suite of data ingestion, data management, and data indexing and retrieval solutions, Liu said. It can connect data from files like PDFs and PowerPoint presentations, as well as apps such as Notion and Slack, with an agent. Salesforce, KPMG, and Carlyle are among the companies using LlamaIndex today, Liu said. "All of these competing solutions solve specific problems at different parts of the generative AI stack, but then it's the developer's responsibility to piece together fragmented solutions to create a working agent," Liu added. "This is a significant pain point that hampers shipping agents to production. LlamaIndex made it our mission to deliver the most secure, accurate, and easy-to-use platform for building end-to-end knowledge agents." LlamaIndex's next chapter is an enterprise service built on top of the company's open-source offerings. Called LlamaCloud, it lets customers create cloud-hosted agents that can work with and manipulate unstructured data in a variety of formats. LlamaCloud can be deployed via a software-as-a-service installation or in a virtual private cloud, and comes with features including role-based access control and single sign-on, Liu said. 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. The new cash brings LlamaIndex's total funding raised to $27.5 million, and Liu says that it'll be used for expanding LlamaIndex's 20-person team, and product development. "We have sufficient runway to take us through initial commercial expansion of our platform," Liu said. "We're betting on a future where developers play a big role in delivering GenAI applications within the enterprise."