“LlamaCloud's capabilities have played a significant role in helping standardize the development of enterprise knowledge assistants at KPMG. The platform's intuitive interface for configuring RAG pipelines allows us to leverage cutting-edge techniques while maintaining consistency. Its ability to handle multi-modal data embedded within documents during both ingestion and retrieval has been valuable in unlocking insights from our diverse enterprise corpora. LlamaCloud is a foundational capability in our AI & Data Center of Excellence, supporting our efforts to drive systematic AI adoption in a trusted manner.”

"As an Applied AI Data Scientist who holds one of the first ML patents in the U.S. and leads AI development 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.”

"LlamaCloud’s ability to efficiently parse and index our complex enterprise data has significantly bolstered RAG performance. 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."

“Cemex, a global construction materials company, has successfully applied AI across its operations since 2018. LlamaCloud has significantly boosted our development process; from taking weeks to develop to delivering value in a few hours. The impressive capacities of LlamaCloud have enabled us to trust and rely on its parsing and indexing capabilities for our complex documents including those with heavy visual content. LlamaCloud has enabled our team to rapidly deliver multiple use cases to our various business stakeholders”

“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.”

“Leading our organization's internal RAG assistant development, LlamaIndex's rich ecosystem of connectors and thoughtful abstractions has enabled us to rapidly iterate on complex data pipelines and LLM-powered solutions. What truly sets LlamaIndex apart is their team's ability to rapidly integrate cutting-edge research and embrace community contributions, enabling us to continuously experiment with state-of-the-art approaches. Their recent focus on Workflows demonstrates their forward-thinking approach, helping us stay at the forefront of generative AI innovation.”

”Through our collaboration with the LlamaIndex team, we've been able to deeply explore and define the critical capabilities and essential standards for useful research AI assistants. LlamaIndex has proven to be an exceptional Agent development framework that enables our extensive experimentation, while LlamaCloud provides a reliable, packaged cloud service that significantly reduces our operational overhead in delivering services to users. Our engineering team now focuses on the end user application instead of the data infrastructure, leading to much higher engagement on the apps we ship.”