List of LlamaIndex Customers
San Francisco, 94107, CA,
United States
Since 2010, our global team of researchers has been studying LlamaIndex customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased LlamaIndex for AI Frameworks and Libraries from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using LlamaIndex for AI Frameworks and Libraries include: The Carlyle Group, a United States based Banking and Financial Services organisation with 2300 employees and revenues of $3.40 billion, Cemex, a Mexico based Manufacturing organisation with 46063 employees and revenues of $1.56 billion, Jeppesen Sanderson, a United States based Professional Services organisation with 3200 employees and revenues of $810.0 million and many others.
Contact us if you need a completed and verified list of companies using LlamaIndex, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The LlamaIndex customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight | Insight Source |
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Cemex | Manufacturing | 46063 | $1.6B | Mexico | LlamaIndex | LlamaIndex | AI Frameworks and Libraries | 2024 | n/a | In 2024, Cemex implemented LlamaIndex as an AI Frameworks and Libraries solution to accelerate document ingestion, indexing, and agent-driven workflows across operations, supply chain, and customer experience. The LlamaIndex implementation leveraged LlamaCloud and LlamaParse to operationalize access to unstructured data within manufacturing and operations contexts. Implementation work centered on building document ingestion pipelines, parsing diverse file formats, and constructing indexing layers to support retrieval and agent orchestration. Configuration included embedding and index management, retrieval augmented generation flows, and agent workflow orchestration to enable conversational and task automation use cases tied to operational processes. Operational coverage targeted operations, supply chain, and customer experience functions, with pipelines ingesting unstructured sources used by central analytics and functional teams. Connectors and parsing routines were standardized to ensure repeatable indexing and retrieval across business units. Governance and rollout were led by a small data science team that standardized parsing, indexing, and model orchestration workflows to accelerate productionization. That team reportedly spun up about 10 production grade use cases in months, materially increasing delivery velocity according to the customer. | |
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Jeppesen Sanderson | Professional Services | 3200 | $810M | United States | LlamaIndex | LlamaIndex | AI Frameworks and Libraries | 2024 | n/a | In 2024, Jeppesen Sanderson deployed LlamaIndex as part of an engineering and R and D initiative to build a Unified Chatbot Framework using AI Frameworks and Libraries. The implementation used LlamaIndex event driven workflows to standardize agent development across internal teams in the United States, creating a common framework for agent lifecycle, testing, and productionization. The Unified Chatbot Framework consolidated reusable agent templates, runtime orchestration patterns, and developer tooling to reduce per agent engineering effort. LlamaIndex served as the core application platform, enabling standardized agent scaffolding, prompt management, and workflow automation that supported rapid instantiation of new agents. Operational scope covered engineering and R and D teams and onboarded approximately 10 to 11 production products into the framework, aligning multiple product teams to a single agent development approach. There are no named third party integrations documented in the provided context, the focus remained on internal product onboarding and framework standardization. Governance centered on framework ownership, developer onboarding, and configuration standards to ensure consistent agent behavior and maintainability across teams. The rollout emphasized reusability of components and a common set of development guidelines to reduce variance in agent implementations. Outcomes reported include approximately 87 percent development time savings per agent, with effort reduced from approximately 512 to 64 hours per agent, and a projection of large annual engineering hours saved as more products were onboarded. Jeppesen Sanderson s deployment of LlamaIndex demonstrates a measurable shift in how AI Frameworks and Libraries are used to centralize and accelerate conversational agent engineering. | |
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The Carlyle Group | Banking and Financial Services | 2300 | $3.4B | United States | LlamaIndex | LlamaIndex | AI Frameworks and Libraries | 2024 | n/a | In 2024, The Carlyle Group implemented LlamaIndex to support its finance and investment research workflows. LlamaIndex is deployed as part of the firms AI tooling under the AI Frameworks and Libraries category and was used to construct retrieval-augmented generation pipelines for document-centered analytics. The implementation specifically leveraged LlamaParse within LlamaIndex to ingest and parse complex investment documents, preserving nested tables, spatial layouts, and embedded images to maintain higher fidelity document representations. Parsed outputs were indexed to support RAG pipelines, with structured extraction and document segmentation to preserve context across multi-page filings and research reports. Deployment covered finance and investment research teams across the firm and integrated parsed document indexes into advanced analytics and research workflows, improving document handling and data integrity as stated. Governance efforts concentrated on parsing configuration, indexing standards, and access controls for parsed assets to ensure consistent data fidelity for downstream RAG and analytics use cases. |
Buyer Intent: Companies Evaluating LlamaIndex
- athenahealth, a United States based Professional Services organization with 7000 Employees
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