Company: NAVN
Filing Date: 2025-10-10
Form Type: S-1/A
Source: 0001628280-25-044812
Chunk: 186

Company: Navan, Inc.
Filing Date: 2025-10-10
Form: S-1/A
Chunk 186
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 issuing partners in Navan Cloud. Our proprietary infrastructure provides customers with dynamic access to pricing and travel availability, ensuring that users always have the most accurate information at their fingertips. Navan Cloud also simplifies expense management during and after a trip so that customers can understand and accurately capture T&E spend in real time. Navan Cognition: Our New Paradigm in AI-Powered Travel Management From our early founding days, we have invested in AI technologies at the core of our platform. We started with advanced ML capabilities that were revolutionary in this industry in our early days, but we did not stop there. As the technology progressed, so did we. We evolved from deploying customized ML algorithms that deliver best-in-class optimization and personalization to building a sophisticated agentic AI platform that is programmable, modular, and dynamic. We developed a new paradigm in AI-powered travel management through Navan Cognition, our third- generation innovative proprietary AI framework that combines the precision and predictive power of ML with the reasoning capabilities of large language models, or LLMs. Navan Cognition is designed to leverage third-party LLMs in combination with our own proprietary, internally developed software to operate a modular framework of virtual agents using a graph-based workflow. On our platform, Navan Cognition enables us to create, train, deploy, and supervise our specialized virtual agents that can handle many complex tasks previously requiring human intervention, including our virtual agent chatbot, Ava. Within the Navan Cognition framework, our networks of virtual agents identify, categorize, and execute user queries (including distinct tasks) as users interface with our platform. The graph-based workflow identifies and processes the intent behind users’ requests to our virtual agents (such as travel type and preferences) to prompt the LLM models to execute the most relevant workflow in response to requests, while refining user intent to strive for accurate responses and minimal hallucinations. Virtual agent outputs undergo compliance, fact-checking, and logic validation, and supervisory workflows are in place with the goal of preventing hallucinations and unauthorized or unintended actions from reaching users. This framework allows our virtual agents to masterfully manage an increasing number of tasks and requests on our platform, from booking modifications to expense tracking, communicating naturally with users while maintaining strict operational safeguards. For instance, our virtual agents can proactively contact hotels to verify payment arrangements before a traveler's arrival, ensuring a smooth check-in experience. For more information regarding the risks related to the use of AI in our business, see the section titled “Risk Factors—Risks Related to Privacy