Navan (NAVN) investor relations material

Technology and AI strategy

• Early focus on automating manual business travel processes, moving from phone-based to browser-based systems, and building a robust API infrastructure for global connectivity.

• Machine learning and AI teams established as early as 2017, enabling personalized travel recommendations and efficient booking experiences.

• GenAI integration accelerated service speed, allowing bookings and changes via conversational AI (Ava), blending AI and human support for seamless user experience.

• 50% of AI interactions now use proprietary models, improving customer satisfaction and reducing costs, with rapid adoption and repeat usage of new AI-driven products like Navan Edge.

• Headless and API-driven architecture enables integration with various platforms, meeting users where they are and supporting enterprise customization.

Growth, financials, and guidance

• Acquisition of BoomPop, an AI-native meetings and events company, aims to automate event planning and expand offerings, with expected revenue synergies and accretive impact by fiscal 2028.

• New signed GBV up 60% year-over-year to $4 billion, reflecting strong enterprise sales and future growth potential.

• Revenue guidance for fiscal 2027 raised to 32% year-over-year growth, with acceleration seen across bookings, revenue, and new product adoption.

• Product-led growth (PLG) and sales-led growth (SLG) both contributing, with PLG cycles translating to revenue quickly and net new business exceeding $4 billion.

• Focus on prudent reporting and high-confidence guidance, emphasizing usage-based revenue and customer ramp-up dynamics.

Market differentiation and competitive landscape

• Deep partnerships with travel suppliers ensure comprehensive content, competitive pricing, and unique features like support for low-cost carriers and direct NDC connections.

• AI-driven automation and orchestration between AI agents and human agents create operational efficiencies and high gross margins (75%).

• Competitors face challenges replicating the integrated online infrastructure and AI capabilities, as legacy systems rely heavily on manual processes.

• Enterprise customers increasingly demand AI-powered solutions, driving modernization and competitive advantage.

• Key KPIs to watch include model usage rates and the proportion of automated interactions, which directly impact gross margins and scalability.