What does it take to build an agentic system for corporate travel that’s not just smart, but fast and reliable? It takes a lot of hard work beyond choosing an AI model. That’s why we have a dedicated team building tools to benchmark, fine-tune and continuously improve our platform. Our latest work with @NVIDIAAI Nemotron 3.5 Super VL is a great example of how we continuously develop our models. We managed to get early access to NVIDIA AI’s Nemotron 3.5 Super VL model and found it to be a powerful tool. It performed well on intelligence benchmarks and outperformed our production baseline. After fine-tuning, it beat or tied competing models on most measures while delivering the efficiency needed to run agentic systems at scale. It was also our most intelligent model with the shortest latency. We completed the process in a couple of weeks at an estimated cost of $3,000, demonstrating how efficiently we can build and train these tools. We’re sharing what we learned in case it’s helpful to other model builders exploring how to use AI to solve real-world problems, whether in travel, healthcare or another industry. Read more: navan.com/blog/nvidia-ai-tra…

AI is changing how we interact with the world — from searching, clicking and filling out forms to simply asking for what we need. At @Navan's #Navigate26 conference in Paris, I’ll share how that shift is reshaping travel, expense and service. See you on October 15.