DiscoverBeyond The Pilot: Enterprise AI in ActionHow Booking.com Boosted Agent Accuracy 2x with Mini LLMs with Pranav Pathak
How Booking.com Boosted Agent Accuracy 2x with Mini LLMs with Pranav Pathak

How Booking.com Boosted Agent Accuracy 2x with Mini LLMs with Pranav Pathak

Update: 2025-12-03
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We built AI agents by accident... and it worked. 🤯


In this episode of VentureBeat’s Beyond the Pilot, we go inside the engineering brain of Booking.com with Pranav Pathak (Director of Product Machine Learning). Pranav reveals how they "stumbled" into agentic architectures before the term even existed, how a simple text box revealed a massive missed revenue opportunity (the "Hot Tub" story), and exactly how they stack LLMs, RAG, and Orchestrators to handle millions of travelers without breaking the bank.


If you are building Enterprise AI, this is the blueprint for moving from "cool demo" to production scale.


🚀 In this episode, we cover:




  • The "Hot Tub" Revelation: How free-text AI search exposed features customers desperately wanted but couldn't find.




  • Real ROI Metrics: How LLMs drove a 2x increase in topic detection accuracy and freed up 1.5x of agent bandwidth.




  • The Booking.com AI Stack: A full breakdown of their Orchestrator → Moderation → Agent → RAG architecture.




  • Latency vs. Intelligence: Why they don't use GPT-5 for everything and how they decide between small models and big brains.




  • The Memory Problem: How to build AI that remembers user preferences without being "creepy”.




00:00 Introduction to Agentic Architectures


00:30 Meet Pranav Pathak from Booking.com


01:24 Evolution of Travel Recommendations


03:41 Impact of Gen AI on Customer Service


07:29 Building an Effective AI Stack


10:32 Agentic Systems and Best Practices


13:45 Choosing Between Building and Buying AI Solutions


18:51 Evaluating AI Models for Business Use


24:10 Challenges in Human Evaluation


25:06 Recommendation System and Data Utilization


27:26 Innovations in Travel Search


29:04 Journey and Challenges in ML Integration


32:08 Managing Memory and User Data


38:07 Future of Travel Assistance


41:33 Advice for New AI Integrations


43:57 Final Thoughts and Farewell


đź”— LINKS & RESOURCES:




  • OutShift by Cisco (Sponsor): outshift.cisco.com




  • VentureBeat: www.venturebeat.com




#ArtificialIntelligence #GenAI #Bookingcom #MachineLearning #AgenticAI #LLM #TechPodcast #EnterpriseAI


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Subscribe to the full podcast here:


Apple: https://podcasts.apple.com/us/podcast/venturebeat/id1839285239


Spotify: https://open.spotify.com/show/4Zti73yb4hmiTNa7pEYls4


YouTube: https://www.youtube.com/VentureBeat



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How Booking.com Boosted Agent Accuracy 2x with Mini LLMs with Pranav Pathak

How Booking.com Boosted Agent Accuracy 2x with Mini LLMs with Pranav Pathak

VentureBeat