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How Lettria Unlocked 20% Accuracy Gains with Qdrant and Neo4J

Session Track: App Dev

Session Time:

Session description

In this session, the speaker will present the engineering architecture behind Lettria's GraphRAG system, which delivers over a 20% accuracy improvement while maintaining sub-200ms latency at scale. You will explore the challenges of synchronizing transactional and non-transactional databases, with a focus on designing for high concurrency and building scalable, cost-efficient infrastructure. The talk will delve into the integration of Qdrant and Neo4j, and introduce a custom sync engine purpose-built for real-time data consistency. As a developer, you will gain practical insights into database synchronization strategies, system design for low-latency applications, and efficient use of modern vector and graph technologies in production environments.

Speaker

photo of Romain Albrand

Romain Albrand

Senior ML Engineer

My name is Romain and I have been a ML Engineer at Lettria for 2 years and a half. I am keen on Computer science and Mathematics and I followed a demanding scientific formation with French Prépa and Top Engineering School. I enjoy working on GenAI issues as well as making my work accessible to everyone.