In this podcast, Eran Avidan, a machine learning engineer at Intel, talks about the company's Sales AI system. Developed over six years, this innovative system uses a knowledge graph to gather and analyze customer data from both internal and external sources. This enables account managers to gain real-time insights and receive automated recommendations, contributing to a remarkable increase of over half a billion dollars in sales revenue. The knowledge graph is constructed with a microservice architecture that includes components for data loading, transformation, enrichment, storage, and updates, using Neo4j as the graph database. Additionally, the system supports both automated insights and allows analysts to manually explore the graph, making it a powerful tool for sales optimization.
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