Glean's Embedding Model for Enterprise-Adapted AI
Hosted by Jason Liu and Manav Rathod
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What you'll learn
Enterprise Embedding Model Creation
Build and fine-tune custom embedding models using MLM, contrastive learning, and user feedback data.
Data Adaptation Strategies
Apply synthetic and real company data to overcome cold-start problems and adapt models to specific contexts.
RAG Architecture Integration
Implement embedding models within RAG systems to create company-specific AI search and generation tools.
Why this topic matters
Custom embedding models are the key to making AI work effectively in business settings. By learning to adapt these models to specific company contexts, you'll be able to build AI systems that truly understand organizational language and deliver real value—a critical skill as enterprise AI adoption grows.
You'll learn from
Jason Liu
Consultant at the intersection of Information Retrieval and AI
Jason has built search and recommendation systems for the past 6 years. He has consulted and advised a dozens startups in the last year to improve their RAG systems. He is the creator of the Instructor Python library.
Manav Rathod
Software Engineer at Glean
Manav is representing Glean and works on the Search and Intelligence Team.
Representing
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