Case study · From the Pluris libraryReceipt no. 8619
What sucked
Thousands of agents were missing crucial educational materials: over 100GB of training content spread across videos and blogs with no efficient search made relevant content cumbersome to find.
What they built
PressW built a large California real-estate brokerage an AI chatbot that ingests and indexes over 100GB of training videos and blog content, using embedding-based semantic search to return context-rich, source-linked answers to agent questions from a single interface.
What changed
80%+ Search Time Reduction
Agents cut the time spent searching for relevant educational content by more than 80%.
100GB+ Content Indexed
Over 100GB of training videos and blogs were made instantly searchable.
Answers With Source Links
Responses come with links back to the underlying training material.
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