AI Knowledge Agent for Real Estate Training
~75%
2–4 months
Not disclosed
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.
PressW built an AI chatbot that ingests and indexes 100GB+ of training videos and blog content, using embedding-based search to return context-rich answers with source links across the brokerage's full library.
The system indexes the brokerage's distributed training content and serves instant, source-linked answers to agent queries from a single interface.
Organizations with large agent or field networks and extensive, distributed training libraries that need instant, source-linked answers.
- Brokerage training library: 100GB+ of training videos and blog content (source corpus)
- Content ingestion and indexing pipeline producing embeddings
- Single agent-facing query interface across the full library
- Training video and blog ingestion to text extraction to embedding index
- Agent query to embedding-based semantic search to ranked passages
- Answer output carrying source links back to the underlying training material
80%+ Search Time Reduction
100GB+ Content Indexed
Answers With Source Links
Bryson Greenwood
The brokerage's 100GB+ training library was spread across videos and blogs with no efficient search. The experts ingested and indexed all of it, then put an embedding-based search agent in front of it, so agents ask a question and get a context-rich answer with a link to the source material. Content-search time fell by more than 80%.
It runs on Claude with embedding-based semantic search over the indexed training content, returning answers with links back to the underlying videos and blog posts.
Agents cut the time spent searching for relevant educational content by more than 80%, and over 100GB of training videos and blogs became instantly searchable, with every answer carrying a source link.
The record does not state a timeline. The work covered ingesting and indexing the full 100GB+ library and standing up embedding-based search across videos and blog content.
Organizations with large agent or field networks and extensive, distributed training libraries that need instant, source-linked answers.
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