customer_support · realestate · workflow
StreetEasy deploys two LLM-powered features for instant property FAQs and personalized agent introductions
Home shoppers spent less than 61 seconds on StreetEasy property pages and struggled with traditional FAQ search engines that returned slow, inefficient, and irrelevant results. Separately, finding a well-matched real estate agent was a complex and intimidating process for buyers.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Analyze submitted shopper questions
Questions submitted by shoppers to agents are analyzed and visualized to identify commonly asked topics.
Tools used
large language models (LLMs)LLM-based evaluation
Outcome
StreetEasy deployed two LLM-powered features: an instant, contextually-relevant property FAQ experience and 'Easy as PIE', a personalized agent introduction tool that won the best AI award at Zillow Hackweek 2024, designed to foster trust between shoppers and agents.
What failed first
Traditional web-based FAQ systems depended on slow, inefficient search mechanisms that required users to navigate complex search engines and irrelevant results, causing frustration.
Results
Time savedless than 61 seconds
Volume46%
Running since2024
Grounding & classification
Source type: technical build writeup
21 fields verified against source quotes.
content generationpersonalizationsummarizationknowledge basehuman review describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedreal estatecustomer satisfactiontechnical build writeupcustomer supportai draft human approval