customer_support · realestate · workflow
PropHero builds a multilingual multi-agent property investment advisor with continuous evaluation on Amazon Bedrock
Property investment information is expensive or inaccessible, and traditional investment processes are manual, time-consuming, and require extensive market knowledge. PropHero needed a system capable of accurate, contextually relevant advice in Spanish across complex multi-turn conversations covering the full journey from onboarding to settlement.
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 · User query via API Gateway
User queries enter through API Gateway and are routed to the router agent.
Tools used
Amazon BedrockAmazon Bedrock Knowledge BasesLangGraphAWS LambdaAmazon DynamoDBAmazon S3Amazon CloudWatchAmazon EventBridgeAmazon QuickSightAmazon API GatewayAmazon Nova ProAmazon Nova LiteCohere Embed Multilingual v3Cohere Rerank 3.5RagasLangFuse
Outcome
The AI advisor achieved a 90% goal accuracy rate, with over 50% of all users and over 70% of paid users actively engaging it. Customer service workload dropped by 30% and AI costs were reduced by 60% compared to using premium models throughout.
Results
Volume90%
Cost replaced60%
Grounding & classification
Source type: platform led case
44 fields verified against source quotes, 3 dropped as unverifiable.
agentic workflowconversational aiknowledge searchmulti agent workflowragchat transcriptknowledge basemetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedfinancial servicesreal estateaccuracy improvementautomation ratecost reductionemployee productivityplatform led casecustomer supportagentic task executionrag answering