CoPilot for Property Search
Helping property agencies manage inquiries by qualifying leads and providing instant answers, freeing staff to focus on closing deals.
Problem
Property agencies are inundated with a high volume of inquiries from potential buyers and renters, making it increasingly difficult for human agents to manage them efficiently. Additionally, the rapid growth of property listings means agents must continuously update their knowledge base, which is both time-consuming and resource-intensive. To address this challenge agencies often face two costly options: hire more people or filter leads more strictly, risking lost prospects—neither of which is sustainable for long-term growth.
Solution
We designed an AI conversational chatbot agent to streamline property inquiries, enhance lead qualification, and support human agents by automating repetitive tasks. Our solution serves property agencies, real estate agents, and potential buyers or renters by providing instant, accurate, and personalized responses to property-related questions. By leveraging advanced natural language processing (NLP) and multi-turn conversation capabilities, we enable the chatbot to engage users in meaningful dialogues, ensuring a smooth and interactive experience. We also integrate API connections with property databases and omnichannel platforms to deliver real-time, context-aware responses.
Recipe
Lead Filtering:
Uses intent recognition to prioritize quality leads and block spam.
Recommendations:
Suggests properties based on preferences via multi-turn AI conversations.
User Tracking:
Logs profiles and history in PostgreSQL and vector database for personalized follow-ups and context retention.
Link Analysis:
Uses RAG to extract details from shared property links and verify them.
Agent Memory:
Employs vector-based memory to retain long-term conversation context and user intent across sessions.
