I will build an agentic real estate ai chatbot with langgraph and custom sql rag


Sobre este Serviço
SCALE YOUR PROPTECH BUSINESS WITH AN EX-ORACLE AI ARCHITECT
Generic AI wrappers fail when processing complex real estate interactions. If a client asks to "find a 3-bed home near good schools under $600k and book a viewing next week," standard chatbots freeze. You need a stateful, deterministic AI Agent that dynamically queries databases, executes cross-selling logic, and coordinates calendar bookings seamlessly.
I build custom, production-grade Real Estate Conversational Agents leveraging LangGraph, FastAPI, and robust relational data models.
WHAT I ENGINEER FOR YOU:
LangGraph Orchestration: Stateful agents , multi-turn requirement adjustments, and conversational loops without context drops.
Custom Natural Language SQL RAG: Precision regex/string text token extractors that automatically parse location, configurations, budget restrictions, and feature keywords directly into database logic.
Fallback & Cross-Sell Logic: If exact matches don't exist, the system adjusts filters dynamically to suggest the closest comparable properties.
Automate your property funnels with high fidelity. CONTACT ME NOW to review your database schema layouts before ordering!
Conheça mais sobre Mehul Gilotra
AI Engineer Agentic RAG Chatbots Full Stack
- A partir deÍndia
- Membro desdenov. de 2023
- Responde em aprox.:1 hora
Idiomas
Hindi, Inglês
Outros serviços de Desenvolvimento de IA que eu ofereço
Perguntas frequentes
How does the chatbot translate natural language text into secure database queries?
I build custom structured tools that safely parse parameters (location, budget, room layouts, and features) from user strings using secure matching techniques and regex token filtering. These clean values are mapped into optimized SQL queries with explicit parameter.
What happens if a buyer searches for a property configuration that is completely out of stock?
The agent uses an intelligent fallback architecture. Instead of failing with a "no results found" error, it expands query filters dynamically within a strict margin (e.g., up to 130% of budget or adjacent layouts) to cross-sell and recommend the next closest match.
