RealGuard
AI automation and conversational workflows for real estate. WhatsApp conversational input → Groq parameter extraction → Java business logic → RERA lookup → in-app EMI calculation → CRM persistence → broker workflow. The LLM extracts parameters while application logic handles authoritative calculations.
Overview
RealGuard is an AI automation and conversational workflow assistant that connects WhatsApp messaging to verified business logic for real estate brokers.
Architecture & Conversational Flow
The system enforces strict separation between conversational interpretation and authoritative domain calculations:
- WhatsApp Webhook Intake: Prospective buyers message through WhatsApp via Twilio webhooks.
- Conversational Parameter Extraction: Groq API (Llama 3) parses unstructured chat to extract budget, preferred locality, BHK requirements, and timeframe into structured JSON parameters.
- Java Business Logic Routing: Spring Boot services validate incoming parameters against application boundaries and route to specific sub-modules.
- RERA Registry Lookup: Queries registered project records to cross-reference developer legitimacy against official regulatory records.
- Deterministic EMI Calculation: Computes loan interest, tenure amortization, and monthly EMI figures strictly within deterministic application code — the LLM never performs financial calculations.
- CRM Persistence & Broker Notification: Stores buyer records and interaction history in MySQL via Hibernate ORM and dispatches structured lead summaries to real estate brokers.
Key Engineering Lessons
- AI for Extraction, Code for Math: Language models interpret conversational nuance, but authoritative financial calculations and compliance rules belong strictly in verified application code.
- Webhook Integrity: Spring Boot verifies Twilio webhook signatures before processing messages to prevent forged broker dispatch events.
- Structured Lead Qualification: Normalizes free-form text conversations into standardized relational CRM records without requiring rigid UI forms.
Implementation Stack
Engineered with Java 17, Spring Boot, MySQL, Hibernate ORM, Twilio WhatsApp API, and Groq API.
Questions about this project?
Feel free to reach out if you'd like to talk about the tech stack, implementation, or a similar project.