Building a Big Data AI Assistant in Real Estate

A real estate SME in India wanted to set itself apart as one of the pioneering AI-first companies in this sector. With millions of property records and rising customer expectations for instant answers, leadership recognized that chatbots trained on small datasets would not suffice. They needed an intelligent AI assistant capable of querying complex listings directly from their database—fast, accurate, and available on the cloud.

Challenge Faced

The company’s ambition was clear, but execution was blocked by:

1. Data Fragmentation at Scale – Over 15 million rows of listing data were scattered across a legacy database.
2. Unstructured and Denormalised Tables – Years of growth had left the schema inconsistent, with multiple overlapping fields.
3. Complex Real-Time Joins – Customer queries required mapping across tables in seconds, not minutes.
4. Time-to-Market Pressure – Management wanted to move quickly and brand itself as an AI-driven real estate SME before competitors.

Our Approach

Superteams deployed a fractional Agentic AI Team, combining data engineers, architects, and applied AI developers, to design a scalable solution.

1. Data Foundation Setup
   • Ingested 15M+ rows into a new cloud-native environment.
   • Normalized and structured the data, creating schemas ready for natural-language access.
2. Agentic AI Chat Layer
   • Built a retrieval-augmented generation (RAG) pipeline that mapped natural-language queries into optimized SQL joins.
   • Ensured complex queries (price filters, multi-location searches, amenities) were resolved instantly.
3. Latency & Performance Optimization
   • Introduced caching, real-time indexing, and pre-computation of common queries.
   • Reduced response latency by 42% in test environments.
4. Prototype in 90 Days
   • Following Superteams’ pilot-first approach, the first prototype was shipped in 90 days.
   • Regular sprint demos and client feedback shaped the assistant into a customer-ready product.

Results Achieved (Ongoing Project)

The engagement is still in progress, but measurable milestones have been reached:

• 15M+ rows successfully ingested and normalized, enabling scalable AI access.
• 42% faster query responses, proven during internal benchmarks.
• 90-day prototype delivered, now being tested with real customer queries.
• Qualified leads generated through the AI assistant, giving sales teams ready-to-convert prospects and shortening the sales cycle.

The client is on track to launch a full-scale intelligent chat assistant, drastically reducing reliance on call-center staff while improving customer satisfaction. With Superteams’ fractional pods and ROI-first execution model, the company is building AI capabilities without the overhead of hiring a full in-house team.

Once complete, the client will stand as one of India’s first AI-driven real estate SMEs, ready to scale its customer base with confidence.