Evolving Real Estate Analytics: The Journey to ChatDB

Navigating Data with Innovation

The development of PRO marked a significant stride in real estate analytics, enabling the scanning of city parcels to pinpoint underutilized ones. The challenge then shifted to determining where to direct our focus, necessitating a deep dive into demographic shifts and market potentials. This led to the inception of ChatDB, a tool born out of necessity to tackle the intricacies of AI in real estate.

The Genesis of In-House Tools

In 2022, we crafted in-house tools tailored for analyzing demographic trends over time, crucial for spotting submarkets poised for growth. These tools, by correlating construction activity with income level changes, laid the groundwork for integrating with PRO, revealing untapped opportunities in the market.

Encountering ChatGPT's Limitations

The advent of ChatGPT brought excitement but also highlighted a critical shortfall—the tool's inability to process raw demographic data at a detailed census level. This limitation underscored a gap in the market, paving the way for a more specialized solution.

The Birth of ChatDB

ChatDB emerged as a synthesis of large language models and sophisticated data analysis, designed to offer a comprehensive view of any sub-market nationwide. It's built on three pillars:

Data Access: ChatDB's foundation is its ability to tap into structured census bureau data, unveiling patterns and insights previously out of reach.

Data Visualization: With its capability to produce graphs, tables, and maps, ChatDB elucidates trends and locates high-performing submarkets geographically.

LLM Integration for Deeper Insights: While the model itself doesn't analyze structured data directly, ChatDB synthesizes information into natural language, enabling the model to draw connections and interpret data results.

A Leap Forward in Real Estate Analytics

ChatDB signifies a pivotal advance in real estate analytics, demonstrating the potential of software model hybrids in early detection of growth-centric submarkets. Our exploration continues, extending similar strategies to zoning data and multi-layered real estate research tasks.

Author Olivia Ramos
Founder and CEO of Deepblocks, holds master's degrees in Architecture from Columbia University and Real Estate Development from the University of Miami. Her achievements before Deepblocks include designing Big Data navigation software for the Department of Defense's DARPA Innovation House and graduating from Singularity University's Global Solutions and Accelerator programs.