Quick Summary
- ▸ CodeBranch built an AI-powered PropTech platform with interactive maps and conversational AI to evaluate commercial and industrial real estate assets using data-driven insights.
- Delivered a fully functional MVP with interactive maps, conversational AI chat, and statistical engines
- Built a proprietary proxy sales model estimating asset revenue with reliable precision where no market data existed
Overview
Real estate agents and investors evaluating commercial properties often lack the data they need to make confident business decisions — sales figures are guarded, foot traffic is opaque, and comparing locations requires manual research across fragmented sources.
A PropTech startup partnered with CodeBranch to solve this problem by building an AI-powered web application that gives users instant, data-driven insights into commercial and industrial assets. The platform features an interactive map with Google Maps integration, a conversational AI chat powered by OpenAI, and proprietary statistical models — including a proxy sales estimator and a foot traffic analyzer that differentiates raw traffic from engaged visitors.
The application includes an administrative dashboard with membership plans and user tiers. CodeBranch delivered a cost-optimized MVP that the client is currently using as the core product asset for venture capital fundraising.
Industries
Services Provided
Approach
CodeBranch took a consultative co-creation approach, guiding the founders through the process of translating business pain points into technical requirements. The team managed the full backend infrastructure — cloud orchestration via Terraform, geospatial mapping with Google Maps API, demographic data from the Data Commons API, and AI integration with OpenAI — while keeping the client focused purely on product value and market fit.
Through cooperative solution building and iterative product discovery, the project evolved from its initial concept into an advanced analytics platform capable of evaluating foot traffic patterns at the storefront level, estimating proxy sales using proprietary statistical models, and running automated competitive benchmarking against major retail chains.
The conversational AI interface was built with automated data guards for security and off-topic filtering, ensuring reliable responses for end users. The platform was architected specifically for low infrastructure costs, maximizing the startup's runway during their fundraising phase.
The team grew dynamically from 1 to 3 full-stack engineers alongside a software architect and project manager, adapting to the project's velocity at each stage.
Results
- Delivered a fully functional MVP with interactive maps, conversational AI chat, and statistical engines
- Built a proprietary proxy sales model estimating asset revenue with reliable precision where no market data existed
- Automated foot traffic analysis differentiating raw traffic, visits, and engaged visitors
- Enabled competitive benchmarking against major retail chains
- Optimized infrastructure costs for extended startup runway
- Platform serves as core asset for ongoing venture capital fundraising
