Case study
Appraiva: turning property imagery into decision support
Building the technical foundation for AI-driven real estate intelligence.
The business problem
Finding potential property investments can involve reviewing scattered information and manually inspecting neighborhoods. Appraiva was built to help investors and developers discover and assess property opportunities through imagery analysis and enriched property data.
My contribution
I lead the technical direction across product architecture, data systems, AI workflows, and cloud infrastructure. I built the core platform supporting property discovery, enrichment, search, and opportunity analysis, working alongside the team on customer discovery and go-to-market strategy.
The product and architecture decisions
The platform combines visual property-condition analysis with additional property information. My work connects those data and AI workflows to search and analysis capabilities, so the output can be used within an investor’s research process.
This scope extends beyond an individual model: it includes how data is prepared, how the platform services fit together, and how a customer reaches useful information through the product.
What the work enabled
The resulting platform supports property discovery and condition-based analysis through a connected set of data and application workflows. Appraiva’s January 2024 launch announcement reported that early customers were already using the beta platform to find residential investment opportunities.
Public reference
Appraiva’s January 2024 founder and launch announcement describes the platform and identifies my founding role under the title used at the time, Lead Data Architect.