Revealio: AI-Powered Property Condition Scoring | Production-ready AI Agents Hackathon @ AIBy theBay

Revealio: AI-Powered Property Condition Scoring Created by: Jena Peoples & Bryce Masterson Real-estate investors traditionally spend hours “driving for dollars” — searching for run-down properties that signal potential opportunities. Revealio replaces that entire process with an automated, AI-first pipeline that can evaluate entire cities in minutes. What It Does Revealio collects property-specific imagery from Google Street View, analyzes every exterior with computer vision and dual LLM grading systems, and assigns each home a “distress score.” It then merges that score with ownership data, public records, and geospatial information to produce a refined, high-value lead list for investors. How It Works Akka, Redpanda, Neo4j, OpenAI, Anthropic, Google Maps API, CoreLogic, Python, Docker, Loveable. Revealio impressed the judges with its clean architecture, strong real-estate insight, and near-production-ready pipeline. Integrates with Google Maps / Street View to capture images at scale Uses a multi-agent LLM system (OpenAI + Anthropic) where one model detects distress indicators, and another evaluates the opposite, reducing bias Aggregates data from CoreLogic and other sources Uses Akka to orchestrate distributed, fault-tolerant workflows across all agents and data-processing components Processes entire markets in minutes thanks to a distributed architecture. More: https://ai.bythebay.io/hackathon/revealio%3A-ai-powered-property-condition-scoring