Track property listings, pricing trends, and market dynamics across MLS and listing platforms.
Aggregate real estate data from multiple sources to power market analysis, investment decisions, and property valuation models.
Real estate professionals need comprehensive market intelligence: property listings, historical sales, neighborhood trends, and comparative market analyses. Manual research across multiple listing services, Zillow, Redfin, and county records is time-intensive. Automated real estate scraping creates continuously updated databases that power investment decisions, appraisal models, and consumer-facing property search tools.
A complete real estate intelligence system aggregates listings from MLS platforms, public records, and consumer sites. Enrichment layers add school ratings, crime statistics, walkability scores, and economic indicators. Investors use these datasets to identify undervalued properties, track market cycles, and optimize portfolios. Proptech companies build consumer applications that deliver superior search and recommendation experiences.
Data quality and compliance are critical. MLS data often comes with usage restrictions and license agreements. Public records are generally accessible but require normalization across jurisdictions. Successful teams combine licensed data feeds with ethical web scraping of public information.
Curated using Supabase relationship data and fallback research when live rankings are unavailable.
Start with providers that demonstrate repeatable wins for real estate—look for success stories, governance assurances, and delivery SLAs.
We evaluate coverage quality, integration effort, and enterprise support tiers when ranking real estate solutions.
Authentication churn, legal reviews, and brittle site changes are the most common blockers—we highlight vendors with mitigations baked in.