The Real Estate Data Challenge
Proptech teams need more than MLS data. Investors, agents, and buyer platforms want school rankings, local amenities, crime reporting, new construction news, and neighborhood sentiment pulled into one place. Each of these signals lives in a different corner of the web, and in 2026 the bar for residential search experiences is synthesized context, not just price and square footage. Teams that cannot surface this ambient data quickly lose to AI first competitors that already did the integration work.
Built for These Teams
- Residential search portals challenging incumbent listing sites
- Real estate investment trusts evaluating markets programmatically
- Mortgage and insurance brands enriching property quote flows
Key Workflows
Neighborhood quality scoring
For every listing, pull Google Maps data on nearby schools, grocery stores, transit stops, and parks. Blend ratings and distances into a custom neighborhood score that displays next to the listing price inside the portal.
Local market news monitoring
Track Google News daily for the top 100 metro markets. Capture new construction announcements, zoning changes, and employer moves that shift long term demand, then route summaries to investor memos for the portfolio team.
YouTube market commentary aggregation
Fetch YouTube videos on specific cities and neighborhoods, extract transcripts, and build sentiment trend lines. Share findings with investment committees evaluating new build-to-rent or single-family rental acquisitions each quarter.
Agent and broker intelligence
Pull Google search results for target agents and brokerages to understand their listings, reviews, and transaction commentary. Feed the data into recruiting and referral pipelines for agent-first platforms trying to recruit top producers.
Why Real Estate Teams Choose Scavio
- Rich neighborhood context from Google Maps and reviews
- News signals to detect shifting local market dynamics
- Video transcripts that reflect on-the-ground sentiment
- Per-ZIP or per-metro queries for hyperlocal experiences
- Grounding data for AI concierge and buyer assistant products
Quick Start Example
Here is a Python example running a real estate query:
import requests
response = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": "your_scavio_api_key"},
json={
"platform": "google",
"query": "austin texas tech layoffs housing market 2026",
},
)
data = response.json()
# Process results for your real estate workflow
for item in data.get("organic_results", data.get("products", []))[:10]:
print(item)Platforms You Will Use
Web search with knowledge graph, PAA, and AI overviews
Google Maps
Local business search with ratings and contact info
Google News
News search with headlines and sources
YouTube
Video search with transcripts and metadata
Scavio is designed for teams that need reliable, structured data at scale. Start with the free tier, build your workflow, then scale when you are ready. No lock-in. No complicated setup. Read the quickstart to get your API key and first response in under two minutes.