Real Estate Data Infrastructure for Property Valuation & Analytics
Clean, normalized property data across MLS sources to power AVMs, market analytics, and property intelligence tools. Spend less time preparing data, more time improving models.
Data Infrastructure
for Property Valuation & Analytics
Normalized Property Data
Access 160M+ property records with standardized schemas across all sources. Consistent field names, data types, and structures reduce data preparation time and improve model reliability.
Reduced Implementation Time
Most valuation platforms are production-ready within days rather than the typical 3-6 weeks data preparation timeline. Pre-normalized data eliminates months of engineering work.
One Partner. Every Data Layer.
Work with a single team for MLS feeds, tax records, parcel data, addresses, geocoding, and ownership information instead of managing multiple vendors.
Comprehensive Comparable Sales
Detailed sales transactions with complete property characteristics, photos, and market context for valuation support. Structured data optimized for comparable selection algorithms.
Historical Data Access
Multi-year historical data for property characteristics, sales transactions, and market trends to support model training, validation, and backtesting.
Unified Data Model
Integrated data from MLS, tax assessors, public records, and market sources in a consistent format across markets, eliminating market-specific data handling.
Normalized Property Data
Access 160M property records with standardized schemas across all sources. Consistent field names, data types, and structures reduce data preparation time and improve model reliability.
Reduced Implementation Time
Most valuation platforms are production-ready within days rather than the typical 3-6 weeks data preparation timeline. Pre-normalized data eliminates months of engineering work.
One Partner. Every Data Layer.
Work with a single team for MLS feeds, tax records, parcel data, addresses, geocoding, and ownership information instead of managing multiple vendors.
Comprehensive Comparable Sales
Detailed sales transactions with complete property characteristics, photos, and market context for valuation support. Structured data optimized for comparable selection algorithms.
Historical Data Access
Multi-year historical data for property characteristics, sales transactions, and market trends to support model training, validation, and backtesting.
Unified Data Model
Integrated data from MLS, tax assessors, public records, and market sources in a consistent format across markets, eliminating market-specific data handling.
How Valuation Platforms Use Data Labs
1/5
Data for Automated Valuation Models
- Access comprehensive property characteristics for subject properties
- Retrieve sales & transfer history for training and comparables
- Pull tax assessed values for validation
- Get AVM estimates for model comparison
- Access historical data for model training and testing
- Property characteristics normalized for feature engineering
2/5
Data for Comparative Market Analysis
- Sales & transfer history with detailed property characteristics
- Property attribute matching for comparable selection
- Market trend data for adjustment factors
- Tax assessment data for verification
- Recent listing data for market activity
- Geographic boundaries for location analysis
3/5
Market Analytics Data
- Historical sales and listing data for trend analysis
- Property characteristics for segmentation
- Tax assessment trends for market analysis
- Transaction volumes and velocities
- Price per square foot calculations
- Absorption rate indicators
4/5
Property Intelligence Data
- Complete property characteristics and details
- Ownership and transfer history
- Tax assessment data and trends
- AVM estimates and confidence scores
- Mortgage and equity information
- Foreclosure and distress indicators
5/5
Portfolio Valuation Data
- Bulk property characteristic access
- Sales comparables for multiple properties
- Tax assessment data at scale
- AVM estimates for portfolio valuation
- Market trend data for portfolio context
- Risk indicators and metrics
Complete Valuation Data Sets
Property Characteristics
- Comprehensive structural details
- Building specifications and quality indicators
- Lot size and features
- Age and condition indicators
- Amenities and upgrades
- Property type and use classifications
- Normalized across MLS sources
Sales Transaction Data
- Sale dates and amounts
- Transaction types (arms-length, foreclosure, etc.)
- Buyer and seller information
- Recording details
- Sale history and frequency
- Price trends over time
Tax Assessment Data
- Current and historical assessed values
- Land and improvement valuations
- Tax amounts and rates
- Assessment methods and dates
- Assessment history trends
- Exemptions and special assessments
MLS Listing Integration
- Active and sold listings (4M+)
- List prices and price changes
- Days on market
- Detailed property descriptions
- Listing status history
- RESO-standardized fields
- Historical listing records
Market Data
- Comparable sales statistics
- Market trends and indices
- Price per square foot metrics
- Absorption rates
- Inventory levels
- Time-series market data
Location Intelligence
- Geographic coordinates (high accuracy)
- School district information
- Neighborhood demographics
- Points of interest
- Walkability and transit scores
- Environmental factors
Property Characteristics
- Comprehensive structural details
- Building specifications and quality indicators
- Lot size and features
- Age and condition indicators
- Amenities and upgrades
- Property type and use classifications
- Normalized across MLS sources
Sales Transaction Data
- Sale dates and amounts
- Transaction types (arms-length, foreclosure, etc.)
- Buyer and seller information
- Recording details
- Sale history and frequency
- Price trends over time
Tax Assessment Data
- Current and historical assessed values
- Land and improvement valuations
- Tax amounts and rates
- Assessment methods and dates
- Assessment history trends
- Exemptions and special assessments
MLS Listing Data
- Active and sold listings (176M+)
- List prices and price changes
- Days on market
- Detailed property descriptions
- Listing status history
- RESO-standardized fields
- Historical listing records
Market Data
- Comparable sales statistics
- Market trends and indices
- Price per square foot metrics
- Absorption rates
- Inventory levels
- Time-series market data
Location Intelligence
- Geographic coordinates (high accuracy)
- School district information
- Neighborhood demographics
- Points of interest
- Walkability and transit scores
- Environmental factors
Why Valuation Platforms
choose Data Labs
Improved Model Accuracy
10-15% improvement in AVM accuracy with access to comprehensive, normalized data across multiple sources.
Faster Model Development
Clean, ML-ready data reduces data preparation time by 60-70%, accelerating model development and deployment timelines significantly.
Broader Market Coverage
Consistent data quality across markets enables deployment of valuation tools in more geographic areas without market-specific tuning.
Enhanced Confidence Scores
Access to data completeness metrics and multiple data sources improves confidence score accuracy and model transparency.
Reduced Operating Costs
Organizations typically see 30-40% reduction in data costs based on customer feedback. Engineering teams refocus on model development rather than data preparation.
Improved Model Accuracy
10-15% improvement in AVM accuracy with access to comprehensive, normalized data across multiple sources.
Faster Model Development
Clean, ML-ready data reduces data preparation time by 60-70%, accelerating model development and deployment timelines significantly.
Broader Market Coverage
Consistent data quality across markets enables deployment of valuation tools in more geographic areas without market-specific tuning.
Enhanced Confidence Scores
Access to data completeness metrics and multiple data sources improves confidence score accuracy and model transparency.
Reduced Operating Costs
Organizations typically see 30-40% reduction in data costs based on customer feedback. Engineering teams refocus on model development rather than data preparation.
Build Valuation Tools with Data Labs
Data Requirements Analysis
Review your valuation methodology, model requirements, and data needs with our team.
Data Exploration
Access sample data for your target markets to evaluate coverage, quality, and suitability for your models.
Technical Architecture
Design data integration approach that supports your valuation platform architecture and performance requirements.
Model Development
Access historical data for model training and validation with support from our data specialists.
Production Deployment
Deploy to production with real-time data access for live valuations and ongoing model monitoring.
Ongoing Optimization
Regular data quality reviews and expansion support as your valuation coverage grows.
