Automated Valuation Models, commonly known as AVMs, have transformed how property values are estimated. What once required weeks of manual appraisal work can now be produced in seconds using data-driven systems. As real estate, finance, and proptech industries continue to scale, one question comes up again and again: what software do people use to make AVMs?
The answer is not a single tool or platform. AVMs are built using a combination of data sources, analytics software, machine learning frameworks, and geospatial tools. In this guide, we’ll break down what software do people use to make AVMs, how these tools work together, and which technologies matter most depending on the use case.
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Understanding AVMs Before Choosing Software
Before diving into what software do people use to make AVMs, it’s important to understand what an AVM actually is.
An AVM is a system that estimates property value using algorithms rather than human judgment. It analyzes large volumes of data such as recent sales, property characteristics, market trends, and geographic factors to generate valuation outputs.
AVMs are commonly used by:
- Mortgage lenders
- Banks and financial institutions
- Real estate platforms
- Investors and analysts
- Government agencies
Because AVMs rely on data, models, and automation, the software stack behind them is critical.
Core Categories of Software Used to Build AVMs
When people ask what software do people use to make AVMs, they are usually referring to a full technology stack rather than a single application.
AVM software generally falls into five major categories:
- Data collection and storage
- Statistical and analytics tools
- Machine learning frameworks
- Geospatial and mapping software
- Deployment and visualization tools
Let’s explore each category in detail.
Data Collection and Data Management Software
Data is the foundation of any AVM. Without accurate and up-to-date data, even the best algorithms fail.
Common Data Sources Used in AVMs
- Property transaction records
- MLS listings
- Tax assessor data
- Rental listings
- Demographic and economic data
- Satellite and geographic data
Software Used for Data Storage and Management
When evaluating what software do people use to make AVMs, data infrastructure plays a huge role.
Common tools include:
- Relational databases like PostgreSQL and MySQL
- Cloud databases such as Amazon RDS or Google BigQuery
- Data warehouses like Snowflake
- NoSQL databases for unstructured data
These systems store millions of property records and allow fast querying for model training and valuation generation.
Statistical and Analytical Software for AVMs
Traditional AVMs relied heavily on statistical modeling before machine learning became dominant.
Popular Statistical Tools
Some of the earliest answers to what software do people use to make AVMs include classic analytics tools such as:
- R
- SAS
- MATLAB
- Python (with libraries like NumPy and Pandas)
These tools are used for:
- Regression analysis
- Hedonic pricing models
- Market trend analysis
- Outlier detection
Even today, statistical software remains important for benchmarking and validation.
Machine Learning Software Used to Build Modern AVMs
Most modern AVMs are powered by machine learning. This is where the biggest shift has happened in recent years.
Common Machine Learning Frameworks
When people ask what software do people use to make AVMs, machine learning frameworks are often the most relevant answer.
Widely used tools include:
- Python-based frameworks such as scikit-learn
- TensorFlow
- PyTorch
- XGBoost and LightGBM
These frameworks allow developers to:
- Train predictive valuation models
- Handle nonlinear relationships
- Incorporate thousands of variables
- Continuously retrain models with new data
Machine learning improves accuracy, especially in dynamic markets.
Geospatial and Mapping Software in AVMs
Location is one of the most powerful drivers of property value. That’s why geospatial tools are essential when discussing what software do people use to make AVMs.
Geospatial Software and Tools
Commonly used tools include:
- GIS platforms
- Mapping APIs
- Spatial databases
- Satellite imagery analysis tools
These tools help models understand:
- Proximity to amenities
- Neighborhood boundaries
- Environmental risks
- Transportation access
- Urban density
Geospatial analysis adds depth that simple numeric data cannot capture.
Property Data APIs and Third-Party Platforms
Many companies building AVMs do not collect all data themselves.
Instead, they rely on:
- Property data APIs
- Listing aggregation platforms
- Public record services
These services provide standardized, cleaned data that can be fed directly into valuation models.
When evaluating what software do people use to make AVMs, these APIs are often just as important as modeling tools.
Visualization and Reporting Software for AVMs
An AVM is only useful if people can understand and trust the output.
Common Visualization Tools
Once valuations are generated, they are often displayed using:
- Dashboard software
- Data visualization libraries
- Custom web interfaces
Popular choices include:
- Business intelligence tools
- Web-based dashboards
- Interactive reporting systems
These tools allow users to explore valuation results, confidence ranges, and market comparisons.
Cloud Platforms Used to Deploy AVMs
AVMs must operate at scale. That’s why cloud infrastructure is a core part of the answer to what software do people use to make AVMs.
Common Cloud Environments
- Public cloud platforms
- Private cloud environments
- Hybrid architectures
Cloud systems support:
- Real-time valuation requests
- High availability
- Model retraining
- Data pipeline automation
Without cloud infrastructure, modern AVMs would struggle to operate efficiently.
Open-Source vs Proprietary AVM Software
Another important distinction when discussing what software do people use to make AVMs is open-source versus proprietary tools.
Open-Source Tools
Pros:
- Flexible
- Cost-effective
- Large developer communities
Cons:
- Require strong technical expertise
- More responsibility for maintenance
Proprietary AVM Platforms
Pros:
- Faster deployment
- Vendor support
- Pre-built models
Cons:
- Less transparency
- Higher cost
- Limited customization
Many organizations use a hybrid approach.
How Financial Institutions Build AVMs
Banks and lenders use AVMs for underwriting, risk assessment, and portfolio monitoring.
Their software stack typically includes:
- Secure data platforms
- Validated machine learning models
- Compliance and audit systems
Accuracy, explainability, and regulatory compliance are top priorities.
How Real Estate Platforms Use AVM Software
Consumer-facing platforms use AVMs to:
- Display estimated property values
- Track market trends
- Support buyer and seller decisions
Their focus is often on:
- Speed
- Scalability
- User-friendly interfaces
This influences what software do people use to make AVMs in consumer markets.
Challenges When Choosing AVM Software
Even with powerful tools, building AVMs is not easy.
Common challenges include:
- Data quality issues
- Market volatility
- Model bias
- Explainability requirements
- Regulatory constraints
Software selection must align with these challenges.
How Accuracy Is Measured in AVM Software
AVM software includes tools for:
- Model validation
- Error tracking
- Performance benchmarking
Metrics such as prediction error and confidence intervals are critical.
This ensures valuations are reliable and defensible.
The Future of AVM Software
As technology advances, what software do people use to make AVMs will continue to evolve.
Future trends include:
- AI-driven explainability tools
- Real-time market adaptation
- Integration of alternative data
- Automated compliance monitoring
AVMs will become more transparent and more responsive.
Who Uses AVM Software Today?
AVM software is used by:
- Mortgage lenders
- Appraisal firms
- Real estate marketplaces
- Investors
- Insurance companies
Each group tailors the software stack to its needs.
Key Takeaways: What Software Do People Use to Make AVMs?
There is no single answer to what software do people use to make AVMs. Instead, AVMs are built using a layered ecosystem of tools.
At a high level, AVMs rely on:
- Data management platforms
- Statistical and machine learning software
- Geospatial analysis tools
- Cloud infrastructure
- Visualization and reporting systems
The best AVM solutions combine these tools into a scalable, accurate, and transparent system.
Final Thoughts
Understanding what software do people use to make AVMs is about understanding systems, not products. AVMs are not built with one tool—they are engineered through a carefully integrated technology stack.
Whether you’re in finance, real estate, or proptech, knowing how these tools work together helps you evaluate AVM accuracy, trust valuation outputs, and make better decisions in a data-driven market.