Property valuation is part science, part art. BuildIQ's Automated Valuation Model (AVM) combines machine-learning with live market data to produce fast, accurate, and transparent value estimates — with clear confidence ratings so you always know how much to trust the number.
An Automated Valuation Model (AVM) uses statistical and machine-learning algorithms to estimate a property's market value based on a combination of comparable sales data, property characteristics, and market trends. AVMs are widely used by mortgage lenders, appraisal firms, and institutional investors as a first-pass valuation tool.
The most common AVM approach is a hedonic pricing model — a regression technique that assigns value to individual property attributes (bedrooms, bathrooms, square footage, garage, pool, etc.) based on how those attributes affect sale prices in the local market. A well-trained hedonic model can estimate values within 5–8% of actual market prices in markets with rich comparable data.
BuildIQ layers a hedonic base model with a spatial interpolation engine that accounts for geographic price gradients, and a time-series adjustment layer that normalises for market movements between the comparable sale date and today. The result is an estimate that's more current and location-specific than traditional AVM approaches.
Critically, BuildIQ's AVM is not a "black box". Every value estimate comes with a data transparency panel that shows exactly which comparables were used, how each was adjusted, what data sources are feeding the model, and why the model assigned the confidence level it did.
Live feed of closed sales from Multiple Listing Service databases. Filtered to within 0.5 miles, 90 days, and within 20% of subject GLA.
Assessed values, land-to-improvement ratios, ownership history, and permit records. Used for cross-validation and trend analysis.
Deed recording data captures transactions not yet reflected in MLS, including off-market sales, auction results, and estate sales.
Rolling 30/90/180-day price trend data at the ZIP code level. Used to adjust static comparable sales for temporal drift in rapidly moving markets.
Block-level price gradients that capture street-by-street value differences — crucial in urban markets where one block can mean a 10% price difference.
Active and expired listing data reveals pricing patterns, seller behavior, and days-on-market trends that inform future-facing ARV estimates.
Every BuildIQ valuation carries an explicit confidence rating. This is not a measure of how good the property is — it's a measure of how reliable the data environment is for computing the estimate.
Criteria: Five or more comparable sales within 0.5 miles in the last 90 days. Low price variance across comps (less than 12% coefficient of variation). Active listing market with strong days-on-market signal.
Action: You can rely on this estimate as a strong proxy for market value. Normal negotiation and due diligence apply, but you do not need a full traditional appraisal before making an offer.
Criteria: Two to four comparable sales, or sales are 90–180 days old, or there is moderate price variance across comps. The model is extrapolating slightly beyond its highest-confidence zone.
Action: Treat the estimate as directional guidance. Expand your comp search manually, consider a drive-by or desktop appraisal, and build extra negotiation buffer into your offer.
Criteria: Fewer than two comparables, rural or unique property with no close matches, comps older than 180 days, or high price dispersion that indicates an illiquid or rapidly changing market.
Action: Do not rely on this estimate for offer decisions. Commission a professional appraisal or use BuildIQ's manual price override to input your own ARV backed by independent research.
BuildIQ presents all valuations as a range rather than a single-point estimate. A typical output might show: Low: $285,000 | Mid: $310,000 | High: $335,000. These represent the 15th, 50th, and 85th percentile estimates derived from the comp distribution after adjustments.
For fix-and-flip analysis, you should use the Low estimate as your conservative ARV when computing MAO. This ensures your offer is defensible even if the eventual sale lands below the median expectation. For cash flow analysis on a rental, use the Mid estimate.
Never use the High estimate for investment decision-making. The High estimate represents the best-case scenario — what the property might achieve in ideal market conditions. Building your thesis around best-case scenarios is the #1 source of unexpected losses in real estate investing.
The AVM is a starting point, not the final word. There are specific situations where you should override the automated estimate with your own researched value:
Enter any UK or US address and get a confidence-rated AVM estimate with full data transparency in seconds.
Run a Valuation Now