Search by address, select comps with smart ranking, and get local adjustment estimates backed by your chosen comparables. Data-driven analysis for appraisers.
Built for appraisers
Breaking the boundary between data and decisions
Whether you're selecting comps, tuning condition ratings, or defending adjustments—every number has a clear story and a defensible prior.
Built for appraisersMLS-integratedTransparent methodology
How it works
From search to adjustments in one workflow
Enter an address, load candidates, and add comps by feature. Finish to see local adjustment effects and prior ranges—all driven by your comp set.
1
Search & target
Enter a subject property address. We find the property and pull key attributes so you have a clear target for your comp set.
2
Select comps
Load nearby sales and add comps by feature (sq ft, beds, baths, etc.). Adjust condition ratings and build a set that fits your assignment.
3
Local adjustments
Finish to see estimated adjustment effects and prior ranges from a linear model fit to your comps—transparent and defensible.
Who we are
About
Comp Check Pro helps appraisers and real estate professionals perform data-driven comparable sales analysis. Our tool connects to MLS and public records so you can search by address, build a comp set with smart ranking and filters, and get transparent local adjustment estimates based on the comparables you choose.
We focus on clarity and defensibility: you see how each adjustment is estimated and the prior ranges behind the model, so your analysis is both rigorous and easy to explain to clients and reviewers.
Purpose
Our mission
To give appraisers a clear, defensible way to select comparables and estimate adjustments—so every comp set is transparent and every number has a story.
What we stand for
Values
Data-driven
Adjustments and rankings based on your comps and clear methodology.
Defensible
Prior ranges and effects are visible so you can explain your conclusions.
Efficient
Search, filter, and rank candidates in one place.
Features
Why Comp Check Pro
MLS & public recordsSmart rankingFlexible filtersLocal adjustmentsMap & export
Support
Frequently asked questions
Smart ranking scores each candidate by how similar it is to your subject property across key features (living area, lot size, beds, baths, etc.). The model uses your comp set and prior ranges to estimate which sales are most comparable, so the top results are the best fits for your analysis.
Prior ranges are derived from a Ridge regression model fit to sales in the broader region. They represent typical per-unit adjustment ranges (e.g. dollars per sq ft) so the local model stays reasonable when your comp set is small. You can review and adjust priors in Settings if needed.
Yes. After you search by address, the subject property card shows fields pulled from MLS or public records. You can edit any of them (living area, beds, baths, condition, etc.) if the data is wrong or you want to run a sensitivity analysis.
Use the feature buttons to rank candidates and click a candidate row to add it as a comp. To remove a comp, use the remove button next to it in the suitable comps list. Smart select comps fills the list to 6 using smart ranking in one click.
Comp Check Pro
Search by address, then pick a feature to optimize and choose comps one by one.
How it works
1
Search & target
Enter a subject property address above. We find the property and pull key attributes so you have a clear target for your comp set.
2
Select comps
Load nearby sales and add comps by feature (sq ft, beds, baths, etc.). Adjust condition ratings and build a set that fits your assignment.
3
Local adjustments
Finish to see estimated adjustment effects and prior ranges from a linear model fit to your comps—transparent and defensible.
Target property
You can edit the subject's features below if public records are incorrect.
Subject property
Suitable comps (selected)
No comps added yet. Candidates load automatically below.
Candidates
Nearby sales load automatically. Adjust filters to refresh.
Search area & ranking
mi
days
sq ft
sq ft
Smart rankings
Distance (nearest first)
Time (newest first)
–
–
–
–
–
–
–
Rank by feature and add comps
listings
Final suitable comps
Subject value from each comp
For each comp: (subject feature − comp feature) × adjustment, summed and added to comp sale price = estimated subject value.
Subject property is required. Search by address to set the subject.
Local adjustments
Linear model fit to your comps with uniform prior ranges. Effect = estimated from data; range = prior bounds (see methodology). Only features that vary across comps are shown.
Adjustment
Effect
Typical range
Advanced Settings
Prior range is the 90% confidence interval (from region Ridge model). Adjust the interval per feature below; the model uses it as a Gaussian prior for adjustments.
Settings
No settings available at the moment.
Prior (local adjustments)
Larger = weaker prior, so your comps have more influence. Default 8.
Radius used when computing adjustment priors from the region. Default 2.
Maximum number of location clusters to try when tuning. Default 12.
