Property Condition Assessments at Scale with

Published by
Nico Lassaux
April 21, 2023
Property Condition Assessments at Scale with

As Automated Valuation Models (AVMs) have increased in popularity, the valuation of properties at scale has become significantly easier. These models do well analyzing all the data associated with a (usually single family) property and its surrounding market to generate valuations, but they are missing a key capability: Accurately assessing a property's quality and condition.

Traditionally, AVMs have lacked the ability to distinguish between well-maintained properties with incredible amenities, and those in disrepair. Humans do this very well – we just look at listing photos for a few properties and we understand their relative quality and condition instantly. But how can you look at ALL the property photos across a large portfolio (or even a whole city) and assess every one of them in terms of quality and condition?

Quality Score: The Missing Variable for AVMs

Fortunately, photo-based analysis can now be done at scale with The team at has been building price prediction and automated valuation models for the better part of a decade, and we’ve combined our expertise in computer vision and AI to fill in this critical gap in AVMs.

An example showing how QualityScore ranks some interior pictures
An example showing how QualityScore ranks some interior pictures

Our model objectively evaluates a property's quality condition and features/amenities from interior and exterior photos. It then converts this data to a consistent, easy-to-understand score for AVMs and comparable property detection algorithms.

We provide quality scores every individual room in a property and it’s exterior, then use that data to generate an overall score for each property so it can be compared to others on an apples-to-apples basis.

By utilizing AI to analyze property photos at scale, we help AVM providers and portfolio operators generate more accurate valuations, facilitate better investment decisions, and reduce portfolio risk.

Standardizing Real Estate Image Analysis

Our AI-powered model offers a consistent, standardized methodology that can be applied to all properties while providing more detailed information than manual appraisals. This level of granularity improves decision-making and facilitates objective property comparisons. With Quality Score, you can:

  1. Build More Accurate AVMs – Users can enhance AVM accuracy by incorporating objective scores for each property in a dataset. With the amenity data we extract, you can also bolster an existing database with new information using Quality Score.
  2. Identify Value-Add Opportunities – Quickly find the prototypical “worst house on the best block” using Quality Score outputs.
  3. Comparable Property Detection – Source better comparables by factoring in condition and quality data to ensure apples-to-apples comparisons.
  4. Automate Appraisal Work – Improve appraisal quality control and consistency by using Quality Score to maintain high standards and eliminate human bias.

Our groundbreaking AI-powered condition and quality assessments are poised to revolutionize the property valuation process, providing unparalleled accuracy and consistency. By harnessing the power of photo-based analysis and offering standardized, granular insights, our models unlock a world of possibilities for real estate investors and technology providers alike.

  • Learn more about how we can evaluate quality from your pictures here: Product Page
  • Check how we're using quality for finding the best comps: Rent Comps

Property managers, investors, brokers and appraisers all use HelloData to analyze multifamily comps, optimize rents, and increase deal flow.

Nico Lassaux

Data Scientist Nicolas Lassaux, with expertise in real estate analytics, was pivotal at Enodo and Walker & Dunlop. Co-founder of Hello Data, he's elevating real estate decisions through innovative data use. Passionate about running, cycling, and music.

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