Williamson County

Process Efficiency & Expense Reduction

A Property Tax Assessor Case Study to Improve Efficiency & Quality Assurance


  • 60% Reduced Error Rate
  • Greater than ~36,000 Hours Saved
  • Greater than ~$900,000 Saved in Wage Expense
  • Greater than ~50X ROI



Like many states, in Texas, property taxes are local taxes that provide the largest source of money local governments use to pay for schools, streets, roads, police, fire protection, and many other services.

With a population of 609,017 Texans to serve, the Williamson County (“Wilco”) Central Appraisal District takes its role seriously as it’s the primary source of revenue for its citizens’ public services. In addition to keeping best management practices and disseminating consistent and clear public communications, the astute Wilco Central Appraisal District team keeps its finger on the pulse of PropTech innovations, all to ensure Wilco residents are fairly taxed and their government is appropriately funded.

In 2019, the Wilco team began to explore integrating artificial intelligence technology into its semi-annual home data collection process to reduce error rates, increase efficiency, and save taxpayer dollars. Specifically, the team focused on improving its process of assigning “Quality Class” to homes by its tax assessors.


Reviewing, grading, and recording an entire region’s property to reassess taxes is a monumental task in itself. It is further complicated by the fact that the Central Appraisal District has a finite time to complete the task, and each county sets its own custom “Quality Class” scale for grading its property. As such, the District has limited time to train, oversee, validate, and record-keep the work of countless, stretched-thin assessors and appraisers.

In automating its “Quality Class” process, the Wilco Central Appraisal District faced the challenge of finding a technology partner that they trusted with this hypercritical task, had true real estate knowledge, could work within its custom “Quality Class” scale, and had advanced AI technology that could perform its quality scoring at a superhuman level.

Municipality Benefit

After sourcing a referral from its trusted technology partner Tyler Technologies, the Wilco Central Appraisal District Office chose to engage FoxyAI to help automate its “Quality Class” process. Using existing photos of homes labeled with the “Quality Class” assigned by Wilco County assessors, Wilco’s Central Appraisal office used the  “FoxyAI Quality Score” model to verify the accuracy of assessor-scored quality classes on photos of over 160,000 parcels in the county.

Today, Wilco residents benefit from the foresight and action of their local Central Appraisal District. FoxyAI’s Quality Score model is currently more accurate in determining Wilco’s “Quality Class” than the average assessor and has reduced error rates by over 60%1. The technology also saved the Office hundreds of thousands of hours of manual verification time and, as a result, saved the county greater than ~$900,000 in wages not incurred2.

The benefits that led the Wilco team to their decision to engage FoxyAI included:

  • Trust

    The Wilco team smartly sourced referrals from its trusted and long-term technology partner, ensuring that FoxyAI was up to its hypercritical task.

  • Real Estate Knowledge

    FoxyAI co-founder Vin Vomero has a background in real estate and technology, as do other employees across the organization. This true real estate experience can be seen and realized throughout FoxyAI’s innovations, product deployment, and customer service.

  • Ability to Work with Customer Defined Definitions for Scoring

    FoxyAI models are  built to accommodate customer defined definitions of quality scoring and occupancy. This allows customers, like Wilco, to seamlessly and efficiently incorporate its “Quality Class” scoring criteria into its use case using the FoxyAI Quality Score.

  • Advanced AI Technology

    FoxyAI’s technology is proven and award-winning, enabling government entities and affiliated agencies to drive efficiency and accuracy across valuations, risk, underwriting, and revenue collection activities.


    1. Error in this study is defined as the % of scores greater than or equal to 2 points away from the Quality Class on the scale of 1-10.

    2. $ saved based on # of hours saved and appraiser salary of $30/hr