Augusta Mutual Adopts ZestyAI’s Risk Analytics to Strengthen Underwriting Precision

ZestyAI, the risk and decision intelligence platform for the insurance industry, announced that Augusta Mutual has selected ZestyAI’s Roof Age and Z-PROPERTY™ to enhance underwriting and rating accuracy, target inspections more effectively, and support sustainable growth across Virginia.

Based in Staunton, Virginia, Augusta Mutual is a single-state carrier serving Virginia since 1870 with a longstanding reputation for personalized service and local expertise. By upgrading from traditional imagery and inspection approaches to ZestyAI’s computer vision and machine learning technology, the insurer gains broader, more consistent property coverage and a more comprehensive, AI-driven view of property risk—unlocking property-level insights such as verified roof age, roof condition, vegetation overhang, and debris accumulation that directly influence claim frequency and severity.

“ZestyAI’s solutions bring a new level of precision to our underwriting process,” said Gretchen H. Collins, Vice President of Underwriting at Augusta Mutual. “We moved from legacy property risk tools to gain broader, verified property coverage, helping us make  faster, more consistent, and more confident decisions for our policyholders across Virginia.”

ZestyAI’s Roof Age delivers verified roof age by cross-validating building permit records with over 20 years of aerial imagery, detecting roof replacement events and assigning confidence scores across 97% of U.S. properties. Z-PROPERTY™ further enhances this insight by assessing roof complexity, materials, and condition, along with other parcel-level attributes that influence loss potential.

ZestyAI works closely with regulators to ensure transparency, validation, and continuous monitoring of its AI-driven models. Its portfolio of risk models has secured nearly 100 approvals from regulators nationwide, giving insurers confidence they can be deployed immediately with the accuracy and transparency regulators demand.