SAN DIEGO, June 23, 2026 (GLOBE NEWSWIRE) — Truepic, the enterprise leader of Visual Risk Intelligence in the AI era, today announced a strategic integration with Cotality™, a leading global property data and analytics company serving mortgage lenders nationwide. Lenders using Cotality’s Mercury Network® and Collateral Management System® (CMS) platforms will be able to seamlessly trigger Truepic Vision virtual inspections directly within their existing workflows. The initial roll-out supports home equity evaluations, 1004D final inspection alternatives, documentation for natural disasters, default servicing, and construction and renovation draws. This new collaboration highlights a shared belief that authenticated property photos and videos will be the foundation of digital and remote appraisals in the AI era.
Truepic Vision is an end-to-end virtual image and data authentication platform that enables lenders to send a secure link to borrowers, real estate agents, or other individuals to complete guided property inspections using their own mobile device. Images and videos are captured through Truepic’s controlled capture technology, which applies fraud detection and authentication testing on all visuals, protecting against image and AI fraud. The platform also ensures all data, including geolocation, time, date, and tamper detection at the moment of capture to ensure media is authentic and unaltered. The Vision platform also features a risk intelligence network to help identify bad actors and fraud techniques in real time.
“Lenders need a virtual inspection solution they can trust and seamless integration with existing workflows,” said Sage Nichols, senior vice president of Cotality’s Collateral Solutions. “This capability provides a frictionless process, reducing time and overall costs without sacrificing quality and integrity. By embedding Vision directly into Mercury and CMS, lenders and servicers can automate inspection ordering and review without leaving their core systems. This lowers costs and reduces turnaround times from days or weeks to hours while maintaining trusted, verified imagery in today’s era of increasing AI-generated fraud risk.”
“We are thrilled to work with Cotality to deliver authenticated images and data across the home and construction lending space,” said Craig Stack, President and Founder of Truepic. “We believe that trusted visual data will become foundational to modern lending infrastructure. By embedding authenticated capture directly into the systems that lenders already rely on, we’re making it easy to scale remote inspections without sacrificing trust, compliance, or risk controls in the AI era.”
Together, Truepic and Cotality are helping modernize property inspection workflows with authentic images and data while strengthening trust across digital lending in the AI era. The integration streamlines compliance, improves operational efficiency, and provides lenders with defensible inspection records that can withstand investor and regulatory scrutiny. As digital lending accelerates, this collaboration ensures institutions can scale inspection capacity without scaling risk.
The new integration will be available in CMS and Mercury later this year. Learn more by visiting the Virtual Inspection page.
About Truepic
Truepic is the leading provider of Visual Risk Intelligence, helping enterprises verify reality in the AI era. Its flagship platform, Truepic Vision, provides a multi-layered approach that authenticates images and data to prevent fraud, reduce risk, and protect business operations. Vision features the Truepic Risk Network, the first visual risk shared intelligence system for alerting suspicious activity across the financial sector. Trusted by Fortune 500 companies and recognized by TIME, Fast Company, and Inc. for its innovation, Truepic enables organizations to safeguard trust while driving growth. Learn more at http://www.truepic.com.
Media Contact
Jules Cassano
press@truepic.com
A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/72f7bb5b-a942-4fe2-baa2-ca9459e37fef.
