Aivre, a real estate appraisal software company, has cut the time it takes to complete an appraisal by more than half, thanks to its integration with Restb.ai's computer vision and image recognition technology, according to a Restb.ai press release.
According to a recently released case study, appraisers using Aivre now save more than three hours per appraisal by automating time-intensive steps like photo classification, comparable scoring and report generation. That’s a productivity boost that can double the number of appraisals completed in a day.
“We're taking the first AI trained to autofill reports in UAD language to the next level through our joint efforts with Restb.ai," Aivre Founder and CEO Jake Lew said in the release. "Aivre frees appraisers from repetitive tasks, allowing them to focus on their expertise and deliver faster, more precise appraisals with greater efficiency."
Lew also notes that manual, repetitive work has long weighed down appraisers. From gathering property characteristics and validating floor plans to selecting comps and populating photo fields, the traditional workflow is filled with time sinks and opportunities for errors, he added.
Restb.ai, an innovator in computer vision AI for the mortgage industry, integrates its market-leading computer vision technology into Aivre’s platform to fully or partially automate many of these time-consuming steps.
Appraisers can instantly extract and classify key property features from photos, receive condition and quality scores for subject and comparable properties, and auto-populate GSE-compliant forms – without manually inputting or verifying the data.
Here’s how Aivre users are recapturing more than 180 minutes per report:
- Collecting and validating property details (e.g., lot size, legal description): 20 minutes
- On-site notetaking: 20 minutes
- Floor plan validation: 20 minutes
- Photo placement and labeling: 10 minutes
- Comp selection and scoring: 60 minutes
- Report typing: 60 minutes
“These gains aren’t just about speed – they're also about accuracy,” Nathan Brannen, chief product officer for Restb.ai and co-author of the case study, said. “By automating more of the manual data fill appraisers enter into each report, we reduce human errors, increase consistency, and ultimately, enable appraisals to spend their energy analyzing and valuing the property.”