AI-assisted appraisal quality control Better insight. Confident review.

Document intake, supported extraction, source evidence, configured QC checks, reviewer and validator workflows, assignment, AI assistance, and reporting. The workspace keeps the document and the review decision connected: findings link to their source context, checkpoint grades and comments stay with the file, and the review-to-validation handoff records who decided what.

The configured printed-form catalogs cover 1004 / Freddie Mac 70, 1025 / Freddie Mac 72, and 1073 / Freddie Mac 465. Package checks also use supporting forms such as 1004MC, 1007, and 216. Supported UAD 2.6 XML and ZIP deliveries are read through their embedded report PDF. Field review (2000) is a review workflow type; it does not add a separate automated extraction catalog.

The delivery’s MISMO XML identifies a redesigned URAR, Restricted Appraisal Update Report, or Completion Report. QC Review selects the corresponding H-1, H-2, or H-3 catalog. Reviewers can inspect XML-based findings with related PDF report context, use eligible AI assistance, and complete checks that require manual attention.

An authorized reviewer verifies AI suggestions and confirms the decision. Depending on the check, the reviewer can accept a suggestion, override it, or record a manual verdict. AI assistance is available for eligible checks under the configured policy, stays off until it is enabled for your organization, and keeps a reviewer’s confirmation on every result.

The intake flows support PDF reports, MISMO XML, delivery ZIPs, engagement letters, and supporting documents. A package can combine a PDF report with its XML delivery, and engagement-letter checks run alongside the report checks. Extraction depends on the supported form and readable source content; image-only scanned reports need a separate evaluation.

Where enabled, tenants can configure a key for a deployment-supported provider, select an accessible model, and set an output cap. AI usage and allocation are visible in the management view, including monthly usage against its limit. Provider support and entitlements depend on the configured deployment, and AI stays off until it is enabled for your organization.

Yes. Organization rules, project overrides, versioned checklists, and rule-specific AI guidance let authorized users configure the process. The Rule Lab provides candidate testing before a rule change is saved. Rule and checklist changes apply only to your organization, switching a rule off requires a reason, and each change is kept in a history.

Documents and review data are stored in a US data-center region and encrypted in transit and at rest. Accounts are created by invitation, access follows each person’s role and project membership, and rule changes stay within your organization. AI assistance stays off until it is enabled for your organization.

Mobile and tablet review screens support checkpoint grades, comments, and page references, so reviewers can work through a file away from a desk. An active network connection is required to save decisions to the server. Grades, comments, validation, returns, and sign-off stay with the file, whichever screen they were recorded on.

Start with a product walkthrough. Bring your review workflow, supported document types, staffing needs, and AI policy so the team can evaluate the right configuration and discuss deployment readiness. Request a demo from the contact page to walk through the documents, checks, and AI assistance that fit your review process.