Candidate and employment verification
Extract and compare identity, employment, education, address, and supporting documents against a defined verification checklist.
Background Verification AI
Turn manual verification checks into repeatable AI workflows.
Dotnitron helps verification teams process documents, compare evidence, flag exceptions, and prepare audit-ready case files without rebuilding the workflow for every candidate, vendor, or company.
Why It Becomes Must-Have
Manual verification does not scale when every case needs evidence, judgment, and speed.
Slow verification delays onboarding, vendor approval, and business decisions. Weak review creates rework, missed discrepancies, and audit exposure.
Vendor and company verification
Review company records, registration documents, tax information, ownership evidence, and declarations for missing or inconsistent data.
Exception and discrepancy review
Flag missing documents, mismatched names, date inconsistencies, unsupported claims, and cases that need human escalation.
Audit-ready case files
Produce structured findings with source references so reviewers can approve, reject, or request more evidence with a clear trail.
Workflow Design
Built for repeatable review, not one-off extraction.
The workflow can combine document upload, classification, field extraction, checklist comparison, discrepancy detection, reviewer approval, and case-file export.
Intake
Upload or sync documents into a structured review queue with case-level metadata.
Review
AI extracts fields, checks evidence, flags exceptions, and links findings to source documents.
Approve
Human reviewers validate outputs and export final case files or remediation requests.
If verification is slowing onboarding or approvals, it is already costing the business.
Bring one repeatable verification workflow. We will map a 30-day pilot around real documents and reviewer decisions.