Enterprises handle thousands of invoices, purchase orders, and contracts every year that require routing to the right department or stakeholder. Manual routing or rule-based legacy systems often lead to delays, errors, and compliance risks, as documents may be sent to the wrong team or miss critical approval steps. This creates inefficiencies, increases cycle time, and exposes organizations to audit issues.
AI-powered workflow routing leverages intelligent extraction, natural language understanding, and contextual data analysis to ensure documents reach the right queue or approver automatically. By reducing manual routing tasks, organizations accelerate approvals, maintain compliance, and minimize costly errors.
This total cost of ownership calculator helps you evaluate the true ROI of the category using modern AI powered alternatives over traditional OCR based solutions.
Key Use Cases:
Automated Workflow Routing
Automatically routes invoices and purchase orders to the correct approvers or queues based on extracted fields such as department code, PO reference, or approval level.
Workflow Routing & Assignment
Routes documents to the appropriate teams by sending invoices to finance, contracts to legal, and purchase orders to procurement based on extracted data.
Approval Workflow Compliance
Ensures proper authorization paths are followed by detecting when invoices, POs, or contracts bypass required approval processes.
Approval Bypass Prevention
Prevents documents from skipping mandatory approval stages by monitoring workflows and blocking unauthorized approvals.
Start by selecting a typical scenario or adjust the baseline details to reflect your exact needs. The calculator will update automatically.
Legacy OCR and static workflow rules often deliver only 80% accuracy, resulting in frequent misrouting and the need for heavy manual review. Analysts spend significant time verifying extracted fields and rerouting documents, which increases operational costs and slows down processing.
Modern AI solutions combine OCR, NLP, and vision models to achieve 92% accuracy ±2%, significantly reducing routing errors. However, since generic AI models cannot precisely identify when a document is misrouted, verification of critical cases is still required. The result is reduced but not eliminated manual effort, with faster, more reliable workflow automation.
Your AI investment isn’t delivering expected savings. This may indicate inefficiencies or incorrect assumptions in your current workflow.
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