The touchless invoice-processing rate increased after deployment.
MULTI-PRACTICE DENTAL ORGANIZATION / OPERATIONS
Invoice automation saves up to 800 hours monthly.
A multi-practice dental organization received 5,000 to 6,000 invoices each month, mostly over email and in different formats. Its touchless-processing rate was 5%, and rules-based automation failed when vendors changed layouts, terminology, or field positions. PivotX built a three-agent pipeline for extraction, validation, and human review of exceptions.
Industry
Healthcare
Function
Operations
Monthly Volume
5,000 to 6,000 invoices
Labor Recaptured
Up to 800 hours/month
RESULTS
5% to nearly 80%
Up to 800 hours recaptured monthly
Time previously spent on manual review became available for other work.
Fewer processing risks
Systematic extraction and validation reduced errors, missing fields, and duplicate-payment risk.
The same approach gives the organization a repeatable model for other high-volume administrative workflows where variable formats and manual exception handling create similar bottlenecks.
THE SITUATION
Rules-based automation failed whenever invoice formats changed.
The organization receives invoices from a large and diverse vendor base, each with its own format, layout, and data conventions. Rules-based automation handled predictable forms but failed when formats varied.
Most invoices weren't predictable. So most invoices went to staff. The manual process consumed approximately up to 800 labor hours each month and increased the risk of OCR errors, missing fields, and duplicate payments.
01
5% touchless rate across 5,000 to 6,000 invoices per month
02
Rules-based automation failing on format variation
03
700 to 800 staff hours per month on manual review
04
OCR errors, missing fields, and duplicate payment risk at volume
THE WORK
What we built
01
A three-agent invoice pipeline
Before working with PivotX, rules-based automation could process only invoices that followed predictable templates. When a vendor changed its format or layout, the invoice was sent to staff for manual processing.
PivotX built three agents that work in sequence. The first identifies the document type. The second uses optical character recognition and language models to extract vendor details, line items, amounts, tax identifiers, and payment terms. The third validates the information against vendor records and routes clean invoices for payment.
The pipeline can process invoices across different formats without relying on fixed templates.
02
Human review focused on exceptions
Before PivotX's involvement, staff reviewed most invoices manually and had to find and verify the relevant information before resolving a problem.
PivotX redesigned the review process so only flagged exceptions are sent to staff. Each exception includes the discrepancy and its source information, allowing reviewers to make a decision without rereading the full invoice.
Touchless processing increased from 5% to nearly 80%, and the organization recaptured most of the 700 to 800 hours previously spent on manual review each month. The process also reduced errors, missing fields, and duplicate-payment risk.
WHERE THIS TRANSFERS
Where this applies
Your team processes high volumes of documents that arrive in formats you do not control.
Automation handles common forms but fails when a document does not match the template.
Staff spend time extracting and routing information that should arrive ready for their review.
Proof
Pilots that became operating procedure.
PivotX has taken companies from initial assessment to production-grade AI in weeks, not quarters. The cases below aren’t proofs of concept. They’re actual production.
Which procurement workflow is creating the longest delay?
We can review the manual steps, handoffs, and systems involved and identify a practical place to begin.