Accounts payable · Production

CNRG boosts invoice processing 4x with Vic.ai, achieving 60% no-touch rate and 76% time reduction

The problem

CNRG's AP department manually processed high volumes of invoices across multiple brands, spending approximately 5 minutes per invoice on downloading, printing, coding, and ERP data entry, and lacked visibility into cross-brand spending and the ability to scale operations without adding headcount.

Workflow diagram · grounded in source

Invoice ingestion via Vic.ai

trigger

“All expense invoices now go through Vic.ai, with automatic coding and integration into Microsoft Great Plains”

AI invoice coding and classification

ai_action

“CNRG has achieved a 90% accuracy rate in invoice coding and classification”

Autopilot no-touch routing

routing

“The implementation of Autopilot for invoices under $3,000 has further increased efficiency”

Human approval for high-value invoices

human_review

“Approvals for invoices have been standardized across the organization, with specific flows set up for invoices over $3,000 and certain GL codes”

ERP sync with Great Plains

integration

“Vic.ai integrates directly with Microsoft Great Plains to enable a seamless flow of financial data across the CNRG organization. The integration allows for real-time synchronization of invoice data between Vic.ai and Great Plains, elimin…”

Real-time analytics output

output

“The platform provides real-time analytics on invoice processing data, team performance, and spending patterns across brands”

Reported outcome

CNRG reduced invoice processing time by 76% (from 5 to 1.2 minutes per invoice), achieved 90% accuracy in invoice coding and classification, and reached a 60% no-touch Autopilot invoice processing rate, with improved visibility into cross-brand spending.

Reported metrics

Invoice coding and classification accuracy> 90%

No-touch invoice processing rate60%

Invoice processing time per invoicefrom 5 to 1.2 minutes per invoice

Invoice processing time reduction76%

Show all 5 reported metrics

Invoice coding and classification accuracy> 90%

No-touch invoice processing rate60%

Invoice processing time per invoicefrom 5 to 1.2 minutes per invoice

Invoice processing time reduction76%

AP team capacity and workloadbalance out the workload

Reported stack

Vic.aiAutopilotMicrosoft Great Plains

Source

https://www.vic.ai/resources/case-studies/scaling-retail-ap-cnrg-boosts-invoice-processing-4x-with-ai

Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

CNRG reduced invoice processing time by 76% (from 5 to 1.2 minutes per invoice), achieved 90% accuracy in invoice coding and classification, and reached a 60% no-touch Autopilot invoice processing rate, with improved…

What tools did this team use?

Vic.ai, Autopilot, Microsoft Great Plains.

What results were reported?

Invoice coding and classification accuracy: > 90%; No-touch invoice processing rate: 60%; Invoice processing time per invoice: from 5 to 1.2 minutes per invoice; Invoice processing time reduction: 76% (source-reported, not independently verified).

How is this accounts payable AI workflow structured?

Invoice ingestion via Vic.ai → AI invoice coding and classification → Autopilot no-touch routing → Human approval for high-value invoices → ERP sync with Great Plains → Real-time analytics output.