Finance ops · Production

Trullion reduces manual audit time by up to 50% at Tanner LLC

The problem

Tanner's audit teams faced growing inefficiencies from legacy processes: invoice-by-invoice detail tests, manual financial statement checks, and hand-extraction of data from lease and debt agreements were slowing delivery and limiting how effectively staff could scale across audits.

Workflow diagram · grounded in source
1
Labor-intensive audit trigger
trigger
“Teams were performing invoice-by-invoice detail tests, checking financial statements by hand, and manually extracting key data from lease and debt agreements—slowing delivery and limiting how effectively staff could scale across audits”
2
OCR and detail testing
ai_action
“Initially adopted for OCR and detail testing”
3
Revenue testing, tie-outs, data extraction
ai_action
“Trullion quickly expanded into revenue testing, financial tie-outs, and data extraction from agreements”
4
Financial statement suite output
output
“Its financial statement suite became a favorite among managers for its accuracy and speed”
Reported outcome

Since adopting Trullion, Tanner reduced time spent on manual audit tasks by up to 50%, with tasks that once took hours now completed in minutes, and staff able to focus more energy on analysis and decision-making.

Reported metrics
Time spent on manual audit tasksup to 50 percent
Task completion time (invoice samples, disclosures)once took hours, are now completed in minutes
Reported stack
TrullionOCR
Source
https://trullion.com/customer-stories/tanner-case-study/
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Since adopting Trullion, Tanner reduced time spent on manual audit tasks by up to 50%, with tasks that once took hours now completed in minutes, and staff able to focus more energy on analysis and decision-making.

What tools did this team use?

Trullion, OCR.

What results were reported?

Time spent on manual audit tasks: up to 50 percent; Task completion time (invoice samples, disclosures): once took hours, are now completed in minutes (source-reported, not independently verified).

How is this finance ops AI workflow structured?

Labor-intensive audit trigger → OCR and detail testing → Revenue testing, tie-outs, data extraction → Financial statement suite output.

Related finance ops cases