Data entry ops · Production
Voltus powers utility bill processing with 90% touchless accuracy using Docsumo Document AI
The problem
Voltus was manually capturing data from over 250 utility bills, consuming significant man-hours each month with no automated extraction in place.
Workflow diagram · grounded in source
1
Utility bills received
trigger
“extracting data from over 250 utility bills”
2
ML model extracts bill data
ai_action
“completely automate the process of extracting data from utility bills - thanks to Docsumo. Their team has helped us train the ML model to support our niche use cases”
3
Human review of exceptions
human_review
“Only 2% of our efforts are spent reviewing the data today”
Reported outcome
Docsumo's Document AI automated utility bill data extraction to 90% touchless accuracy, saving 98% of previously manual man-hours and reducing active review effort to just 2%, freeing the team to focus on growth.
Reported metrics
Man-hours saved on data capture98%
Touchless accuracy achieved90%+
Effort spent reviewing extracted data2%
Reported stack
Docsumo
Frequently asked questions
What did this team achieve with this AI workflow?
Docsumo's Document AI automated utility bill data extraction to 90% touchless accuracy, saving 98% of previously manual man-hours and reducing active review effort to just 2%, freeing the team to focus on growth.
What tools did this team use?
Docsumo.
What results were reported?
Man-hours saved on data capture: 98%; Touchless accuracy achieved: 90%+; Effort spent reviewing extracted data: 2% (source-reported, not independently verified).
How is this data entry ops AI workflow structured?
Utility bills received → ML model extracts bill data → Human review of exceptions.