Data entry ops · Production

Ellement automates pension contribution report data extraction with Nanonets, reducing processing time by 90%

The problem

Ellement's team manually gathered data points from employer Pension Contribution Reports and entered them into Excel spreadsheets, making data collection the most time-intensive step in their workflow and causing delayed speed-to-value for customers.

First attempt

Ellement tried Microsoft Power Automate but it offered limited accuracy even for structured data.

Workflow diagram · grounded in source
1
Employer submits pension reports
Trigger
A customer (employer) submits Pension Contribution Reports.
▾ source quote
“A customer (employer) submits Pension Contribution Reports.”
2
Auto-import from OneDrive
Integration
Nanonets provides a one-click integration with OneDrive to automatically import all employer pension contribution reports.
▾ source quote
“Nanonets provides a one-click integration with OneDrive to automatically import all employer pension contribution reports from a customer into Nanonets.”
3
AI data extraction
Ai action
A one-shot model extracts all relevant data points such as employee name, SSN number, hours worked, and pension contributions with high accuracy and minimal training.
▾ source quote
“Our powerful one-shot model extracts all relevant data points, such as employee name, SSN number, number of hours worked, amount contributed to their pension fund, etc. with high accuracy and minimal training.”
4
Post-processing cleanup
Validation
The extracted data undergoes post-processing to remove any special characters and whitespaces from multiple extracted data points.
▾ source quote
“The extracted data then undergoes post-processing to remove any special characters and whitespaces from multiple extracted data points.”
5
Export to Excel
Output
The clean extracted data gets exported to a pre-configured Excel sheet with columns automatically mapped to their counterparts.
▾ source quote
“The clean extracted data then gets exported to a pre-configured excel sheet with columns automatically mapped to their counterparts.”
Reported outcome

Nanonets automated the full data extraction pipeline, cutting the time for the data gathering step by 90% and enhancing the overall end-customer experience.

Reported metrics
Data gathering time reduction90%
End-customer experienceenhanced overall end-customer experience
Reported stack
NanonetsPower AutomateOneDriveExcel
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Source
https://nanonets.com/customer-success-story/ellement-automates-data-extraction-from-employer-pension-contribution-reports-using-nanonets
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Nanonets automated the full data extraction pipeline, cutting the time for the data gathering step by 90% and enhancing the overall end-customer experience.

What tools did this team use?

Nanonets, Power Automate, OneDrive, Excel.

What results were reported?

Data gathering time reduction: 90%; End-customer experience: enhanced overall end-customer experience (source-reported, not independently verified).

What failed first in this deployment?

Ellement tried Microsoft Power Automate but it offered limited accuracy even for structured data.

How is this data entry ops AI workflow structured?

Employer submits pension reports → Auto-import from OneDrive → AI data extraction → Post-processing cleanup → Export to Excel.

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