# Automating timesheet processing for a weekly payroll run

Hundreds of emailed timesheets a week, a hard payment deadline and no room for a wrong payslip. This is how the reading, checking and reconciliation moved to a pipeline of agents.

10 → 2

About 80 percent less manual work on the weekly run

People needed on the weekly payroll run, client-confirmed.

## The problem

Timesheets arrived by email every week in whatever form a site could produce, spreadsheets, PDFs and scans. Each one had to be read, checked against the rules for that worker and that site, and keyed before a fixed payment deadline.

With hundreds arriving a week, most of the effort went on reading and re-keying. The work that genuinely needs a person, the unclear sheet or the disputed rate, got whatever time was left before the deadline.

## How the pipeline works

Four agents split the job, each with one responsibility, so a failure in one step is visible instead of silently passed along.

1. A reader extracts the worker, site, dates and hours from each timesheet as it arrives.
2. A checker applies the business rules, such as which rate or priority applies, and sends anything that fails back to a person with the reason attached.
3. A reconciler matches the checked lines against the records payroll already holds, so a line is neither paid twice nor missed.
4. When a document cannot be read cleanly, an OCR backup takes a second pass before a person is asked.

Every change ships behind a replay suite. Real past weeks run through the new version and the results are compared line by line before it goes live. That suite caught a divergence in how a priority rule was applied before it could mis-pay a live run.

## What changed

The weekly run went from ten people to two, about 80 percent less manual work, against the same payment deadline. Nothing reaches payroll that has not passed the checks or been approved by a person.

## What a project like this needs from you

Access to the systems the work already lives in, usually a mailbox and the system of record, with a login the agent can use safely. The rules written down, or a person who knows them and has an afternoon to explain them.

A set of real past cases to test against. Replaying last month through a new version before it goes live is what lets a team trust the change. A named owner for the decisions the agent will not make, and a period where it runs alongside the team in shadow mode before it acts on anything.

## Common questions

### Can AI read timesheets reliably enough for payroll?

Reading is the easier half. What makes it reliable enough for payroll is what happens after the read, rule checks on every line, reconciliation against the records you already hold, and a person on anything the checks cannot confirm. Every change is also tested by replaying real past weeks before it goes live.

### What happens when a timesheet is unreadable or wrong?

It goes back to a person with the reason attached instead of being guessed. Poor scans get a second pass from an OCR backup first. The rule is that nothing reaches payroll unless a check has passed it or a person has approved it.

### How long does a timesheet automation project take?

It depends on how many formats and rules you have. I scope the first version to one workflow and one clear outcome so it ships in weeks rather than quarters, run it in shadow mode alongside the team, then widen it.

### Does timesheet automation replace the payroll team?

The aim is to remove the reading and re-keying, not the people who understand the rules. Someone still owns the sign-off, and the exceptions still need judgement, which is where the team's time goes once the keying is gone.

## Field notes behind this[EvalsThe Regression Test That Caught a Payroll Error Before It Shipped](https://shurco.ai/insights/the-regression-test-that-caught-a-payroll-error-before-it-shipped/)[DocumentsReading a Document With an Agent Is Easy Trusting It Is the Hard Part](https://shurco.ai/insights/reading-a-document-with-an-agent-is-easy-trusting-it-is-the-hard-part/)[DesignHuman in the Loop Is a Design Decision Not a Disclaimer](https://shurco.ai/insights/human-in-the-loop-is-a-design-decision-not-a-disclaimer/)

## Other problems I have solved[ManufacturingAn AI quoting agent for a manufacturer, from days to hoursThe quoting inbox took one to three days per quote. An agent now reads the enquiry and the bill of quantities and prices it against the live catalogue, behind a rules engine that keeps every price explainable.](https://shurco.ai/solutions/ai-quoting-for-manufacturers/)[Field operationsAutomating multi-site field reporting, from days to minutesDaily reporting across many sites took about three days to compile because the data lived in several places. Collector agents now gather it in parallel, a reconciler merges it and a reporter writes the report.](https://shurco.ai/solutions/multi-site-field-reporting-automation/)[DistributionAutomating sales order entry from emailed purchase ordersPurchase orders arrive by email as PDFs, spreadsheets and free text, and someone keys every line into the ERP. For one wholesale distributor that became a checked pipeline, then the same approach ran across every country in a group.](https://shurco.ai/solutions/sales-order-entry-automation/)[Asset managementDecision support for specialist matching at a global asset managerFinding the right specialist match took about three days, in a setting with real accountability. An audit-grade agent now returns ranked, cited recommendations, and a person makes the call.](https://shurco.ai/solutions/specialist-matching-decision-support/)

## Have the same problem

Each system above was built around one client's process. Yours will differ in the details, which is where the work is. [Tell me what your team spends too long on.](https://shurco.ai/#contact)

Web version https://shurco.ai/solutions/timesheet-to-payroll-automation/