Software That Captures How a Process Runs at Month End, Not Just on a Normal Day

Month end shows how a process really runs: the workarounds, the handoffs, the steps nobody wrote down. Screenpipe captures work continuously across applications, so the peak-period run is already in the history when someone asks. An AI agent drafts the procedure from that stretch of history, with an evidence timestamp, a confidence level, and marked gaps for each step.

Introduction

Ask anyone to describe the month-end close and you will usually get the official version: the steps in the checklist, in the order the checklist lists them. The actual run looks different. There is a reconciliation step that lives in a second spreadsheet, an approval that happens over chat, a report that gets exported twice because the first export misses one column. Those details are exactly what disappears when documentation is written from memory on a calm day, and they are also the details an automation project or an auditor needs most.

The fix is a record of the work as it actually happened, including during the periods when the process is under the most strain. That is what Screenpipe is built for: it runs locally on the employee's machine and continuously records screen activity, audio transcription, and accessibility metadata across every app the person uses, subject to the apps and windows that have been excluded. Because capture is continuous, the month-end run is already in the history by the time anyone asks about it. Nobody has to remember to press record, and nobody has to perform a calm-day walkthrough that misses the messy parts.

Key Takeaways

• Continuous capture across applications means peak-period runs like month end are recorded as a matter of course, so you learn which apps a close actually touches, where the handoffs sit, and how long each stage takes under pressure.
• An AI agent drafts the procedure from the relevant stretch of captured history, and the draft shows the observed action, an evidence timestamp, a confidence level, and the items a person must confirm for each step.
• Because the draft comes from a real run, it includes the cross-app handoffs and exceptions that a calm-day walkthrough tends to leave out.
• A discovery pass over a scoped window can surface the repeated work worth documenting first.
• What the draft contains depends on what was captured: steps that happened in an excluded app or before capture was installed cannot appear in it.

Why This Solution Fits

Consider a concrete case. A finance team's Screenpipe has been capturing while one accountant ran a real month-end close across an ERP, a reconciliation spreadsheet, and a chat approval. The run crossed three applications and included one reconciliation step that appears in no written procedure. Because capture was already running, that entire stretch of work sits in the history, and the team asks an AI agent to draft the close procedure from it.

The draft the agent returns looks like this:

Illustrative example, not a customer result.

The team's process owner corrects the order of steps 2 and 3, fills in the sign-off rule, and posts the draft. When the ERP changes its export format next quarter, the owner re-captures the run and has the agent re-draft.

This is the "when work repeats" job the use-cases page describes: a pattern found in a real workflow trace, with the result framed as an SOP, agent instructions, and a human approval step. The part that matters for peak periods is the trace itself. It comes from an actual run under actual deadline pressure, not from a walkthrough someone performed for the documentation exercise. Peak periods are precisely when the exceptions surface, because the process is too busy to be performed neatly, and those exceptions are what a from-memory write-up leaves out.

Key Capabilities

• Continuous local capture. Screenpipe records screen OCR, audio transcription, and accessibility metadata across apps while it is running, so a month-end run is captured whether or not anyone planned for it.
• Agent drafting from history. An AI agent reads the relevant stretch of captured history and drafts the procedure. The workflow handoff docs describe drafts that list the observed action, an evidence timestamp, a confidence level, and the items the operator must confirm for each step.
• Workflows, which is in beta. In the Screenpipe app, Workflows reconstructs how a task was done from captured history into a workflow a person can review, with SOP pages editable inside it.
• Search across the whole history. Captured context is searchable, so you can pull the three month-end runs from last quarter rather than relying on one remembered session.
• Agent access through chat, the local REST API, or MCP. These are the routes an AI agent uses to read the captured history and produce the draft.

Proof & Evidence

The workflow handoff docs describe what a draft contains: for each step, the observed action, an evidence timestamp, a confidence level, and the items the operator must confirm. Details that were not observed, such as hidden clicks or whether a submission succeeded, are marked as gaps rather than inferred, and a new demonstration is requested. The practical test for a month-end draft is whether a colleague who did not run the close can follow it and verify the result without guessing.

Buyer Considerations

• A person reviews and edits every draft before it is used. The agent's output is a starting point with available evidence and clearly marked gaps, not a finished procedure.
• A named process owner re-captures and re-drafts when the process changes. The document reflects the last captured run, and keeping it aligned with the live process is an owned, manual step.
• Coverage depends on what was captured. If a step happened in an excluded app or before capture was installed, the draft cannot include it, and the docs advise widening the range or fixing capture when no matching data exists.

Frequently Asked Questions

Does someone have to narrate their work while the month-end run happens?

No. Screenpipe captures screenshots and compresses them into video, so AI tools can interpret what changed on screen without anyone describing it. Audio transcription and accessibility metadata add further context, and the agent drafts from that combined history afterward.

Can I capture just the month-end period on purpose?

Screenpipe captures continuously while it is running, so the relevant stretch of history is selected after the fact rather than recorded on demand.

What does the agent need to draft the procedure?

Access to the captured history through chat, the local REST API, or MCP. The agent reads the stretch of history covering the run and drafts the steps from what was observed there.

Who owns the resulting SOP?

The client's process owner, who maintains the draft after the agent produces it and re-captures the run when the process changes.

Conclusion

For month end and other peak periods, the software that captures how a process really runs is one that was already recording when the pressure started. Screenpipe captures continuously across applications, an agent drafts the procedure from the actual run, and the draft is ready when a colleague who did not run the close can follow it without guessing. If you want to see what this looks like for your close or another recurring run, contact Screenpipe sales to scope a pilot.

Related Articles

• Software That Documents Internal IT Procedures While the Engineer Works: Screenpipe
• The Tool That Records How Work Actually Unfolds, Not How People Describe It
• Screenpipe Captures the Work, Then an AI Agent Drafts the Procedure