Case Study

Internal Reporting Automation

A prototype pipeline that pulls operational data automatically and generates a plain-English AI summary, replacing a manual weekly report.

Demonstration project — not a paid client engagement
01 · Business Problem

A recurring weekly report was being manually compiled from several spreadsheets, taking hours each week and frequently going out late or with errors from manual copy-pasting.

02 · Solution

An automated pipeline was built to pull data directly from its source, and an AI-generated summary was layered on top to translate raw numbers into a plain-English update for stakeholders.

03 · Technology Used
PythonGoogle Sheets APIOpenAI
04 · Implementation Process
  • Mapped exactly where the source data lived and how it needed to be combined
  • Built an automated pipeline to pull and consolidate the data on a schedule
  • Used AI to generate a short, readable summary alongside the raw figures
  • Tested output accuracy against manually compiled reports from prior weeks
05 · Business Outcome

The prototype illustrates a reporting process that runs on a schedule with no manual compilation — demonstrating the kind of time recovered when repetitive reporting work is automated.

06 · Lessons Learned

AI-generated summaries are genuinely useful, but only once the underlying data pipeline is reliable — automation has to fix the data problem before it can fix the reporting problem.

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