Manual data stood between the team and the answer
Inven is an AI-powered deal sourcing platform for M&A. Its two-person finance team relied on Google Sheets for modeling, but every update began with the same routine: export data from billing and accounting, clean it up, and paste it into the right place.
That made every model depend on the last manual refresh. It also meant finance time went into moving data instead of forecasting and analysis.
- Each source required its own export cycle
- Copy-paste introduced avoidable reconciliation work
- Models became stale as soon as the underlying systems changed
A live data layer for the spreadsheets Inven already used
Inven connected its accounting system to Control and brought billing data in through CSV import. The spreadsheet connector now feeds structured data into the team’s existing Google Sheets models.
The setup took hours. Formulas, charts, and board templates stayed in place; only the manual input layer changed.
| Before | With Control |
|---|---|
| Export and paste from each source | Scheduled data updates |
| Clean and map columns by hand | Consistent, model-ready structure |
| Recheck freshness before reporting | Refresh on demand when needed |
More time for modeling, less time maintaining it
Inven’s models now update daily without a recurring export routine. The finance team can spend that time on scenarios, forecasts, and investor reporting instead of data transfer.
Control reduces manual data transfer...we get the information into a smarter format, and from there to wherever is needed.
Joona Puro, Finance, Inven
The result is simple: a small finance team keeps the tools it knows, while the data underneath them stays current as the company grows.
