Expense Automation System
Nightly Splitwise-to-Airtable sync turned raw transactions into a clean reporting dataset
The Problem
As company transaction volume grew, Splitwise records alone were not enough for compliance, tax preparation, annual filings, and broad spending analysis. Manual extraction was repetitive and inconsistent, and reporting quality suffered as the dataset expanded.
Our Solution
We built a lightweight nightly automation using Make. The flow retrieves only changed Splitwise records since the previous run, filters actual expenses, extracts relevant values, and performs batched upserts into Airtable by source expense ID. Airtable then applies category grouping for higher-level analysis and dashboard views.
How It Works
Nightly job fetches only changed records since the previous run
Pipeline filters non-expense noise and keeps valid spend events
Relevant fields are extracted and normalized for reporting
Batched upserts write to Airtable keyed by original expense ID
Category grouping in Airtable creates broader analytical views
Team consumes structured dashboards instead of fragmented raw entries
Technologies Used
Results & Impact
Reliable and predictable spend analytics without manual data wrangling
Nightly Automated
Sync Frequency
Nightly
Data Strategy
Changed-record only
Write Mode
Batched upsert
Outcome
Structured analytics
Key Takeaway
Simple automations can deliver high practical value
Efficiency comes from processing only meaningful changes
Thoughtful data modeling is as important as automation itself
Related Work
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