Milestone: We just won the Apify "Social Good" Spotlight! (FEC Scraper)
Hey everyone,
I wanted to share a small win that actually feels really big for us.
We recently built a tool to help make political funding data more accessible. It connects to the Federal Election Commission API and helps researchers track campaign finance contributions without needing to write complex code.
To our surprise, Apify just selected us as the winner of their Social Good Spotlight!
It is honestly such a great feeling to be recognized for building something that serves a public purpose. We often get caught up in building tools just for revenue, so working on a project focused on transparency and democratic oversight was a breath of fresh air.
This really validated for us that the community cares about Tech for Good. It motivates us to keep looking for other ways to use our skills for public impact.
For the builders here: If you are building in the Political Tech or GovTech space, we’d love any honest feedback on:
How you handle visualizing large datasets like this?
Are there other government APIs that are notoriously difficult to work with?
Thanks for letting us share this win!
https://apify.com/parseforge/fec-campaign-finance-contributions-scraper
Congrats on the spotlight - campaign finance data is one of those public datasets that's technically accessible but practically unusable for most people. Making it queryable without coding is real public service.
On your questions:
For large dataset visualization, I've seen teams get stuck trying to show everything at once. The ones that work best usually start with aggregate views (totals by candidate, by state, over time) and let users drill down into individual records. Hierarchy beats flatness.
As for notoriously difficult government APIs - the SEC's EDGAR system is a classic pain point. Inconsistent filing formats, weird character encodings, and no real query language. Also state-level courts - PACER equivalents at the state level are wildly inconsistent.
What's the typical use case you're seeing so far? Journalists doing investigative work, or more academic research?