I built a Congress stock trade tracker that filters 4,000 annual disclosures down to the ones actually worth acting on
Most people have no idea that every member of Congress is legally required to disclose their stock trades. The STOCK Act passed in 2012 made it mandatory. 535 members. Every buy, every sell, publicly filed within 45 days.
The data is out there. The problem is what existing tools do with it.
They show you everything. All of it. Raw filings with a ticker, an amount range, and a date. No context. No filtering. No way to know if you're looking at a committee chair loading up on defense stocks
before a budget vote or a routine spousal ETF rebalance.
I spent 3 months trying to use these tools and kept hitting the same wall. The signal was in there somewhere. I just couldn't find it.
So I built Kapitol.ai.
The core idea is simple: not all congressional trades are equal. A buy matters a lot more when the member sits on the committee that oversees that sector, when the timing aligns with legislative activity,
when the position size is significant relative to their history. We score every trade against those factors and only send an email alert when something clears the bar.
You get the trade, the score, and a written breakdown of why it matters. That's it.
What I learned building this:
The hardest part wasn't the tech. Laravel made the backend straightforward. The hard part was the curation model, figuring out what actually separates a high-conviction trade from noise. That took a lot of
manual review of historical disclosures before the scoring logic felt right.
The second hardest part was positioning. "Congress stock tracker" sounds like a dozen other things. The differentiation is the filtering and analysis layer, not the data itself. Getting that message right
took longer than I expected.
Where it stands today:
Plans start at $35 per month or $299 per year. Fully bootstrapped.
If you've ever looked at congressional trading data or built anything in the fintech space, I'd love to hear what you think.
