Key insights
- An individual investor developed an open-source tool to monitor SEC filings (10-K, 10-Q, 8-K, etc.) for specific tickers and generate AI-driven summaries, including financial highlights, management commentary, risk factor changes, and insider transaction sentiment. The tool aims to provide timely awareness of critical filings, potentially informing investment decisions, but its impact is limited by its individual nature and reliance on AI interpretation.
I hold a concentrated portfolio of 8 positions and I read the actual filings — not analyst summaries, not earnings call transcripts fed through a chat interface. The problem is keeping up. Miss a Friday afternoon 8-K and you find out on Monday when the market has already moved.
So I built something to solve this. It's a small Python bot that runs on a spare phone sitting on my desk. I message it "Any news?" and it goes straight to SEC EDGAR, pulls the latest 10-K, 10-Q, 8-K, and Form 4 filings for whatever tickers I'm tracking, analyzes each one, and sends back a structured summary.
What the summaries cover:
— Financial highlights with YoY comparison
— Management commentary (what they're emphasizing, what they're quietly walking back)
— Risk factor changes between filings (I find this underrated — when a company adds or removes a risk factor, it's worth paying attention)
— Insider transaction sentiment: Bullish / Bearish / Neutral with specific names and amounts
A few things that made me think this community specifically might find it useful:
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It reads the primary source. Not a data vendor. Not a curated feed. Raw SEC EDGAR. You can verify every claim by clicking the source link.
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It supports 13 form types. Beyond the usual 10-K/10-Q/8-K, it handles SC 13G/13D (I want to know when an activist takes a 5%+ position), DEF 14A (proxy statements — executive compensation is worth reading), and S-1s if you follow pre-IPO companies.
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No subscription, no algorithm deciding what's "important." You set the watchlist and the form types. It does the reading.
It's not trying to replace your research process. It's the layer that ensures you don't miss the 8-K filed on a Friday at 4:58 PM.
The whole thing is open source. No cloud service involved — runs locally on whatever hardware you have.
github.com/authorturker/sec-analyzer-ai
Happy to answer questions about the setup, the analysis quality, or how I actually use it in my own research process. Feedbacks will be super cool for me, I'm thinking to add more features with them. Also, for people who wants to try this, model selection affects quality a lot. :)