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In the past year I have been working 10+ hour days to create a stock analysis platform and API that parses full SEC reports and creates normalized financial data. There are APIs that do that right now as you know, but unless you pay big money, you are not getting precise data out of them.
The problem is that the "cheaper" providers parse data from SEC programmatically, but because this data is very complex and custom, they make a ton of mistakes. I've used many in the past, their numbers have tons of errors frankly.
So I created an automated pipeline that extracts this data using AI instead. AI is far superior because of reasoning and the ability to think like an analyst. I don't parse the data, I give it to the AI and ask it to normalize for me with fields like revenue, net_income, free_cash_flow etc..
I think the platform came out really really well, I am very proud of it. And the API and data accuracy has been really surprising.
It's been an insane journey frankly. Behind the scenes, I have created ways to extract data from SEC, including storing in a NAS, ingesting, checking SEC daily index, automatically extracting reports, even foreign filers, missing zero quarters. It's really wild what has come out of it.
Two examples of the many challenges I encountered: First, SEC filings use "Incorporation by Reference" (IBR) where companies point to data in other documents instead of including it directly. I had to figure out which exhibit types actually contain the financial data - turns out it's EX-13, EX-13.1, EX-13.2 (Annual Reports to Shareholders), EX-99.1, EX-99.2, EX-99.3 (earnings releases), EX-12 (ratio computations), and even EX-1 through EX-9 for some foreign filers.
Second challenge: foreign filers. They submit thousands of 6-K forms for all sorts of reasons - press releases, events, random updates. Only some are actual quarterly earnings. I built a system where AI analyzes each 6-K and scores whether it's an earnings report or not. It even handles edge cases like semi-annual reporters and companies that put their financials in PDF exhibits instead of HTML. And cases where companies change their fiscal calendars mid year.
I'm looking for a small number of early users who actively invest and are willing to give honest feedback. I'm trying to figure out:
- Are the AI-generated investment stories useful or just noise? They have been genuinely very useful for me, but I wonder what others think about them and what would they add to get a better picture of the company's quarter/annual report.
- What's missing that you'd want to see?
- Would something like this fit into how you research stocks today?
The platform is on www.stockainsights.com , FREE account available if you want to check it out, especially if you are an investor and even more if you are looking for solid stock data.
You can use this FREE coupon for full access:
STOCKAIFREE26
Happy to answer questions about the extraction pipeline or anything else about the tool and API.