superproton

Good point. There are a few (Creditsafe, Experian) but they're expensive and focus on basic credit metrics, not comprehensive financial health analysis. The real value is in the contextual interpretation - understanding what the numbers mean for investment/credit decisions. That requires domain knowledge baked into the analytics, not just clean data feeds. Plus controlling the full pipeline lets us iterate quickly on scoring algorithms based on user feedback. Hard to do that with third-party normalised data.

I use Claude to help me with the copy, I found is the best LLM for that, at least work for me.

Fair point - I started with the Companies House API and traditional parsing too. The issue isn't data access, it's consistency. UK companies file in wildly different formats - some use full GAAP, others micro-entity accounts, many have incomplete data. Rule-based systems work for ~60% of companies, then break on edge cases. Financial health also requires context: Is this debt ratio concerning for their industry/size? Are these cash patterns seasonal or declining? How do you weight profitability vs growth stage? I spent months on traditional approaches first. The AI handles the inconsistency and contextual interpretation that spreadsheet formulas can't.

That's great feedback, thanks a lot!

Thanks!!!

Wrong, my friend, that is only for small companies, big companies accounts are only available in PDF. Plus, in any case you have the raw data, here you have a full financial analysis.