Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

We’re Kris, Suhas, and Heather (YCS21) and we’re building Bedrock AI ( https://bedrock-ai.com/ ). We use machine learning to extract hard-to-find information and assess risk in public company reports (SEC filings). Our platform is used by investors to improve portfolio returns and mitigate downside risks. Most public company data is unstructured and textual. Because relevant information is hard to find, a lot of corporate data is radically underused, to the detriment of investors. For example, our research shows it can take 12-18 months for corporate malfeasance to be incorporated into stock price after clear warning signs appear in financial text. Hard-to-find information that we extract includes accounting and governance choices, product defects, regulatory issues, customer/market reliance and much more. One example is Sino-Forest, Canada's Enron. Sino-Forest was a darling of Canadian investors until an infamous exposé, by short-seller Muddy Waters, in 2011.