AI

AI Assistant for Analyzing SEC Filings like 10-K and 10-Q Reports

Hacker News

AI Assistant for Analyzing SEC Filings like 10-K and 10-Q Reports

I created an AI Assistant (chatbot) to analyze and review SEC filing documents such as 10-K, 20-F, 40-F, 10-Q, and 8-K reports. The AI Assistant helps with the following tasks: - Summarizing, reviewing, and analyzing SEC filing documents like 10-K, 20-F, 40-F, 10-Q, and 8-K reports - Reads the entire filing document to provide insights and identify risks, challenges, and opportunities from the Filings. - Saves time and effort in researching investments and companies. - Chats and discusses the SEC filing, answers questions, and performs analytical tasks on the filing. You can try out the AI Assistant by selecting a company to review its SEC filings from here: https://decodeinvesting.com/sec_filings Review NVIDIA's latest 10-K filing with the assistant here: https://decodeinvesting.com/sec_filings/NVDA/chat/0001045810... See more details here: https://www.reddit.com/r/DecodeInvesting/comments/1blzih0/ai...

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Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
TrustMRRFits verified-revenue profile · Strong signals: answers · Missing: mobile apps, ios, personal
61%61% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: tasks, code · Missing: mac, agents, macos
53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released
45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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