Pocketstox is a SaaS product enabling users to perform semantic similarity searches between news articles and earnings transcripts using vector embeddings. The central aim behind this idea is to democratise financial analysis, specifically stock discovery, for retail investors by leveraging natural language processing.
The stock discovery process prevents many retail investors from actively investing in the market. The time and effort required leads them to settle for trending companies or passive investments.
The stock market's steep learning curve deters many potential retail investors from taking their first steps. Conventional wisdom often directs beginners to passive investments like S&P 500 ETFs—a safe but limiting approach that doesn't serve those interested in active investing. While ETFs provide diversification and relative safety, they don't help investors develop critical analysis skills or market understanding. As a result, beginners who wish to invest actively often find themselves asking "how do I find companies to invest in?" Without clear guidance, many either abandon active investing entirely or follow online trends, pouring money into heavily discussed stocks like Tesla or GameStop. This herd mentality, while common, prevents investors from developing independent thinking skills crucial for long-term success in the market.
To empower retail investors to discover investment opportunities by intelligently connecting news they read to relevant companies, making stock discovery more intuitive and accessible.
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