The best investors spend considerable time reading and listening. Why? Because the information needed for informed decisions is often not readily available on a Bloomberg screen. Investors who outperform gather data from numerous, often disorganized sources.
Hudson Labs' specialized financial AI allow you to extract both numeric and non-numeric data from unstructured sources, such as earnings calls, in seconds. Here are a few examples.
Traffic at Costco stores
Costco’s stock price is primarily driven by one key metric: comparable sales, also known as same-store sales. While comparable sales are frequently reported, the core factors influencing those figures, such as store traffic, are typically only discussed during earnings calls.
Without Hudson Labs AI, gathering traffic data and commentary from eight different earnings call transcripts would take considerable time.
Guidance at Visa
Most guidance is delivered through press releases and presentations, but key insights often emerge only during earnings calls. Without Hudson Labs AI, these forward-looking statements can be overlooked.
For example, Visa discussed the impact of its new acquisitions, Featurespace and Pismo, on 2025 results only during the call.
Pro vs DIY performance at Home Depot
Understanding qualitative dynamics can be just as important as analyzing quantifiable data. With one query, Hudson Labs AI reveals how the COVID-era dominance of DIY shoppers at Home Depot has diminished over the past two years.
Hudson Labs AI doesn’t just save time in the investing process; it uncovers insights you would otherwise miss. It helps investors filter valuable data from noise by extracting the most relevant information. Learn more about how Hudson Labs distinguishes itself from generic chatbots by building finance-specific tools here.
