Financial podcasts hold sustained conviction — the kind of in-depth insight that short-form data never captures. Context Analytics is the first to turn it into structured, investable signal.
Full episode transcripts — high-accuracy ASR captures every word from end to end
Named entity extraction — tickers, executives, and organizations tagged at the mention level
Topic & theme classification — recurring narratives surfaced and organized for research workflows
Custom feed targeting — filter by show, speaker, keyword, or sector
Get a one-day data sample and full product documentation. Interested in full backhistory? Our data team will walk you through it.
Every episode captured end-to-end via ASR, producing structured transcripts that feed directly into the sentiment pipeline.
Tickers, people, and organizations extracted and tagged at the mention level with time-stamped sentiment scores.
Fine-tuned NLP scoring built for investment context — not brand monitoring or PR measurement.
Recurring narratives and cross-sectional themes surfaced before they appear in mainstream price action.
10+ years of data for long-horizon backtesting and factor validation.
Target CEO interviews, analyst discussions, or specific shows via keyword and metadata filters.
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