The only provider of structured signals from podcasts. We transcribe and score business, tech and finance podcasts for long-term conviction on the companies mentioned.
Podcasts are one of the most influential media formats and one of the least measured. This feed creates a way to take the market's opinion on brands and add it as a signal layer.
Structured signals from transcribed and scored podcast audio, ready to plug into trading workflows as a signal layer in longer-term strategies.
JSON field groupsWhy a company is being mentioned, derived from the quantitative output, with an AI summary added after and a relevance score for each mention.
What it deliversCorrect, and that is the point. This is long-term conviction on discourse and emerging brands, scored through the same engine. Pair it with S-Factor to cover both ends of the horizon.
Context Analytics monitors financial, business and technology podcasts in real time, identifying company and ticker mentions and analyzing the sentiment and relevance of the conversation behind them. Each mention is timestamped and scored, turning unstructured audio into structured, ticker-level sentiment data.
It works in four steps: high-accuracy transcription of raw audio, entity tagging of tickers and companies at the mention level, finance-tuned sentiment scoring, and validation against 10 years of historical data for backtesting.
The quantitative feed delivers structured, ticker-level sentiment scores built for systematic and quant trading workflows, designed to plug directly into a model or pipeline. The qualitative feed delivers AI-generated summaries of the conversations themselves, per company mention, built for portfolio and risk managers who want the signal without the data engineering lift.
10 years of historical podcast sentiment data for backtesting.
Unlike generic media monitoring, which is built for PR tracking, or raw transcription APIs, which are DIY and unstructured, this feed is delivered as structured JSON built specifically for quantitative trading, not brand monitoring.
Yes. We support custom feed generation targeting specific shows, CEO interviews, analyst discussions, or keyword and metadata filters based on your research strategy.
Podcast sentiment data is delivered via JSON.
Request a historical sample for your universe and test podcast sentiment against your own long-horizon models.