Turn earnings calls
into analyst-ready insight.

A different approach to earnings call analysis.

Earnings call analysis is the practice of turning the words spoken on a quarterly earnings call, plus the tone behind them, into insight: what management is confident about, what they are hedging on, and how that compares with what they said last quarter. Analysts, investor relations teams, and portfolio managers have used it for years to inform models, notes, and client conversations.

Why earnings call review breaks down

For most research teams, the practice never matched the promise. Calls got listened to live, once, with a page of handwritten notes and a transcript ordered afterward from a vendor. The transcript arrived a day later: a wall of text with speaker labels and no sense of which line in the prepared remarks changed from last quarter, or whether the CFO sounded confident answering the margin question or was reading from a script. Comparing five calls in a sector meant five separate PDFs and an afternoon of searching for keywords.

Reading the call, not just the transcript

Speak AI treats every earnings call the way a senior analyst would, at machine speed. Each call is transcribed in your language, with 100+ supported, and then the recording itself is analyzed: the tone and energy in management’s voice, the confidence or hedging in how a question gets answered, the pacing that shifts before a hard number. Guidance language, margin figures, named competitors, and key phrases are extracted into structured fields your models can use.

Then the questions start. Ask across your entire library of calls with AI chat, using the same prompt workflows analysts once ran manually in a spreadsheet, now running natively over transcripts with ChatGPT, Claude, and Gemini built in.

What analysts ask their earnings calls

• “What did management say about guidance this quarter, and how does the language compare with last quarter?”
• “Which calls this quarter mention margin pressure or freight costs, and what exactly was said?”
• “Show me every call where a competitor was named directly.”
• “Which executives sounded confident on this call, and where did the tone shift during Q&A?”
• “Summarize the most common themes across every call in this sector this quarter.”

From a call replay to a research-ready note

The result is a call library that writes half the note for you. Guidance language is tracked against the prior quarter automatically. Sentiment and tone across management’s answers become a chart instead of a gut feeling, and dashboards you can customize and white-label track confidence, guidance changes, and competitor mentions over time, so this quarter’s call is measured against the last four. One healthcare consulting firm put a comparable volume of client sessions through this same analysis engine and saved $190K and 10,000+ hours, without adding headcount.

And because earnings calls rarely live alone, the same engine scores calls, meetings, and recordings on the same criteria, connecting call analysis to call scoring and coaching across every conversation your team reviews.