Turn Every Earnings Call into Structured Intelligence

Access full earnings call transcripts, historical earnings surprises, forward estimates, and earnings calendars — the complete data set for building automated earnings monitoring, sentiment analysis, and investment signal tools.

Full-text, all quarters

Earnings Transcripts

Full earnings call transcripts for thousands of public companies across all available quarters — management commentary, analyst Q&A, and guidance language in structured, retrievable form.

Surprises, estimates, calendar

Earnings Data & Estimates

Historical earnings surprises (actual vs estimated EPS and revenue), forward analyst estimates, consensus data, and earnings calendars — the quantitative layer alongside transcript text for earnings intelligence workflows.

What you can build

Earnings intelligence tools powered by FMP.

Transcript analysis

Full earnings call text for NLP, sentiment analysis, topic modelling, and AI-driven extraction of management guidance and strategic signals.

Earnings surprise monitoring

Historical and current earnings surprises across thousands of companies — the signal data for systematic earnings momentum and post-earnings drift strategies.

Forward estimate tracking

Analyst consensus EPS and revenue estimates alongside revision history to track how expectations evolve into and out of each reporting period.

Earnings calendar alerts

Forward earnings dates and reporting schedules for automating earnings season monitoring, pre-announcement positioning, and post-earnings analysis workflows.

Complete Earnings Coverage

Batch transcript retrieval across all available quarters for a company — enabling longitudinal analysis of management tone, language shifts, and guidance accuracy over time.

Multi-quarter history

Earnings calendar with actual results, consensus estimates, and surprise data updated through each reporting season for timely monitoring and alerting.

Updated each quarter

Investment teams and AI developers use FMP's earnings data and transcripts to build the monitoring tools that surface material information as it emerges — not after the market has moved.