EarningsCall EarningsCall

EarningsCall

Earnings call transcripts, audio, slide decks, and earnings calendar for 9,000+ public companies. One API.

EarningsCall provides developers, quants, and researchers with programmatic access to structured earnings call data, with many transcripts available within 15 minutes of each call ending.

What We Offer

API

REST API and official Python and JavaScript SDKs for accessing:

Earnings call transcripts with speaker-level data
Q&A and prepared remarks segmented separately
Raw MP3/WAV audio files
Investor slide decks
Earnings event calendar
Real-time webhook notifications

Covers 9,000+ publicly traded companies across NYSE, NASDAQ, and global exchanges with 5 years of historical data.

Mobile App

Real-time access to earnings call data on iOS and Android. Stay updated on earnings calls while on the go.

Quick Start

pip install --upgrade earningscall

from datetime import date

from earningscall import get_calendar, get_company

company = get_company("aapl")
transcript = company.get_transcript(year=2026, quarter=2, level=2)

# Access speaker-level data (level=2)
for speaker in transcript.speakers:
    print(f"{speaker.speaker_info.name} ({speaker.speaker_info.title})")
    print(speaker.text[:200])

# Download audio file
company.download_audio_file(year=2026, quarter=2, file_name="AAPL-Q2-2026.mp3")

# Download slide deck
company.download_slide_deck(year=2026, quarter=2, file_name="AAPL-Q2-2026-Slides.pdf")

# Get earnings calendar
calendar = get_calendar(date(2026, 9, 20))
for event in calendar:
    print(f"{event.company_name} - Q{event.quarter} {event.year} on: {event.conference_date.astimezone().isoformat()}")

Speaker-level data (level=2) requires a plan that includes Enhanced Transcript Data.

For full documentation and examples, visit the API Documentation page. To learn more about transcript data and coverage, see the Earnings Call Transcripts API page.

Key Features

Speaker-level transcripts: every word mapped to the speaker who said it
Q&A segmentation: prepared remarks and analyst Q&A separated automatically
Audio files: MP3/WAV download for every covered earnings call
Slide decks: investor presentation slides alongside transcripts
Earnings calendar: upcoming earnings event data via API
Real-time notifications: webhook alerts when new transcripts are available
Python and JavaScript SDKs: official clients for fast integration

Pricing

Plans start at $60/month. No annual lock-in. 7-day money-back guarantee for first purchases only, if requested within 7 days of the initial purchase and fewer than 1,000 API calls have been made.

View Pricing

Use Cases

Backtesting Quants and algorithmic traders use earnings call transcripts as a signal source, testing how management tone, guidance language, and Q&A sentiment correlate with post-earnings price movement.

Trading Applications Fintech builders embed EarningsCall data into trading platforms and analytics tools, giving their users access to structured transcript data and audio alongside market data.

Dashboards Teams build internal dashboards that pull transcripts and earnings calendar data to monitor portfolio companies, track executive commentary, and flag guidance changes automatically.

Internal Research Investment firms and analysts use EarningsCall to speed up equity research, pulling transcripts programmatically instead of reading PDFs or watching recordings manually.

Sentiment and NLP Data scientists build sentiment models, topic classifiers, and named entity extraction pipelines on top of speaker-level transcript data from thousands of companies.

AI Agents Developers building financial AI agents and copilots connect EarningsCall to their LLM pipelines to answer questions about what management said on any earnings call.

Academic Research Universities and research institutions use EarningsCall to build financial NLP datasets, reproduce published studies, and run new research on management communication and market behavior.

Who Uses EarningsCall

Developers: building financial data apps and NLP pipelines
Quants and researchers: event-driven strategies and sentiment analysis
Institutional investors: tracking management tone and guidance
Academic researchers: financial NLP datasets and studies
Finance professionals: faster equity research

Resources

Mission

To give developers and analysts reliable, structured access to earnings call data, without scraping, parsing, or waiting.

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