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API & SDKs
Next live call

MU Q4 FY26

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Live

Every word arrives within seconds of being spoken. Streaming transcript, no replay delay.

Attributed

Each line tagged to the speaker who said it. 99% accuracy on named attribution.

Analyzed

AI insights surface as the conversation unfolds — guidance, surprises, the moments that move the stock.

On this call: Satya Kumar, Sanjay Mehrotra, Mark Murphy · 9 covering analysts

Build on Live Earnings

The only live-attributed earnings feed.
Now an API.

Every word attributed to the speaker who said it. Streamed within seconds of being spoken. This is the foundation for every product that operates while the call is live — alerts, signal generation, position sizing, post-call analysis. Build what your competitors can't.

Diarization tells you a speaker changed. Live Earnings tells you who it was.

Other live transcript feeds
Live Earnings
Speaker 1 / Speaker 2
Toshiya Hari, Goldman Sachs
Diarization only
Speaker name + role + firm
Buggy real-time labels
Provisional events with explicit corrections
Generic transcript text
Typed event stream (attribution, phase, insight)

Live diarization is not enough. Live Earnings resolves the speaker.

Trading desks

Surface guidance, surprises, analyst pressure points in the seat — sub-5-second from spoken word to your terminal.

Research products

Replace transcription vendors that ship hours later. Live attributed copy, ready to highlight, quote, embed.

Internal LLM pipelines

Feed attributed turns into your own models for sentiment, deviation-from-guidance, Q&A pattern detection.

Install
Pythonpip install live-earnings
from live_earnings import LiveEarningsClient

client = LiveEarningsClient(token=...)
for env in client.stream("nvda-q1-fy27"):
    print(env.event.name, env.event.text)
TypeScriptnpm i live-earnings-sdk
import { LiveEarningsClient } from "live-earnings-sdk";

const client = new LiveEarningsClient({ token });
for await (const env of client.stream("nvda-q1-fy27")) {
  console.log(env.event.name, env.event.text);
}