Zeta (ZETA)

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As of Oct 23, 2026, Kalshi has settled 14 word markets on Zeta’s earnings calls since 2026, on 14 different words. Next call: Nov 3, 2026 (13 words listed).

Next: Earnings call ·

13 words listed · Occasion page

Who counts: Kalshi: company speakers + operator

Kalshi

Zeta: the words listed for Tue, Nov 3, how often each was said on past occasions, and the probability for this one
WordQ3’24Nov '24Q4’24Feb '25Q1’25May '25Q2’25Aug '25Q3’25year agoQ4’25Feb '26Q1’26Apr '26Q2’26last callTrendLast 8ScriptedAll-timeProbabilityMarket
OpenAI / ChatGPT0 times: OpenAI / ChatGPT, Q3’24 Nov '240 times: OpenAI / ChatGPT, Q4’24 Feb '250 times: OpenAI / ChatGPT, Q1’25 May '250 times: OpenAI / ChatGPT, Q2’25 Aug '254 times: OpenAI / ChatGPT, Q3’25 Nov '25, counts as said6 times: OpenAI / ChatGPT, Q4’25 Feb '26, counts as said1 time: OpenAI / ChatGPT, Q1’26 Apr '26, counts as said16 times: OpenAI / ChatGPT, Q2’26 Aug '26, counts as saidrising4/850%2/825%7/2133%84%transcripts from the transcript model74¢ Kalshi
Palantir0 times: Palantir, Q3’24 Nov '240 times: Palantir, Q4’24 Feb '250 times: Palantir, Q1’25 May '250 times: Palantir, Q2’25 Aug '250 times: Palantir, Q3’25 Nov '250 times: Palantir, Q4’25 Feb '260 times: Palantir, Q1’26 Apr '2615 times: Palantir, Q2’26 Aug '26, counts as saidrising1/812%1/812%1/215%75%n=1+tx from settlement history blended with transcripts46¢ Kalshi
Loyalty0 times: Loyalty, Q3’24 Nov '240 times: Loyalty, Q4’24 Feb '250 times: Loyalty, Q1’25 May '250 times: Loyalty, Q2’25 Aug '251 time: Loyalty, Q3’25 Nov '25, counts as said4 times: Loyalty, Q4’25 Feb '26, counts as said2 times: Loyalty, Q1’26 Apr '26, counts as said2 times: Loyalty, Q2’26 Aug '26, counts as saidrising4/850%3/838%6/2129%75%n=1+tx from settlement history blended with transcripts46¢ Kalshi
Snowflake6 times: Snowflake, Q3’24 Nov '24, counts as said0 times: Snowflake, Q4’24 Feb '250 times: Snowflake, Q1’25 May '250 times: Snowflake, Q2’25 Aug '250 times: Snowflake, Q3’25 Nov '251 time: Snowflake, Q4’25 Feb '26, counts as said0 times: Snowflake, Q1’26 Apr '265 times: Snowflake, Q2’26 Aug '26, counts as saidsteady3/838%2/825%13/2162%67%n=1+tx from settlement history blended with transcripts46¢ Kalshi
AI Infrastructure0 times: AI Infrastructure, Q3’24 Nov '240 times: AI Infrastructure, Q4’24 Feb '250 times: AI Infrastructure, Q1’25 May '250 times: AI Infrastructure, Q2’25 Aug '250 times: AI Infrastructure, Q3’25 Nov '250 times: AI Infrastructure, Q4’25 Feb '260 times: AI Infrastructure, Q1’26 Apr '266 times: AI Infrastructure, Q2’26 Aug '26, counts as saidrising1/812%1/812%1/215%61%n=1+tx from settlement history blended with transcripts46¢ Kalshi
Inference0 times: Inference, Q3’24 Nov '240 times: Inference, Q4’24 Feb '250 times: Inference, Q1’25 May '250 times: Inference, Q2’25 Aug '250 times: Inference, Q3’25 Nov '250 times: Inference, Q4’25 Feb '262 times: Inference, Q1’26 Apr '26, counts as said2 times: Inference, Q2’26 Aug '26, counts as saidrising2/825%1/812%2/2110%59%n=1+tx from settlement history blended with transcripts46¢ Kalshi
Foundry0 times: Foundry, Q3’24 Nov '240 times: Foundry, Q4’24 Feb '250 times: Foundry, Q1’25 May '250 times: Foundry, Q2’25 Aug '250 times: Foundry, Q3’25 Nov '250 times: Foundry, Q4’25 Feb '260 times: Foundry, Q1’26 Apr '264 times: Foundry, Q2’26 Aug '26, counts as saidrising1/812%1/812%1/215%55%n=1+tx from settlement history blended with transcripts46¢ Kalshi
Cannes Lions0 times: Cannes Lions, Q3’24 Nov '240 times: Cannes Lions, Q4’24 Feb '250 times: Cannes Lions, Q1’25 May '253 times: Cannes Lions, Q2’25 Aug '25, counts as said0 times: Cannes Lions, Q3’25 Nov '250 times: Cannes Lions, Q4’25 Feb '260 times: Cannes Lions, Q1’26 Apr '261 time: Cannes Lions, Q2’26 Aug '26, counts as saidsteady2/825%1/812%2/2110%44%n=1+tx from settlement history blended with transcripts46¢ Kalshi
SuperGraph0 times: SuperGraph, Q3’24 Nov '240 times: SuperGraph, Q4’24 Feb '250 times: SuperGraph, Q1’25 May '250 times: SuperGraph, Q2’25 Aug '250 times: SuperGraph, Q3’25 Nov '253 times: SuperGraph, Q4’25 Feb '26, counts as said2 times: SuperGraph, Q1’26 Apr '26, counts as said0 times: SuperGraph, Q2’26 Aug '26rising2/825%2/825%2/2110%39%n=1+tx from settlement history blended with transcripts46¢ Kalshi
Connected TV0 times: Connected TV, Q3’24 Nov '240 times: Connected TV, Q4’24 Feb '250 times: Connected TV, Q1’25 May '250 times: Connected TV, Q2’25 Aug '250 times: Connected TV, Q3’25 Nov '252 times: Connected TV, Q4’25 Feb '26, counts as said2 times: Connected TV, Q1’26 Apr '26, counts as said0 times: Connected TV, Q2’26 Aug '26rising2/825%2/825%7/2133%36%n=1+tx from settlement history blended with transcripts46¢ Kalshi
Trade Desk0 times: Trade Desk, Q3’24 Nov '240 times: Trade Desk, Q4’24 Feb '250 times: Trade Desk, Q1’25 May '250 times: Trade Desk, Q2’25 Aug '250 times: Trade Desk, Q3’25 Nov '251 time: Trade Desk, Q4’25 Feb '26, counts as said1 time: Trade Desk, Q1’26 Apr '26, counts as said0 times: Trade Desk, Q2’26 Aug '26rising2/825%0/80%3/2114%28%n=1+tx from settlement history blended with transcripts46¢ Kalshi
Agentic Commercenever said0 times: Agentic Commerce, Q3’24 Nov '240 times: Agentic Commerce, Q4’24 Feb '250 times: Agentic Commerce, Q1’25 May '250 times: Agentic Commerce, Q2’25 Aug '250 times: Agentic Commerce, Q3’25 Nov '250 times: Agentic Commerce, Q4’25 Feb '260 times: Agentic Commerce, Q1’26 Apr '260 times: Agentic Commerce, Q2’26 Aug '26steady0/80%0/80%0/210%12%n=1+tx from settlement history blended with transcripts46¢ Kalshi
Enterprise Intelligence0 times: Enterprise Intelligence, Q3’24 Nov '240 times: Enterprise Intelligence, Q4’24 Feb '250 times: Enterprise Intelligence, Q1’25 May '250 times: Enterprise Intelligence, Q2’25 Aug '250 times: Enterprise Intelligence, Q3’25 Nov '250 times: Enterprise Intelligence, Q4’25 Feb '260 times: Enterprise Intelligence, Q1’26 Apr '260 times: Enterprise Intelligence, Q2’26 Aug '26steady0/80%0/80%2/2110%12%n=1+tx from settlement history blended with transcripts46¢ Kalshi
  • times said on that call
  • counted as said (ring)
  • no call
  • probability next time, with n
  • Select a word or a cell for its quotes
What the columns mean
Last N
of the appearances shown, how many counted as said
Trend
how the count moved over these calls
Scripted
calls of the last 8 where it was said in the prepared remarks
All-time
every call on file
Probability
the calibrated probability for the next listing; n is the settled observations behind it when it was computed, '+tx' adds the transcripts, 'new' means too little history

Market prices are mid quotes from Kalshi and Polymarket, shown for context, may be delayed by several minutes and are not a signal. Quotes as of Oct 22, 2026 23:21 UTC.

Every word

1–2 of 2, most settled first
Zeta: every word with settled markets, most settled first
WordQ3’24Nov '24Q4’24Feb '25Q1’25May '25Q2’25Aug '25Q3’25Nov '25Q4’25Feb '26Q1’26Apr '26Q2’26last callTrendLast 8ScriptedAll-timeProbability
Forrester3 times: Forrester, Q3’24 Nov '24, counts as said0 times: Forrester, Q4’24 Feb '250 times: Forrester, Q1’25 May '250 times: Forrester, Q2’25 Aug '250 times: Forrester, Q3’25 Nov '251 time: Forrester, Q4’25 Feb '26, counts as said3 times: Forrester, Q1’26 Apr '26, counts as said1 time: Forrester, Q2’26 Aug '26, counts as saidsteady4/850%3/838%11/2152%67%n=1+tx from settlement history blended with transcripts
OpenAI0 times: OpenAI, Q3’24 Nov '240 times: OpenAI, Q4’24 Feb '250 times: OpenAI, Q1’25 May '250 times: OpenAI, Q2’25 Aug '253 times: OpenAI, Q3’25 Nov '25, counts as said6 times: OpenAI, Q4’25 Feb '26, counts as said0 times: OpenAI, Q1’26 Apr '2615 times: OpenAI, Q2’26 Aug '26, counts as saidrising3/838%2/825%4/2119%85%n=1+tx from settlement history blended with transcripts
What the columns mean
Last N
of the appearances shown, how many counted as said
Trend
how the count moved over these calls
Scripted
calls of the last 8 where it was said in the prepared remarks
All-time
every call on file
Probability
the calibrated probability for the next listing; n is the settled observations behind it when it was computed, '+tx' adds the transcripts, 'new' means too little history

Appearances and settled record

latest 12

Our transcript counts matched how 14 of 14 settled words resolved (100.0%). How we check.

Recent appearances and how their listed words settled
DateAppearanceTextWordsSettledOur count agreed
Aug 4, 2026Earnings call FY26 Q2Speaker-labelled transcript149 yes · 5 no14/14 (100%)
Apr 30, 2026Earnings call FY26 Q1Speaker-labelled transcript0––
Feb 24, 2026Earnings call FY25 Q4Speaker-labelled transcript0––
Nov 4, 2025Earnings call FY25 Q3Speaker-labelled transcript0––
Aug 6, 2025Earnings call FY25 Q2Speaker-labelled transcript0––
May 1, 2025Earnings call FY25 Q1Speaker-labelled transcript0––
Feb 26, 2025Earnings call FY24 Q4Speaker-labelled transcript0––
Nov 11, 2024Earnings call FY24 Q3Speaker-labelled transcript0––
Aug 1, 2024Earnings call FY24 Q2Speaker-labelled transcript0––
May 6, 2024Earnings call FY24 Q1Speaker-labelled transcript0––
Feb 28, 2024Earnings call FY23 Q4Speaker-labelled transcript0––
Nov 1, 2023Earnings call FY23 Q3Speaker-labelled transcript0––

Citeparrot.markets, “Zeta (ZETA): earnings call word history”, as of Oct 23, 2026, https://parrot.markets/earnings/ZETA (CC BY 4.0)

Agents: this page as TSV at /api/v1/entity/zeta · words: /api/v1/history?entity=zeta · columnar JSON in #parrot-data · llms.txt · MCP