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# 1. Scan a global watchlist for "agentic AI" mentions in Q1 2026
# → per-ticker mention counts across markets, in one request
curl -sG https://earningscalls.dev/api/v1/search/by_ticker \
-H "X-API-Key: ec_..." \
--data-urlencode 'q="agentic AI"' \
--data-urlencode 'tickers=NVDA,SAP,SHEL' \
--data-urlencode 'date_from=2026-01-01' \
--data-urlencode 'date_to=2026-04-30'
// example response · ~312 ms
{
"query": "\"agentic AI\"",
"tickers_scoped": 3,
"total_companies": 3,
"total_calls": 7,
"results_count": 3,
"results": [
{ "ticker": "NVDA", "company_name": "NVIDIA Corporation", "calls_matched": 4, "last_match_date": "2026-03-17T16:00:00.000Z" },
{ "ticker": "SAP", "company_name": "SAP SE", "calls_matched": 2, "last_match_date": "2026-04-23T21:00:00.000Z" },
{ "ticker": "SHEL", "company_name": "Shell plc", "calls_matched": 1, "last_match_date": "2026-02-05T14:30:00.000Z" }
]
}Four primitives that turn raw earnings calls into a clean dataset your strategy can consume.
Every segment pre-tagged. Five categories with verified counts: executive (826k), analyst (470k), operator (208k), attendee (33k), shareholder (4k). 93% carry the speaker's name.
GET /api/v1/speakers/:idSweep the live archive for phrases like "margin pressure" in one query. Boolean operators, exact phrases, ticker filters across global markets.
GET /api/v1/search?q=…Scan up to 500 tickers in a single request. Per-ticker counts, sector breakdown, last-match date — screen a global universe in one call.
GET /api/v1/search/by_tickerIncremental sync via since / after_id. Re-runnable, idempotent. New calls land within hours of the wire and flow straight into your pipeline.
GET /api/v1/transcripts/recentChange the ticker, click Run, see the actual response.
GET /api/v1/search?q=agentic AI&type=speakers&speaker_type=Executive&ticker=NVDA&limit=5
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