Earnings Transcript

Earnings Transcripts capture what executives say on quarterly earnings calls — the most candid public statements about a company's priorities, challenges, and technology investments.

We ingest transcripts from 4,000+ public companies on a weekly basis. Our model scans the full transcript — CEO remarks, CFO commentary, and analyst Q&A — to extract signals across 40+ subtypes. A single transcript typically produces 5-15 signals, each with direct quotes and speaker attribution. We prioritize statements with dollar amounts, percentages, or explicit commitments over generic commentary.

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Each transcript is classified into one or more of 40+ event subtypes (AI investments, budget increases, competitive intelligence, hiring surges, and more) — the specific business events we extract from executive commentary.

Available Subtypes (40+)

Subtype Enum	Category	Description
`acquisitionActivity`	growth	M&A activity — acquiring or being acquired
`aiInvestment`	budget	AI/ML specific investment or priority
`budget`	budget	General budget discussion
`budgetAndSpending`	budget	Budget and spending discussion
`budgetGrowth`	budget	Budget growth mentioned
`budgetIncrease`	budget	Specific budget increase announced
`capexDecrease`	budget	Capital expenditure decrease announced
`capexIncrease`	budget	Major capital expenditure increase announced
`cloudInvestment`	budget	Cloud infrastructure/migration investment
`competitiveIntelligence`	competitive	Competitive dynamics discussed
`competitivePressure`	pain	Competitive threats or market share loss
`competitorMention`	competitive	Competitor explicitly mentioned
`costPressure`	pain	Cost/margin pressures discussed
`customerExperienceFocus`	strategic	Customer experience improvement priority
`customerGrowth`	growth	Customer base expanding significantly
`customerWin`	growth	Significant customer win announced
`dataInvestment`	budget	Data infrastructure/analytics investment
`digitalTransformation`	strategic	Digital transformation initiative
`efficiencyFocus`	strategic	Operational efficiency as priority
`expansionPlan`	growth	Geographic or market expansion plans
`guidanceIncrease`	growth	Forward guidance raised
`guidanceDecrease`	pain	Forward guidance lowered
`headcountGrowth`	growth	Significant hiring or headcount expansion
`headcountReduction`	pain	Layoffs or headcount reduction
`internationalExpansion`	growth	International market entry or expansion
`marketShareGain`	growth	Gaining market share from competitors
`newProductLaunch`	strategic	New product or service launch announced
`partnershipAnnouncement`	strategic	Strategic partnership announced
`platformInvestment`	budget	Platform modernization or investment
`pricingChange`	strategic	Pricing model change announced
`revenueAcceleration`	growth	Revenue growth rate accelerating
`revenueDeceleration`	pain	Revenue growth rate slowing
`securityInvestment`	budget	Cybersecurity investment or priority
`supplyChainIssue`	pain	Supply chain challenges discussed
`sustainabilityInvestment`	strategic	ESG or sustainability investment
`talentInvestment`	budget	Talent acquisition or retention investment
`techDebtReduction`	strategic	Technical debt reduction initiative
`transformationProgram`	strategic	Major business transformation underway
`vendorConsolidation`	strategic	Consolidating vendors or tech stack

Example Signal

What a single entry looks like in a delivered signal file:

{
  "signal_id": "d4a71c83-6e9f-4b28-a3d7-52c0f8e19b46",
  "batch_id": "2026-03-15-00-00-00",
  "signal_type": "earnings_transcript",
  "signal_subtype": "aiInvestment",
  "detected_at": "2026-03-15T16:42:09.114583Z",
  "association": "company",
  "company": {
    "name": "CrowdStrike Holdings, Inc.",
    "domain": "crowdstrike.com",              // match on domain
    "linkedin_url": "linkedin.com/company/crowdstrike",  // or match on LinkedIn URL
    "industries": ["Computer and Network Security"],
    "employee_count_low": 5001,
    "employee_count_high": 10000,
    "ticker": "CRWD",
    "sector": "Technology"
  },
  "contact": [],
  "data": {
    "headline": "CrowdStrike committing $200M to Charlotte AI platform expansion with explicit ROI targets",
    "detail": "CEO George Kurtz stated CrowdStrike is allocating $200M in incremental R&D to expand Charlotte AI across all Falcon modules. He named specific use cases: automated threat hunting, natural-language SOC querying, and AI-driven incident response playbooks...",
    "relevance": 0.93,                      // 0.0-1.0; higher = more actionable for outreach
    "confidence": "high",                    // how certain this signal is accurate
    "sentiment": "positive",
    "sales_relevance": "Actively building AI-native security platform — potential integration partnerships or infrastructure needs",
    "signal_category": "budget",
    "evidence": [
      "We are committing an incremental $200 million to Charlotte AI over the next 18 months because we see this as the defining platform shift in cybersecurity...",
      "Charlotte AI will be embedded across every Falcon module by fiscal year-end. We're not bolting on AI — we're rebuilding the analyst workflow from the ground up..."
    ],
    "evidence_speakers": [
      {
        "speaker_name": "George Kurtz",
        "speaker_title": "CEO & Co-Founder"
      },
      {
        "speaker_name": "George Kurtz",
        "speaker_title": "CEO & Co-Founder"
      }
    ],
    "earnings_date": "2026-03-04",
    "fiscal_period": "Q4",
    "fiscal_year": 2026,
    "metric_dollar_millions": 200.0,
    "metric_headcount": null,
    "metric_pct": null,
    "competitors_mentioned": ["SentinelOne", "Palo Alto Networks"],
    "vendors_mentioned": [],
    "technologies_mentioned": [
      "Charlotte AI",
      "automated threat hunting",
      "natural-language SOC querying",
      "AI-driven incident response"
    ],
    "regions": []
  }
}

Field Reference

Standard envelope and entity fields are shared across all signals — see Schema and Resolution. The fields below are specific to this signal:

Signal-Specific Fields

The data object contains everything unique to this signal type — the intelligence extracted from the earnings transcript.

Field	Type	Description
`headline`	string	One-line headline summarizing the signal (e.g., "CrowdStrike committing $200M to Charlotte AI platform expansion"). Designed to be shown directly to end users. Typically 10–20 words, always includes the company name and the core commitment or event
`detail`	string	Multi-sentence analysis written for a salesperson or account executive. Explains what was said, who said it, why it matters commercially, and what kind of vendor or solution the company might need. Typically 3–5 sentences. Generated by synthesizing the full transcript, not just the quoted evidence
`relevance`	float (0.0–1.0)	How actionable this signal is for outreach. Higher = stronger commercial signal. Useful for prioritization and filtering
`confidence`	string	Confidence that this event was stated and categorized accurately. `high`, `medium`, or `low`. High confidence = explicit dollar commitment or named initiative. Useful for filtering in production
`sentiment`	string	Whether the disclosed event is favorable (`positive`), unfavorable (`negative`), or informational (`neutral`) for the company. Useful for segmenting outreach tone
`evidence`	array[string]	Direct quotes from the transcript that support this signal. Each element is one quoted passage, typically 1-3 sentences. These are verbatim excerpts — useful for displaying to users as proof or building personalized outreach
`evidence_speakers`	array[object]	Speaker attribution for each evidence quote, in the same order. Each object contains `speaker_name` (e.g., "George Kurtz") and `speaker_title` (e.g., "CEO & Co-Founder"). Useful for personalizing outreach based on who said what
`earnings_date`	string (date)	Date the earnings call took place. Useful for recency filtering and correlating with stock movements
`fiscal_period`	string	Fiscal quarter reported (e.g., "Q4", "Q1"). Useful for aligning signals to budget cycles
`fiscal_year`	integer	Fiscal year being reported on. May differ from calendar year depending on fiscal year-end
`metric_dollar_millions`	float \| null	Dollar amount in millions when an executive cites a specific figure (e.g., "$200M in AI R&D"). Null when no dollar amount is mentioned. Useful for sorting signals by financial magnitude
`metric_headcount`	float \| null	Headcount figure when cited (e.g., "hiring 500 engineers"). Null when no headcount is mentioned. Useful for identifying hiring-driven signals
`metric_pct`	float \| null	Percentage figure when cited (e.g., 0.35 = 35% growth). Null when no percentage is mentioned. Useful for filtering by growth rates
`competitors_mentioned`	array[string]	Competitors explicitly named by executives on the call. Empty array if none mentioned
`vendors_mentioned`	array[string]	Vendors or partners explicitly named. Useful for identifying existing tech stack and integration opportunities
`technologies_mentioned`	array[string]	Technologies, platforms, or tools referenced. Useful for building tech-stack-based targeting
`regions`	array[string]	Geographic regions referenced in the context of this signal. Empty array if no specific regions mentioned
`sales_relevance`	string	Brief phrase describing the outreach angle this signal creates. Useful as a prompt input or display label
`signal_category`	string	Category grouping (see Available Subtypes above). Useful for routing signals to the right sales motion

Timing & Delivery

detected_at is when we processed and extracted the signal from the transcript. Use earnings_date for when the call actually occurred.
One signal per subtype per company per earnings call. A single transcript can produce multiple signals across different subtypes, but won't fire the same subtype twice for the same call.
Each delivery arrives in a timestamped folder. Treat all signals in a new folder as recent — no need to diff against prior deliveries.

Coverage

Refresh: Weekly
Coverage: 7,000 public companies
Best for: Budget-cycle selling, identifying named technology investments, competitive intelligence from executive commentary

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See real delivered data → Sample Files

Example Signal

Field Reference

Signal-Specific Fields

Timing & Delivery

Coverage