Podcast Mentions (Company)

Overview

Podcast Mentions (Company) surface what's being said about a company on podcasts—strategy, funding, product moves, and pain points, pulled straight from the conversation.

We process episodes across a large catalog of business and industry shows, transcribe them, and extract structured signals about the companies discussed. Each mention is classified into one of 66 subtypes (funding, M&A, product launches, hiring, layoffs, security incidents, and more) and carries the exact quotes that support it, who said them and how they relate to the company, and our confidence in when the event took place.

The result: you know when a prospect just raised money, named a competitor, launched a product, or disclosed a pain point on air—timely, quotable triggers for outreach.

Available Subtypes

The signal_subtype field takes one of the values below. The Category column is an organizational grouping for readability only—it is not a field in the payload.

Subtype Enum	Category	Description
`acquisitionAnnounced`	strategic	Company announces intent or agreement to acquire another company
`acquisitionCompleted`	strategic	Company completes an acquisition
`aiInvestment`	technology	Company investing in AI capabilities, models, or tooling
`automationInvestment`	technology	Company investing in process or workflow automation
`boardChange`	leadership	Change to the company's board of directors
`bookingsDecline`	financial	Decline in bookings or new business discussed
`capacityConstraint`	operations	Production or service capacity limits
`capexIncrease`	financial	Increase in capital expenditure
`carbonCommitment`	market	Carbon-reduction or net-zero commitment
`cashFlowConcern`	risk	Cash-flow pressure or liquidity concern
`ceoChange`	leadership	CEO transition
`channelShift`	strategic	Shift in go-to-market or distribution channels
`cloudInvestment`	technology	Investment in cloud infrastructure or migration
`companyPodcastAppearance`	market	General appearance or feature of the company on a podcast
`competitorNamed`	competitive	A competitor is explicitly named or compared
`complianceBurden`	risk	Regulatory or compliance burden discussed
`costReduction`	financial	Cost-cutting or efficiency initiative
`ctoChange`	leadership	CTO transition
`customerChurn`	risk	Customer churn or account losses discussed
`customerConcentration`	risk	Revenue concentrated in a small number of customers
`cybersecurityIncident`	risk	Security breach or cyber incident
`cybersecurityInvestment`	technology	Investment in security tooling or programs
`dataInvestment`	technology	Investment in data infrastructure or analytics
`debtRefinancing`	financial	Refinancing or restructuring of debt
`digitalTransformation`	technology	Broad digital-transformation initiative
`divestiture`	strategic	Company divests a business unit or asset
`executiveOpinion`	leadership	An executive shares a notable opinion or point of view
`expansion`	operations	General business expansion
`fundingEvent`	financial	Funding round or capital raise
`growthSignal`	revenue	General growth indicator
`hiringSignal`	workforce	Hiring or headcount growth
`industryPrediction`	market	Prediction about industry direction or the future
`inflationImpact`	risk	Impact of inflation on the business
`internalControlWeakness`	risk	Weakness in internal controls
`internationalGrowth`	operations	Expansion into international markets
`inventoryIssue`	operations	Inventory problem (excess or shortage)
`laborShortage`	workforce	Labor or talent shortage
`layoffs`	workforce	Workforce reductions
`leadershipChange`	leadership	Leadership change other than CEO or CTO
`legacyModernization`	technology	Modernizing legacy systems
`litigationMaterial`	risk	Material litigation or legal action
`logisticsChallenge`	operations	Logistics or shipping challenge
`majorContractLoss`	revenue	Loss of a major contract
`majorContractWin`	revenue	Win of a major contract
`marginPressure`	financial	Pressure on profit margins
`marketExpansion`	market	Expansion into new markets or segments
`marketShareLoss`	competitive	Loss of market share
`painPointDisclosed`	risk	A business pain point or challenge disclosed
`partnership`	strategic	Partnership or alliance announced
`platformStrategy`	technology	Platform or ecosystem strategy
`pricingPressure`	competitive	Pricing pressure discussed
`productLaunch`	technology	New product or service launched
`qualityIssue`	operations	Product or service quality issue
`recurringRevenueShift`	revenue	Shift toward a recurring-revenue model
`regulatoryFine`	risk	Regulatory fine or penalty
`restructuring`	strategic	Organizational restructuring
`restructuringCharge`	financial	Restructuring charge taken
`revenueAcceleration`	revenue	Revenue growth accelerating
`revenueDeceleration`	revenue	Revenue growth slowing
`softwareImplementation`	technology	Implementing new software or systems
`spinoff`	strategic	Spinning off a unit into a separate entity
`strategyShift`	strategic	Notable change in company strategy
`supplyChainDisruption`	operations	Supply-chain disruption
`sustainabilityInvestment`	market	Investment in sustainability or ESG
`techAdoption`	technology	Adoption of a new technology
`techMigration`	technology	Migration between technologies or platforms

Schema

{
  "signal_id": "2d4cbad6-026d-505d-bfe9-dafa6de6d6ab",
  "signal_type": "podcast-company",
  "signal_subtype": "industryPrediction",
  "signal_name": "Databricks · industryPrediction · ongoing_state (2026-06)",
  "detected_at": "2026-08-24T10:25:03.000Z",
  "association": "company",
  "company": {
    "name": "Databricks",
    "domain": "databricks.com",
    "linkedin_url": "linkedin.com/company/databricks",
    "industries": ["Software Development"],
    "employee_count_low": 10000,
    "employee_count_high": 10000,
    "revenue": "1 Billion and Over",
    "description": "Databricks is the Data and AI company."
  },
  "contact": null,
  "data": {
    "headline": "Databricks · industryPrediction · ongoing_state (2026-06)",
    "speaker": "Maggie Fanari",
    "speaker_relation": "third_party",
    "quotes": [
      "We also shareholders in companies like Anthropics and Databricks who are doing really really well and continue to compound growth",
      "Databricks versus Snowflakes is an interesting thing to watch because Databricks' valuation in public markets has already surpassed Snowflakes in public.",
      "It's an incredible business that's having this sort of reacceleration because of AI. It's built this platform that is sticky and they just keep adding products, keep sort of expanding into adjacencies like security, customer data for marketing."
    ],
    "evidence": "We also shareholders in companies like Anthropics and Databricks who are doing really really well and continue to compound growth",
    "timing": "ongoing_state",
    "event_date": "2026-06",
    "is_ad": false,
    "podcast_name": "Switch Your Money On",
    "episode_title": "Special Guest Maggie Fanari on AI and Global Investing",
    "episode_url": "https://shows.acast.com/switch-your-money-on/episodes/special-guest-maggie-fanari-on-ai-and-global-investing",
    "episode_id": "57076815260",
    "published_at": "2026-07-02",
    "recorded_at_estimate": "2026-06-16",
    "date_confidence": "exact",
    "transcript_source": "transcript"
  }
}

Field Reference

Core Fields

Field	Type	Required	Description
`signal_id`	string (UUID)	✓	Unique identifier for this signal
`signal_type`	string	✓	Always `"podcast-company"`
`signal_subtype`	string	✓	Specific signal subtype (see allowed values above)
`signal_name`	string	✓	Human-readable label for the signal (mirrors `data.headline`)
`detected_at`	string (ISO 8601)	✓	When Autobound detected/ingested the signal (not the episode date—see `data.published_at`)
`association`	string	✓	Entity association type—always `"company"`
`company`	object	✓	The company the signal is about (see Company Object)
`contact`	null	✓	Always `null` for company-level signals

episode_id is nested under data, not at the top level. There is no parent_signal_id field.

Company Object

Field	Type	Required	Description
`company.name`	string	✓	Company discussed
`company.domain`	string	✓*	Company domain (primary match key)
`company.linkedin_url`	string (URL)	✓*	Company LinkedIn URL (alternate match key; may be `""`)
`company.description`	string		Company description (nullable)
`company.industries`	array[string]		Industry classifications (may be empty)
`company.employee_count_low`	integer		Lower bound of employee-count range (`0` when unknown)
`company.employee_count_high`	integer		Upper bound of employee-count range (`0` when unknown)
`company.revenue`	string		Revenue band when available via enrichment (e.g. `"1 Billion and Over"`); nullable/absent

^{*A company signal requires at least one of domain or linkedin_url.}

Data Object

Field	Type	Required	Description
`data.headline`	string	✓	One-line summary of the signal (mirrors `signal_name`)
`data.speaker`	string		Name of the person who made the statement on the episode
`data.speaker_relation`	string		Speaker's relationship to the subject company—e.g. `own_company` (an exec/employee of the company) or `third_party` (someone else discussing it)
`data.quotes`	array[string]	✓	Verbatim transcript quotes supporting the signal
`data.evidence`	string		The primary supporting quote (typically the first of `quotes`)
`data.timing`	string		When the described event occurs relative to the episode—e.g. `ongoing_state`, `in_progress`, `completed`, `planned`
`data.event_date`	string		Best-estimate month of the event (`YYYY-MM`)
`data.event_date_text`	string		Raw temporal phrase from the transcript (e.g. `"these days"`), when present
`data.is_ad`	boolean	✓	Whether the segment came from an ad / sponsor read
`data.podcast_name`	string	✓	Name of the podcast show
`data.episode_title`	string	✓	Title of the episode
`data.episode_url`	string (URL)		Link to the episode
`data.episode_id`	string	✓	Source podcast episode identifier (dedup key)
`data.published_at`	string (date)	✓	Episode publication date (`YYYY-MM-DD`)
`data.recorded_at_estimate`	string		Best estimate of when the episode was recorded
`data.date_confidence`	string		Confidence in the date fields: `exact` or `inferred`
`data.transcript_source`	string		Origin of the analyzed text (e.g. `transcript`)

Coverage

Refresh: Monthly
Association: Company-level
Subtypes: 66