Particle API

Returns a paginated list of companies, ranked by news coverage (most-covered first), then name. Filter by entity slug (e.g., 'apple'), ticker, domain, CIK, or QID. Search by name or fetch updates since a timestamp. With no search or filter, the list contains only companies with news coverage; a filter returns every matching company, with uncovered ones last. A bulk ids lookup is not ranked: it returns companies in request order, unpaginated.

Returns a single company by slug (e.g., 'apple'), domain (e.g., 'apple.com'), or ID.

Returns a paginated list of competitors for a company, ordered by prominence (news coverage volume, market cap, podcast appearances, Wikidata notability) so the largest / most-newsworthy competitors come first. Each result includes a competitive basis describing the relationship. Identify the company by slug (e.g., 'apple'), domain, or ID.

Returns every known third-party profile and identifier for the company — LinkedIn, social accounts, its registrable domain, Wikidata QID, SEC CIK, and stock tickers — as one list. Identify the company by slug (e.g., 'apple'), domain, or ID. Pair it with GET /v1/entities/lookup, which resolves any of these identifiers back to the company.

Returns a paginated list of people associated with a company (executives and other known roles), current roles first and most-recently-joined first. Each person carries the full Person payload — bio, role history, external profile links, and knowledge-graph cross-reference. Set current_only=false to include historical roles, or filter by role title. Identify the company by slug (e.g., 'apple'), domain, or ID.

Returns advertising intelligence for a specific company across the podcast ecosystem, including reach metrics and recent ad placements. Identify the company by slug (e.g., 'apple'), domain, or ID.

Returns a newest-first, keyset-paginated feed of physical podcast ad placements with a known episode publication time, attributed to a company, with episode and podcast context plus every company-scoped sponsor attribution.

Returns podcasts ranked by exact company-linked ad count, with company-wide sponsor filters, per-podcast sponsor breakdowns, recent preview segments, and cursor pagination.

Returns shows the company does NOT advertise on, ranked by how related they are to the shows it DOES — the buy-side prospect list. Each seed show counts by how much the company advertises there, so a list is anchored on its main venues; every show it has ever bought is excluded. Each row carries the podcast, a calibrated score in (0,1), a band (strong / moderate / weak), and with include=via the company's own shows that led there. Companies with no podcast advertising get an empty page.

Returns the product hierarchy for a company as a nested tree. Segments contain product lines, which contain individual products. Identify the company by slug (e.g., 'apple'), domain, or ID. Defaults to active products only.

List knowledge graph entities (people, organizations, places) across all podcast content. Defaults to the most frequently appearing entities, ranked by the number of distinct podcast episodes featuring them. Filter by podcast slug or ID, or fetch specific entities with `ids`. To search by name, use GET /v1/entities/search.

Resolves external identifiers — LinkedIn slugs, social handles, company domains, stock tickers, SEC CIKs, Wikidata QIDs — to the people and companies that carry them. It is the reverse of GET /v1/people/{slug}/external-links and GET /v1/companies/{id}/external-links. Pass a comma-separated `identifier` list (up to 100 per call); `platform` is optional, so a handle with no known source still resolves. A full profile URL works in place of a bare identifier and the platform is inferred from it, and the stored form is matched for you — pass `satyanadella` or the profile URL, not `in/satyanadella`. Each result echoes the input identifier and carries a `matches` array, because an identifier is not unique to an entity: a LinkedIn profile claimed by two duplicate person records resolves to both, and `match_count` reports the total. Unresolved identifiers come back with an empty `matches`, so a bulk caller never has to reconcile a shorter response against a longer request. Correlate by the echoed `identifier` rather than by position, since duplicate identifiers collapse to one result. Use GET /v1/entities/search instead when you have a name rather than an identifier, and GET /v1/podcasts/lookup or GET /v1/podcasts/episodes/lookup for podcast and episode identifiers.

Find a person, company, or knowledge graph entity by free-text query — a name, partial name, nickname, stock ticker, @handle, or website domain. Returns the best matches ranked by relevance, each tagged with a `match_quality` so you can tell an exact identification from a fuzzy guess. Use it to turn what a user typed into a specific entity — for example before creating an alert to watch it for podcast mentions. Unlike a knowledge graph entity, a result's top-level `type` may be `person`, `company`, or `knowledge_graph_entity`; pass its `id` or `slug` to the matching resource endpoint (/v1/people, /v1/companies, /v1/entities), or its `id` to alert creation.

Returns the entity categories supported as values for the `type` query parameter on /v1/entities and the `entity_type` query parameter on /v1/podcasts/episodes/search.

Returns a single knowledge graph entity by slug (e.g., 'sam-altman', 'apple') or ID. A person slug or ID (as returned by a `person` hit on /v1/entities/search) also resolves, to that person's linked knowledge graph entity.

Ranks the people listed under an occupation or field of research, most likely first, with their expertise as GET /v1/people/{id}/expertise describes it. Narrow by standing, seniority, whether they still practice the occupation, how they know their field, a second field, or their employer. Occupations and fields accept a code, slug, or title (browse them with GET /v1/people/occupations and GET /v1/people/fields). Hosts, guests, panelists, and correspondents are read once linked to a podcast appearance.

Lists one level of the ANZSRC 2020 Fields of Research: the divisions, the groups of a division, or the fields of a group. Every code, slug, and title listed here is accepted wherever speaker expertise is filtered by field.

Returns one ANZSRC 2020 field of research with its parent and children. The {code} parameter accepts the code, slug, or title.

Ranks the people listed under an ANZSRC 2020 field of research by their podcast guest and panelist appearances in a window of publication dates (the last 30 days by default), then by the distinct shows they appeared on. The {code} parameter accepts the code, slug, or title. For the shows that book them, use GET /v1/people/fields/{code}/podcasts.

Ranks the shows by their guest and panelist appearances of people listed under an ANZSRC 2020 field of research in a window of publication dates (the last 30 days by default), then by how many distinct such people they booked. The {code} parameter accepts the code, slug, or title.

Lists one level of an official occupation standard: SOC 2018 major groups, or the detailed occupations under one; or, for ISCO-08, the groups SOC 2018 maps to, listed flat: 436 unit groups and the two minor groups (211, 315) the crosswalk maps an occupation to whole. Every code, slug, and title listed here is accepted wherever speaker expertise is filtered by occupation.

Returns one SOC 2018 or ISCO-08 occupation with its parent, its children, and the same occupation in the other standard per the official BLS crosswalk. The {code} parameter accepts the code, slug, or title.

Ranks the people listed under an occupation by their podcast guest and panelist appearances in a window of publication dates (the last 30 days by default), then by the distinct shows they appeared on. Raise min_podcasts to favor guests booked across the medium over one show's regulars. Appearances follow the rules of GET /v1/podcasts/episodes?guest_occupation=: settled links only, and none whose analysis doubts the guest is the person linked. The {code} parameter accepts the code, slug, or title. For the shows that book them, use GET /v1/people/occupations/{code}/podcasts.

Ranks the shows by their guest and panelist appearances of people listed under an occupation in a window of publication dates (the last 30 days by default), then by how many distinct such people they booked. The {code} parameter accepts the code, slug, or title. For the guests themselves, use GET /v1/people/occupations/{code}/guests.

Returns the comprehensive Person payload including display name, slug, headshot, curated bio, the Person's company-role history (most recent first), known third-party profile links, and an optional knowledge-graph cross-reference. The {id} parameter accepts the Person slug (recommended) or the encoded Person UUID.

Returns what the Person's records say about their expertise, in words: the SOC 2018 and ISCO-08 occupations and ANZSRC 2020 fields of research they are listed under (each usable as a filter by code, slug, or title), how their standing is recognized, their seniority and experience, how they know their field, where they work, and a sentence stating their credentials. Hosts, guests, panelists, and correspondents are read once linked to a podcast appearance; anyone else returns 404. The {id} parameter accepts the Person slug (recommended) or the encoded Person UUID.

Returns every known third-party profile (LinkedIn, Wikipedia, social) for the Person. Discovery happens asynchronously via the v1.person.created enrichment subscriber; a freshly-created Person may not yet have all its profiles populated. Any identifier here resolves back to the Person through GET /v1/entities/lookup.

Returns a paginated list of podcasts, with filters for topic, language, suitability tier, popularity, and format. The `q` parameter searches by name and is kept for backwards compatibility — `GET /v1/podcasts/search` is the canonical way to search podcasts, and `q` here may be removed in a future version.

Returns pairs of sponsors that frequently appear together in the same podcast episodes.

Returns the top podcast advertising sponsors ranked by the specified metric, with optional time range and company filtering. All-time rankings — and two day-anchored windows: the trailing 7 days (since = UTC today−7d, no until) and the 7-day window ending 30 days ago (since = today−37d, until = today−30d) — reflect periodically refreshed snapshots; other time-windowed and company-filtered results may be cached for up to one hour.

Returns the top 10 advertising sponsors of the trailing 7 days ranked by the chosen metric, each with its rank movement versus the equivalent 7-day window ending 30 days ago. Every caller gets the same board regardless of plan, so unlike get-advertising-leaderboard this endpoint requires no premium access and is safe to render for signed-out visitors. Use get-advertising-leaderboard for deeper pages, other time windows, and company or publisher filtering.

Ranks podcast publishers by an advertising activity metric across their entire catalog. ads_per_active_podcast is the monetization-density metric — small sub-networks (e.g. 'iHeartPodcasts and The Volume', 'Dan Patrick Network') typically rank far above broad catalogs on this dimension.

Returns a paginated list of podcast advertising sponsors, optionally filtered by name search or company.

Surfaces advertisers whose podcast ad volume is accelerating. Each row compares the sponsor's ads aired in the trailing window (default 7 days) against the equal-length window immediately before it, ranked by the delta. Windowing follows episode publication dates, so rankings reflect when ads aired, not when they were ingested. Results may be cached for up to one hour.

Returns a single advertising sponsor with activity metrics. The {id} path parameter accepts a sponsor ID, a company ID, a company domain, or a company slug.

Returns a paginated list of podcasts where the sponsor advertises, ordered by the number of episodes featuring the sponsor.

Returns the podcast publishers a sponsor advertises across, ordered by podcast coverage (the count of distinct publisher podcasts where the sponsor appears). Surfaces the bundle-buy signature: a sponsor showing 60–100% coverage on multiple publishers is doing network buys, not per-show buys.

Returns the individual ad segments attributed to a sponsor, ordered by episode publication date descending, optionally scoped to a single podcast. Results are consistent with the ad_count values from the sponsor podcasts endpoint. Network promos are excluded.

Returns time-bucketed ad placement counts for a sponsor or company, split into host-read and pre-recorded placements, plus range totals. Exactly one of sponsor_id or company_id is required; company_id aggregates across every sponsor alias linked to the company. Pass podcast_id or publisher_id to scope the counts to one show or network, matching the mentions timeseries so both series can be charted under the same scope. Counts use the same attribution as the sponsor podcasts and segments endpoints, so bucket sums agree with their ad_count values. Network promos are excluded.

Returns a paginated leaderboard ranking publishers by a chosen bias metric: most_left_leaning, most_right_leaning, most_political, most_diverse, most_monolithic, or most_analyzed. min_analyzed_podcasts and min_political_podcasts gate small-sample publishers from the ranking. Optional political_context, since, and until restrict the corpus before aggregation.

Returns a paginated list of publishers whose analyzed catalog contains at least min_count podcasts in the requested bias bucket, ranked by raw count or by share of the publisher's analyzed catalog. Useful as a flip of the publisher bias profile — answers 'which publishers carry the most RIGHT-leaning shows?'.

Returns AI-extracted highlight clips across podcast episodes, ranked by engagement potential. Filter by podcast, episode, clip type, minimum engagement score, or speaker (the person talking in the clip). For text-based clip discovery (semantic, keyword, or entity mention search), use GET /v1/podcasts/episodes/search — matching clips are embedded inside each search result alongside the parent segment and dialogue.

Returns a single clip by its unique identifier.

Returns the diarized transcript for a specific clip.

Returns every entity chart with the headline state of its current edition: the edition date, whether narratives have been written yet, and what sits at rank 1. Each chart's `source` says whether its entries measure entity mentions or guest appearances, `group` tabs the directory into overall, entertainment, and sports, and `windows` lists the windows that chart publishes. Use the returned `category_slug` to fetch a full chart. Every chart lists, but `leader` is omitted for charts the caller may not read: an API key reads every chart, while a session without paid Radar access reads only the `all` chart.

Returns the current edition of one chart, each entry with its movement since the previous edition. How the chart ranks depends on the chart. The per-category mention charts (`tv-series`, `movies`, `video-games`) rank entities by how many distinct podcasts mentioned them organically in the window, which is `podcast_count`. The sports charts (`nfl`, `nba`, `mlb`, `nhl`, `college-football`, `wnba`, `college-basketball`, `soccer`, `golf`, `tennis`, `formula-1`, `nascar`, `pro-wrestling`) rank the players, teams, coaches, and events resolved into that league or sport rather than a single entity type, so their entries mix subject kinds. A sports chart blends each member's reach, measured against members of the same kind, with 52-day elevation, so its ranks do not follow `podcast_count`, and league organizations such as divisions sit below the top 10. The composite charts rank by a blend of reach and 52-day elevation, so their ranks do not follow `podcast_count`: `all` draws on a wider curated pool of entity types — people, books, music, brands, companies and organizations, sports, events, and products as well as the three published categories — while `all-entertainment` and `all-sports` pool only their own group's charts, so an entry there always has a sibling chart to drill into. The guests chart ranks people by the distinct shows they appeared on. When the narrative pipeline has explained an entry, `why` carries a one-line explanation and, when one was captured, the verbatim quote with its source episode and the offsets to play it from; `why.verifiable` says whether that episode still exists. `why` is absent for entries with no explanation, which is normal: a flat hold or an ordinary decline is deliberately left unexplained. Access: an API key reads every chart at full depth. A session without paid Radar access reads only the composite `all` chart, its top 10 entries with the signal operands (`signals.trend_*`, `signals.elevation_*`) omitted, and is refused the per-category charts. The composite charts (`all`, `all-entertainment`, `all-sports`) and every sports chart except `nfl`, `nba`, `mlb`, `nhl`, and `college-football` publish the 7d window only, so requesting one with `window=24h` is a 422.

Returns a paginated list of podcast episodes across all podcasts. Filter by podcast slug or ID, entity slug or ID, company slug or domain, date range, and language.

Resumable, strictly-ordered poll of episodes as they are ingested — the all-plans pull alternative to the Enterprise stream. Subscribe to a milestone (default transcribed); each call returns episodes that reached it since your cursor, in ingestion order, with a cursor to poll again. Filter by podcast_ids, topic_ids, and/or popularity_threshold — a filter is required, and coverage is capped at 100 podcasts. Enterprise organizations are exempt: they may poll unfiltered (the pull form of the stream) and popularity_threshold applies uncapped.

Resolves one or more external episode identifiers or links to Particle episodes. Paste a Spotify, Apple Podcasts or YouTube episode link as it is and it is resolved by the platform it points to; links from different platforms may share a call, and `platform` is then optional. Bare identifiers need `platform`: Apple Podcasts episode IDs (the `?i=` value in an Apple Podcasts URL), Spotify episode IDs and YouTube video IDs; the episode's RSS `guid` — the identifier the publisher's own feed carries, and the one most podcast tooling keys on — and a `podcastindex` episode ID; and hosting-platform IDs read from the episode's audio URL: `megaphone`, `omny`, `acast` and `art19`. Pass a comma-separated list (up to 100 per call). Guids and hosting-platform IDs are matched exactly as supplied and never read as links, since a guid is whatever string the feed carries and is often itself a URL. Because identifiers are comma-separated, a guid that itself contains a comma cannot be expressed here — about 1.2% of episodes, almost all of them SoundCloud-hosted, whose guids take the form `tag:soundcloud,2010:tracks/123`; look those episodes up by another identifier. Each result echoes the input identifier alongside the matched episode and its podcast; unresolved identifiers omit the `episode` field entirely so bulk callers can correlate inputs and outputs by key presence without doing a separate join. This is the episode-level counterpart to GET /v1/podcasts/lookup. Coverage is partial and differs by identifier, so a miss is not an error: Apple exposes only the most recent episodes of each show, so older back-catalogue episodes may not resolve; the first lookup of a Spotify episode can take a few seconds, and a call resolves at most 10 Spotify episodes not looked up before — retry the rest; YouTube resolves any video already discovered for an episode; `guid` is the broadest at roughly 89% of episodes; and a hosting-platform ID resolves only for episodes served by that host.

To find podcasts (shows) by name or topic, use `/v1/podcasts/search?q=…`. This endpoint searches *inside* episode dialogue — by meaning (`semantic_search`), by exact phrase (`keyword_search`), or both at once (hybrid). Each result is a segment of an episode, returned with bounded preview windows of dialogue and any highlight clips that overlap the segment. For "every line about a person or company" use `/v1/podcasts/mentions` instead — that endpoint returns episode-grouped mention windows with line-level highlights and is shaped for the read-everything-about-X use case. `entity_id` and `company_id` here narrow the result set to episodes featuring the resolved entity, but the ranking still comes from `semantic_search` / `keyword_search`.

Returns time-bucketed counts of episodes matching the same filters as GET /v1/podcasts/episodes, plus range totals. Use it for appearance, publication, or topic trend charts instead of paging the episode list or search once per period. keyword_search counts episodes whose transcripts match (exact counts, no pagination floors) and adds per-bucket mention_count plus total_mentions; semantic_search does the same by meaning, using the search endpoint's similarity threshold, and requires since. The two cannot be combined. Buckets are UTC-aligned, zero-filled, and Monday-aligned for weeks. A since or until inside a bucket produces a partial first or last bucket labeled with the full bucket's start date. Requires at least one of entity_id, person_id, company_id, podcast_id, keyword_search, semantic_search, guest_occupation, or guest_field; the other guest_ filters narrow one of these. Omitting since aggregates all time, except with semantic_search, which always requires it. Ranges are capped at 1000 buckets.

Returns a single episode by its unique identifier.

Returns the advertising spots detected in a specific episode, including the sponsor, the linked company in the knowledge graph, the advertised product or offer, the read type (HOST_READ vs PRE_RECORDED), and the placement (PRE_ROLL/MID_ROLL/POST_ROLL). Network promos are excluded.

Returns the AI-extracted highlight clips for a specific episode, sorted by engagement score.

Returns knowledge graph entities mentioned in a specific episode, with salience scores and occurrence counts.

Returns each guest on the episode with how the episode used their expertise (whether it is within their field, whether they are there mainly to promote something, and how the episode introduced them) and what their records say about it, as GET /v1/people/{id}/expertise describes it. Guests the episode has not been read for yet are omitted, as are guests whose episode may describe a different person than the one linked.

Returns episodes from other shows that cover the same story or subject as this episode, best first: a live nearest-neighbour search over episode content, reranked on shared salient entities, shared topics and a shared news story. Each result carries a calibrated score and a band (strong / moderate / weak); pass include=basis to see the signals behind each match. Use published_within_days for 'who else covered this story this week'; pass same_podcast=true to admit the show's own episodes. Returns an empty page when the episode has no embedded content yet, and 404 when the episode is not found.

Returns the AI-identified segments for a specific episode in chronological order.

Returns the identified speakers in a specific episode with their roles and speaking durations.

Returns the topic taxonomy classifications for a specific episode.

Returns the diarized transcript for a podcast episode. Supports dialogue (speaker-attributed lines), plain text, and SRT subtitle formats. Optionally filter by speaker or time range.

Finds all mentions of a specific entity within an episode's transcript and returns each mention with surrounding dialogue context. Useful for seeing exactly where and how an entity is discussed.

Returns one segment of an episode's transcript: the latest segment starting at or before `at` (seconds), or the opening segment when `at` is omitted. A moment falling between two segments resolves to the earlier one, and a moment outside the episode clamps to the first or last segment, so the returned range does not always contain `at` — `segment_start_seconds` and `segment_end_seconds` report what was actually returned. Every caller gets the same excerpt for a given moment regardless of plan, so unlike the full transcript this response is cacheable and safe to render for signed-out visitors. Use this to open a deep link on a moment; use get-episode-transcript for the whole episode.

Returns the word-level timestamped transcript for a podcast episode. Use start/end to extract a time range, limit/cursor to paginate (defaults to all words), and exclude_spacing=true to drop the inter-word whitespace tokens that NLP/LLM consumers don't need.

Returns a paginated directory of Persons who have appeared on at least one podcast episode in a non-host listing role. Filter by name, topic, podcast, date, and brand-safety tier.

Surfaces guests who are currently making the podcast rounds — the kind of cross-show interview activity that signals a book launch, product unveil, news-cycle moment, or new-on-the-scene debut. Each row is a guest whose recent activity is materially elevated above their own historical baseline AND who has appeared on multiple distinct podcasts inside the window with substantive (5+ minute) interviews. Filter by recency window, topic, brand-safety tier, and an optional first-appearance cutoff to find people new to the scene. This is not a leaderboard of perennial podcast regulars, recurring co-hosts, or daily news-segment contributors — those are filtered out by design; use /v1/podcasts/guests for a steady-state directory. Statistics refresh hourly.

Returns the lifetime profile for a podcast guest including their Person identity (name, slug, headshot, current title/company), total appearances, distinct podcasts, role mix, and the most-frequent shows they've appeared on. The {id} parameter accepts the Person slug (recommended), the person's knowledge-graph entity slug, or the encoded Person UUID.

Returns the chronological list of episodes a guest has appeared on, most recent first. Supports filtering by podcast, role, topic, date range, brand-safety tier, and minimum speaking duration.

Returns the distinct set of podcasts a guest has appeared on, with per-podcast appearance counts, first/last appearance dates, and the podcast's brand-safety and bias attributes when evaluated.

Returns shows the person has NOT appeared on, ranked by how related they are to the shows that booked the person as a guest — the pitch list. Seeds count once per publisher (an outlet's sibling feeds are one venue) and correspondent segments for the person's own newsroom do not seed it. Each row carries the podcast, a score in (0,1), a band (strong/moderate/weak), and with include=via the person's own shows that led to the recommendation, so a pitch can cite them ('hosts of X and Y book guests like you'). Circuit regulars are discounted upstream so the list is about fit, not fame. Recommendations are derived from each show's precomputed related set (GET /v1/podcasts/{id}/related); a person with no guest or panelist bookings on record (host and correspondent appearances do not seed the list), or whose shows have no computed related set yet, gets an empty page. For the shows a person has already been on, use GET /v1/podcasts/guests/{id}/podcasts.

Returns the distribution of IAB Tech Lab brand-suitability tiers across the podcasts a guest has appeared on, plus the most-frequently flagged categories observed in those shows. This measures the guest's exposure across the shows they've appeared on — not a verdict on the guest themselves.

Resolves one or more external platform identifiers (Apple Podcasts collection IDs, Spotify show IDs, YouTube channel IDs, …) or show links — or RSS feed URLs via `platform=rss` — to Particle podcasts. Paste a show's Apple Podcasts, Spotify or YouTube URL, its page on any other platform, or its feed URL as it is and it is resolved by what it points to; `platform` is then optional and links from different platforms may share a call. Bare identifiers need `platform`. Pass a comma-separated list (up to 100 per call). Each result echoes the input identifier alongside the matched podcast; unresolved identifiers omit the `podcast` field entirely so bulk callers can correlate inputs and outputs by key presence without doing a separate join. Use this when you already hold platform-native IDs and want a deterministic mapping; for fuzzy name search use GET /v1/podcasts/search.

Returns every line of dialogue that mentions a person or company, grouped by episode and ordered by recency. Each result is one episode plus all of that episode's mention windows — a window is a contiguous range of dialogue containing the mention with `context_lines` of surrounding context, and lines containing the mention have `is_mention=true`. Mentions inside ad reads are excluded by default; pass `include_ads=true` to include them. Subjects with no knowledge graph entity (most podcast guests, smaller companies) are matched by scanning dialogue for their name verbatim instead of curated entity tags; such pages carry `matched_by: "name"` and echo the resolved `person` or `company` instead of `entity`. Use this endpoint for the "every line about X" use case. For finding dialogue by topic or exact phrase use `/v1/podcasts/episodes/search` instead.

Returns the podcasts that mentioned a person, company, or entity in a window, each with its episode and mention line counts there and in the equal-length window just before it, labeled `new`, `continuing`, or `dropped`: which shows picked the subject up, which kept talking about it, and which went quiet, without paging the mentions themselves. The totals count every podcast, whatever the page or `change` filter, and the current window's match `/v1/podcasts/mentions/timeseries` for the same filters. Mentions inside ad reads are excluded unless `include_ads=true`. The window defaults to the last 7 days and may span 90; the response echoes its exact bounds, so pass `start` and `end` back as since and until when paging. The newest day fills in as episodes are processed, usually within a day, so end the window earlier for a settled comparison. `interval` adds each podcast's buckets over the current window. Requires entity_id or company_id. For the lines, call `/v1/podcasts/mentions` with the row's `podcast_id` and the same since and until. For the total over time, use `/v1/podcasts/mentions/timeseries`.

Splits the podcast lines mentioning an entity by the occupations or fields of the people who said them: what share of what is said about it comes from, say, journalists or economists. A line counts when its speaker is linked to a person with an expertise reading and, for a guest, the appearance read does not doubt it is them; a person counts under every code listed for them, so shares can sum past 1. Ad reads are excluded unless include_ads. The window defaults to the last 30 days and may span 365; interval adds each group's mentions per bucket. Requires entity_id or company_id. For the mentions themselves, use GET /v1/podcasts/mentions; for their counts over time, GET /v1/podcasts/mentions/timeseries.

Returns time-bucketed counts of episodes mentioning an entity, plus per-bucket mention line and distinct podcast counts and range totals — the aggregate twin of `/v1/podcasts/mentions`. For windows the search can fully enumerate, bucket counts match what it returns: mentions inside ad reads are excluded by default (pass `include_ads=true` to count them), so use this for mention trend charts instead of paging the search once per period. Buckets are UTC-aligned, zero-filled, and Monday-aligned for weeks; a bucket the window cuts through, such as the current week of a window running to now, is marked `partial`, so compare full buckets with each other. Requires entity_id or company_id. Omitting since aggregates all time. Ranges are capped at 1000 buckets. For which podcasts carried the mentions, compared with the period before, use `/v1/podcasts/mentions/by-podcast`. For appearance trends by speaker role across episode-level filters (language, duration, keyword_search) use `/v1/podcasts/episodes/timeseries` instead; its `role=mention` counts include ad reads.

Returns a paginated list of podcast publishers, ordered by catalog size (largest first, the default) or alphabetically by name. Filter with q (case-insensitive name/slug substring; exact name matches sort first). Each entry includes the publisher name, slug, and the number of podcasts attributed to the publisher.

Returns a single podcast publisher by slug (e.g., 'goalhanger', 'iheartpodcasts', 'bbc-radio-4') or ID. Slugs are human-readable identifiers populated for the vast majority of publishers and are the recommended way to reference a publisher in URLs. The ID always works as a fallback for publishers whose name doesn't slugify.

Returns advertising intelligence rolled up across every podcast attributed to the publisher: total ads, unique sponsors, episode reach, host-read vs pre-recorded mix, the top sponsors, and the count of network buyers (sponsors hitting at least 3 podcasts and at least 25% of the publisher's catalog).

Returns a paginated list of the publisher's podcasts ordered by total ad count. Differs from /v1/podcasts/publishers/{id}/podcasts (popularity-ordered) by exposing monetization data instead of audience signals: ad_count, unique_sponsors, episodes_with_ads, avg_ads_per_episode, and the host-read/pre-recorded breakdown.

Returns a paginated list of sponsors active across the publisher's catalog. Each entry includes the bundle-buy signal — podcast_coverage (distinct podcasts in the catalog where the sponsor appears) and coverage_share (the same as a 0..1 fraction of the publisher's catalog). Sort by podcast_coverage and combine with min_podcast_coverage to surface network buyers.

Returns political bias intelligence rolled up across every analyzed podcast attributed to the publisher: coverage stats, political share, average lean (on a -3..+3 ordinal scale), lean diversity, the bias-bucket and regional distributions, and the most recent evaluation timestamp. Score-based metrics are omitted when the publisher has no political podcasts.

Returns a paginated list of the publisher's analyzed podcasts with their latest bias analysis attached. Supports filtering by bias bucket, political_context, and a toggle for excluding NOT_POLITICAL podcasts, plus sort by lean_score, evaluated_at, or name.

Returns a paginated list of podcasts attributed to a publisher, ordered by popularity. Identify the publisher by slug (e.g., 'goalhanger', 'iheartpodcasts', 'bbc-radio-4') or ID.

Returns a publisher-level rollup of IAB Tech Lab Brand Safety & Suitability Framework (formerly GARM) verdicts across the publisher's catalog: tier composition (SAFE / LIMITED / SENSITIVE / UNSAFE), confidence distribution, per-category exposure across all 12 GARM dimensions, and the top concerns surfaced from the category rollup. The coverage block (analyzed_coverage as a 0..1 share + a LOW/MEDIUM/HIGH quality enum) tells callers how representative the rollup is — analyses are still being backfilled across the long tail of the catalog. Identify the publisher by slug (e.g., 'iheartpodcasts', 'bbc-radio-4', 'bloomberg') or ID.

Returns a paginated list of the publisher's analyzed podcasts decorated with their latest IAB/GARM tier, confidence, evaluated-at timestamp, and any non-NONE category exposures (flagged categories). Filter by tier(s), by a specific GARM category (optionally constrained to a minimum prevalence and a particular treatment), and choose how to sort (most-risky first by default). Per-category reasoning and evidence excerpts are intentionally omitted — fetch GET /v1/podcasts/{id}/suitability for full per-category detail.

Returns chart entries from the live ranking snapshot. The most common call needs no parameters — it returns the first page (default 25, max 100 per request) of the US Apple Top Podcasts overall chart, ordered by rank ascending. Charts run to rank 200; paginate with `cursor` to fetch the rest. Narrow the result with `country`, `category_slug`, `source`, or `podcast_id`. When `podcast_id` is set, the response is the podcast's current chart appearances across the matching slots.

Returns every category currently represented in the rankings dataset, optionally restricted to a single source. For Apple sub-categories the response includes `parent_slug` so clients can render the category hierarchy.

Returns every country currently represented in the rankings dataset, optionally restricted to a single source. Each entry carries the human-readable country name (when known) and a count of distinct chart slots.

Returns historical chart snapshots for a chart slot, ordered most-recent first. Set `since` / `until` to bound the time range; set `podcast_id` to filter to one podcast within the slot.

Returns the chart entries whose rank changed between the live snapshot and the comparison snapshot `window_days` ago. Use the `change` filter to focus on debuts (`new`), departures (`exit`), or directional moves (`up` / `down`). Stable rows are excluded.

Returns each (source, chart_type) pair available on this API together with row counts and freshness for the live snapshot.

Searches the podcast catalog by show name — the canonical podcast search. Functionally equivalent to `GET /v1/podcasts?q=…`: the same forgiving, typo-tolerant ranked search, the same filters (topic, language, suitability tier, popularity, format), and the same `match_quality` signal on each result. To search *inside* episode dialogue, use `/v1/podcasts/episodes/search` instead.

Returns AI-identified segments across podcast episodes. Segments represent structural sections like topic discussions, interviews, ads, etc. At least one of `episode_id`, `podcast_id`, or `type` is required — this endpoint does not return a global feed.

Returns a single segment by its unique identifier.

Returns the diarized transcript for a specific segment.

For one of the 12 GARM brand-safety categories, returns a paginated ranking of podcast publishers by exposure across their catalog. The killer view for regulated brands: an alcohol advertiser pivots on illegal_drugs_alcohol_tobacco and immediately sees which publishers carry the highest catalog-level exposure (and at what prevalence + treatment); a family brand pivots on adult_sexual or hate_speech_aggression to build an exclusion list. min_prevalence + treatment narrow what counts as 'exposed'. Each row includes prevalence + treatment breakdowns and up to three example podcasts in the publisher's catalog that exhibit the highest exposure.

Returns a paginated, ranked list of podcast publishers by IAB/GARM brand-suitability composition. Pick a metric (safest, riskiest, most_placeable, most_analyzed) to choose how the ranking is constructed. min_analyzed_podcasts guards against tiny catalogs dominating share-based metrics. The ranking reflects each publisher's current catalog composition; paginate the audit history per show via GET /v1/podcasts/{id}/suitability?include=history when you need point-in-time analysis. Each row carries the full tier_breakdown (counts + shares) plus the metric_value the row was ranked by.

Returns the top-level topics covered across all podcasts, sorted by the number of podcasts covering each topic.

Returns a single podcast by slug (e.g., 'all-in') or ID. Slugs are human-readable identifiers included in every podcast response.

Returns advertising intelligence for a specific podcast, including aggregate stats, read type breakdown, and top sponsors. Identify the podcast by slug (e.g., 'all-in') or ID.

Returns per-sponsor ad activity on a single podcast (ads, distinct episodes, most recent placement), ordered by ad count descending. Pass company_id to scope the list to every sponsor linked to one company — the direct lookup for a multi-brand advertiser's footprint on one show, replacing a paginated scan of each sponsor's full podcast list. Entries agree with the ad_count values from the sponsor podcasts endpoint for the same sponsor and podcast. Network promos are excluded.

Returns the most recent automated political bias analysis for a podcast, including the agent's reasoning, transcript evidence, web research evidence, and the sample episodes that informed the rating. Returns 404 when the podcast is not found or when it has not yet been analyzed.

Returns a paginated list of episodes for a specific podcast, identified by slug (e.g., 'all-in') or ID.

Returns every third-party platform on which the podcast has a known presence — podcast directories (Apple Podcasts, Spotify, Castbox, …), social profiles (X, Instagram, TikTok, …), video channels (YouTube), and the publisher's own website. Each entry includes the platform-native identifier, a resolved web URL, and a list of optional attributes (audience size, profile metadata, account status). The shape is uniform across platforms; new attributes may be added over time without breaking existing clients.

Returns the full format breakdown for a podcast: how often episodes feature guests, detected production formats (interview, panel, call_in, solo_narrated), advertiser and video presence, episode length distribution, publishing cadence, the publish-day histogram, and the sample sizes behind each attribute. The compact form of this data is embedded as the `format` field on podcast responses; use this endpoint for the exact rates and distributions. Returns 404 when the podcast is not found or its format profile has not been computed yet.

Returns the paginated set of identified guests who have appeared on the podcast, grouped by Person. Each row carries the Person identity, the per-podcast appearance count, first/last appearance dates, and dominant listing role.

Returns the show's guest-expertise profile over every guest and panelist appearance analyzed for expertise, all time: how many there were, the share whose standing others conferred, who spoke within their field, and who came mainly to promote something, the guests' seniority, and their most common occupations and fields of research. Appearances whose analysis doubts the guest is the person linked are left out. The profile is rebuilt at most once a day. For each guest's own expertise, use GET /v1/people/{id}/expertise; for one episode's guests, GET /v1/podcasts/episodes/{id}/expertise.

Returns episodes where a specific entity appears within a podcast, ordered by most recent. Each result includes the episode, salience score, occurrence count, and speaker roles. Requires entity_id or company_id.

Returns every live chart appearance of the given podcast — across sources, countries, and categories. Identify the podcast by slug (e.g., 'the-daily') or ID.

Returns the historical rank entries for a podcast across one or more chart slots. Optional filters narrow the scope (single source, single country, single category, or a date range).

Returns a one-call aggregate of the podcast's current chart presence: the number of distinct chart slots, sources, countries, and categories it appears on, plus the single best (lowest-numbered) rank it currently holds and a per-source breakdown.

Returns user-generated ratings (1-5 stars plus optional review text) captured from third-party platforms. Today's source is Apple Podcasts, walked across the Anglophone storefronts (us, gb, ca, au, nz, ie). Newest ratings first; paginate with `cursor`. Filter by `platform_slug`, `locale`, `min_stars`, or a date window on `since`/`until`.

Returns the numeric aggregate of a podcast's ratings — one entry per (platform, locale) it has been rated on, a combined cross-source roll-up, and the latest LLM-generated narrative summary of recent review text when one has been generated.

Returns people who have guested on the podcast's related shows but never on this one, ranked by how related those venues are and how many distinct publishers among them chose the person — a booking pipeline, not a prediction. Recurring on any one show does not count, and a publisher's sibling feeds count once, so an outlet's own correspondents do not outrank guests several independent shows chose. Guests who appear everywhere (circuit regulars) are excluded, since recommending them says nothing about this show. Each row carries the person, a score, a band, how many related shows booked them, and with include=via which shows. For the show's existing roster use GET /v1/podcasts/{id}/guests; for shows like this one use GET /v1/podcasts/{id}/related.

Returns advertisers that run on the podcast's related shows but not on this one, ranked by how related those venues are, how much the sponsor buys there, and how recently — a prospecting list for a show selling its own inventory ('who buys shows like mine'), not a prediction. Each row carries the sponsor (with its linked company, the path to people to contact via GET /v1/companies/{id}/people), a score, a band, how many related shows run it, its ad count across them, the date of its most recent ad, and with include=via which shows. active_since keeps only sponsors still buying after a date. Related sets are precomputed (GET /v1/podcasts/{id}/related); a show whose set has not been computed yet gets an empty page. For who sponsors THIS show use GET /v1/podcasts/{id}/advertising; for a sponsor's full footprint use GET /v1/podcasts/advertising/sponsors/{id}/podcasts.

Returns the shows most related to a podcast, best first, each with a calibrated `score`, a coarse `band` (strong, moderate, weak) to branch on, and — with `include=basis` — the signals behind the pairing: content similarity of recent episodes, shared topics, shared guests (named), same publisher, and shared sponsors. Related sets are precomputed per show from its embedded transcripts, topic profile, guest roster, network, and advertisers, restricted to the show's language, and refreshed as new episodes land; the endpoint is a fast page read. Only shows above a relatedness floor are listed, machine-generated and farmed feeds are never listed, and a publisher's duplicate feeds of one show appear once (sets computed before that rule are collapsed on read, best-effort). An empty first page is 200 with a `coverage` note saying whether the set is not computed yet, nothing cleared the floor, or the filters removed everything — never 404. Use this for "shows like this show" — media planning around a known show, PR pitch lists, and agent traversal from one resolved slug to its neighbours. It is not a topic browser (use `GET /v1/podcasts?topic_id=…` for shows that cover a topic), not a guest lookup (`GET /v1/podcasts/guests/{id}/podcasts` lists where a guest has appeared), and not advertiser co-occurrence (`GET /v1/podcasts/advertising/co-occurrence`). Every result carries the related show's `slug`, which every other podcast endpoint accepts as `{id}`; person slugs in the basis feed the guest endpoints and topic slugs feed `topic_id`. Identify the podcast by slug (e.g., 'all-in'), internal ID, or numeric iTunes ID.

Returns the most recent brand suitability assessment for a podcast against the IAB Tech Lab Content Taxonomy 3.x Brand Safety & Suitability Framework (the industry-standard 12-category taxonomy formerly stewarded by GARM): overall tier, per-category prevalence and treatment, evidence excerpts from sampled episodes, and the methodology that produced the rating. Pass include=trend for a deterministically-derived comparison against the prior assessment, or include=history for the list of prior assessments. Returns 404 when the podcast is not found or has not yet been analyzed.

Returns the hierarchical topic taxonomy. Use parent_id to navigate the tree, or q to find topics by name.

Returns a single topic with breadcrumb ancestors and the top direct children by prominence. Children are capped — use /v1/topics?parent_id={id} to paginate beyond the cap.