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Données ouvertes

Bibliothèque

Jeux de données ouverts, entièrement documentés — interrogeables ici, et lisibles par n’importe quel LLM.

Les titres et les descriptions proviennent des sources de données, en anglais.

3 jeux de données

startup

  • AI startup funding rounds (agent-curated)

    AI startup funding rounds (weekly)

    Weekly structured digest of AI startup funding rounds announced in the trailing 7 days. Three queries against the keyless Google News RSS search interface (AI startup raises funding / AI startup seed round / artificial intelligence startup Series funding) are filtered to completed raises ("in talks", "seeks funds" and roundup listicles dropped), deduplicated on a canonical company key across reporting outlets (most informative report kept, n_reports counted), and parsed into structured fields: round type (pre-seed/seed/angel/series a-e/venture/growth/bridge, else undisclosed), amount FX-normalized to USD millions (EUR 1.16, GBP 1.34, CAD 0.73; original currency kept), valuation when the reporting discloses one (amounts inside a valuation phrase are routed to valuation, never to amount), investors (lead marked where stated), country + ISO alpha-3 (only when the collected material states a location — never guessed), announcement date, headline, publisher and a per-row verifiable source URL. Agent-verified enrichment: rounds the agent verified beyond the headline carry the verified country, investors, round type and canonical article URL, each with its own provenance URL. Rows are deal-size ranked (undisclosed amounts last). Columns: ISO week, fetch timestamp (day-granular, UTC midnight), company, round type, amount in USD millions, original currency, valuation in USD millions, investors, country, ISO alpha-3 country code, announcement date, headline, publisher, source URL, deal-size rank, report count. Primary key: (week, company). Cadence: weekly; each snapshot is the trailing-7-day announced-round universe, ranked biggest first. Nullability: amount_usd_m is null when only a valuation was disclosed; valuation_usd_m is null when none was disclosed; country/country_code/investors are null when not stated in the collected material; announced_date may be empty when the feed omits it. Caveats: amounts are as-reported (equity/growth/debt mixed); only facts from headlines are stored, no article text; commercial_use is unclear (underlying reporting belongs to the credited publishers). Sample use: order by deal_size_rank for the week's biggest AI rounds, or filter country_code = 'USA'.

    • startup
    • ai
    • technology
    • signals
    lignes
    32
    Qualité
    91
    Mis à jour
    25 sept. 2026
    À jour
    Licence
    Licence incertaine

  • AI Product Launch Signals (agent-curated)

    AI Product Launches — Weekly Tracker

    Weekly curated snapshot of AI products that actually launched: new models, agents, devtools and AI features that became generally available, went live in an API/app/store, or were open-sourced in the trailing 7-day window. Each row records the exact announcement URL, a deterministic category and pricing signal, and an evidence score that rewards independent corroboration and recency. Method: agent-curated — each weekly sweep searches public AI news digests and product-coverage pages for launches in the trailing 7-day window (inclusion: GA/live/open-sourced; excluded: announced-only, waitlists, previews without user access, future GA dates, planned launches, models still training). No keyless programmatic launch API exists for this domain (GDELT refused traffic from this environment on 2026-09-24; news sites prohibit scraping), so collection is manual and each snapshot is ingested through the hub store/publish path with provenance 'agent-curated' plus the run timestamp. Units: one row per launched AI product per week. Columns: ISO week, sweep timestamp, deterministic launch id (canonical company slug + product slug), product and canonical company name, company country (ISO alpha-3 + name, empty when the coverage does not state it), deterministic keyword category (model, agent, image-generation, video-generation, audio, robotics, devtools, productivity, marketing, ecommerce, security, legal, other), deterministic pricing signal (free, freemium, paid, enterprise, unknown), launch date, one-line agent-written summary (<=220 chars), exact announcement URL, count and comma-joined list of coverage URLs, launch_score = 100 * (1 + ln(1 + coverage_count)) * exp(-age_days / 7), and launch_rank (1 = strongest signal) by score desc, tie-broken by launch_date desc then launch_id asc. Primary key: (week, launch_id). Cadence: weekly. Nullability: company country fields are empty when not stated in coverage; everything else is always populated. Caveats: curated from public coverage, so unpublicized launches may be missing and launch dates reflect the first public launch report seen; category and pricing_signal are deterministic keyword rules on the summary, not editorial judgments; coverage is English-language press plus vendor announcements. Sample use: order by launch_rank for the week's strongest launch signals, or filter category = 'model'.

    • ai
    • technology
    • startup
    • news
    lignes
    28
    Qualité
    99
    Mis à jour
    25 sept. 2026
    À jour
    Licence
    Usage commercial OK

  • US Business-Formation Signals (derived)

    US business-formation signals (entrepreneurship pipeline gauges)

    Weekly US business-formation signals from Census Bureau Business Formation Statistics (FRED BUSAPPWNSAUS + HBUSAPPWNSAUS, 2006 ->): total and high-propensity business applications with 13-week momentum, year-on-year change, 30-week change volatility, 3-sigma anomaly flags, naive-drift forecasts, and the high-propensity share of applications (the quality mix of the startup pipeline). The entry-margin lens on the US business cycle — applications lead formations, and high-propensity applications lead employer births. Companion to us-labor-market-signals (established firms) and us-state-coincident-activity-signals (output). All rows normalized to country_code USA. Raw series: U.S. Census Bureau Business Formation Statistics via FRED.

    • business-formation
    • entrepreneurship
    • startup
    • ein
    lignes
    2 154
    Qualité
    100
    Mis à jour
    22 sept. 2026
    À jour
    Licence
    Usage commercial OK

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