Data Conference Databasea Query.Farm index
Companies

Explosion

Product category (jev): GenAI & LLMs 50% confident
Org type (jev): Software vendor 80% confident
Also listed as: Explosion (spaCy, Prodigy) · Explosion AI · Explosion.AI
Conferences sponsored1
Events sponsored2
Speaker slots377 distinct people
Conferences present at9sponsor or speaker
Years active2019–2026

Circuit mix

Where Explosion shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.

Presence by conference and year

Each cell is one conference in one year. Fill shows the company sponsored, shaded by its best tier that year; a dot means it had speakers there. Hover for details; click to open the event.

  • Title
  • Platinum
  • Gold
  • Silver
  • Bronze
  • Other / unlabeled tier
  • Had speakers
Conference2019202020212022202320242025202620272028
PyData
PyCon (national Python conferences)
Budapest Data+AI Forum
Py4AI - Python and AI International Conference
Compute!
DataHack Summit
EuroPython
MLOps World (Machine Learning in Production)
QCon

Activity by year

Three measures on one year axis; each panel has its own scale. 2027, 2028 is still mostly ahead, so its bars are faded and incomplete.

Conferences present at

Distinct conferences each year, split by whether the company sponsored or only had speakers there.

  • Sponsored
  • Speakers only

Distinct speakers

People from this company on a program that year, each counted once.

Sponsorships by tier

Sponsorship rows per year (one per event and listing), stacked by normalized tier.

  • Gold

Where they've grown or pulled back

DownNothing recorded in 2026; sponsored 1 conference in 2023.

Counted per conference. 2026 is the latest year whose conferences have mostly happened. Tiers use the best tier each year; swatches show the path, oldest first. A conference counts as pulled out only when a later event published a complete sponsor list, since most events don’t say whether their list is complete.

Once or on and off 1

No clear direction, or a gap we can’t confirm because later sponsor lists are incomplete.

Lookalikes

Companies with the most similar conference footprint: they sponsor and speak at the same conferences. Bars are cosine similarity, from 0 (nothing shared) to 1 (identical).

  1. KLM Royal Dutch Airlines0.83
  2. Mor Consulting0.83
  3. Warsaw University of Technology0.81
  4. ASML0.80
  5. Picnic0.79
  6. Vonage0.76
  7. Recursion0.75
  8. Ordina Pythoneers0.75

8 Cluster: PyData · posit::conf circuit →

Often sponsors alongside

Companies that sponsored the same events, by number of shared events (out of 2 this company sponsored).

CompanyShared eventsShare
Coiled2100%
Hopsworks2100%
HumanSignal2100%
Taipy2100%
Adyen150%
Babbel150%
BlockScience150%
Bloomberg150%
Booking.com150%
Capgemini150%
Covalent150%
Cubist Systematic Strategies150%
CVS Health150%
Datapane150%
Dexter Energy150%

Neighborhood: companies with nearby conference footprints

Explosion (ringed) and the 30 companies closest to it on the company map. Close together means they sponsor and speak at many of the same conferences. Distances are only meaningful locally; the axes have no meaning. Dot size: conferences present at. Color: cluster.

ExplosionFlatiron HealthPicnicThe Alan Turing InstituteKLM Royal Dutch AirlinesGramenerThe Institute for Ethical AI & Machine LearningYelpWarsaw University of TechnologyRasaTaipyEpisourceKrakenCompassLightbendEdgeDBPhilip Morris InternationalMercariHaystackKiwi.comBack MarketBluevineNexmoCartaDropboxYDataKlarna
ExplosionFlatiron HealthPicnicThe Alan Turing InstituteKLM Royal Dutch AirlinesGramenerYelpRasaTaipyEpisourceKrakenCompassLightbendEdgeDBMercariHaystackOctopus EnergyKiwi.comBack MarketBluevineNexmoDropboxYData

Sponsorships 2

EventDatePlaceTier as listedNormalized tier
PyData NYC 2023Nov 1–3, 2023New York, United StatesGold Gold
PyData Amsterdam 2023Sep 14–16, 2023Amsterdam, NetherlandsGold Sponsors Gold

Speakers 37

SpeakerEventRoleTalkLinks
Ines MontaniCompute! Paris 2026keynoteA New Era of Developer Tools—
Ines MontaniPyData & PyCon Yerevan 2026keynoteBuild-to-own AI: Agentic Development for Humans—
Ines MontaniPy4AI 2026speaker——
Matthew HonnibalPy4AI 2026speaker——
Ines MontaniPyData London 2026talkVibe NLP for Applied NLP—
Ines MontaniPyCon DE & PyData 2026talkVibe NLP for Applied NLPSlides
Ines MontaniPyCon DE & PyData 2026panelOpen Source as a Business — Models, Paths, and Practice—
Ines MontaniPyCon DE & PyData 2026panelPanel: Evolution, Revolution, or Illusion? The Future of Python and Coding in the Age of AI—
Ines MontaniPyCon Ireland 2025keynoteKeynote: Ines Montani—
Ines MontaniPyCon Ireland 2025panelPanel: AI and its impact—
Ines MontaniPyData London 2025talkFeminist AI Lounge—
Ines MontaniPyData London 2025talkConquering PDFs: document understanding beyond plain text—
Ines MontaniPyCon DE & PyData 2025talkConquering PDFs: document understanding beyond plain text—
Ines MontaniPyCon DE & PyData 2025panelAI in Reality Fireside Chat: Enterprise AI & Open‑Source Innovation—
Ines MontaniPyConFR 2024keynoteReality is not an end-to-end prediction problem: Applied NLP in the age of Generative AI—
Ines MontaniPyData Amsterdam 2024keynoteKeynote - Applied NLP in the age of Generative AI—
Ines MontaniDataHack Summit 2024keynoteReality is Not an End-to-End Prediction Problem: Applied NLP in the Age of Generative AI—
Ines MontaniPyData London 2024talkTaking LLMs out of the black box: A practical guide to human-in-the-loop distillation—
Ines MontaniBudapest Data+ML Forum 2024speakerData+ML Community Meetup (Free)—
Ines MontaniBudapest Data+ML Forum 2024speakerTaking LLMs out of the black box: A practical guide to human-in-the-loop distillation—
Ines MontaniPyCon DE & PyData Berlin 2024talkThe AI Revolution Will Not Be Monopolized: How open-source beats economies of scale, even for LLMs—
Ines MontaniQCon London 2024speakerThe AI Revolution Will Not Be Monopolized: How Open-Source Beats Economies of Scale, Even for LLMs—
Vincent D. WarmerdamPyData Eindhoven 2023talkActive Teaching, Human LearningVideo
Ines MontaniPyData NYC 2023tutorialHalf hour of labeling power: Can we beat GPT?Video
Ryan WesslenPyData NYC 2023tutorialHalf hour of labeling power: Can we beat GPT?Video
Matthew Honnibal4th Annual MLOps World Conference & Expo 2023speakerHow many Labelled Examples Do You Need for a BERT-sized Model to Beat GPT4 on Predictive Tasks?—
Ines MontaniPyData Amsterdam 2023talkThere are no bad labels, only happy accidents—
Laura SummersPyData Amsterdam 2023talkOk, doomer—
Vincent WarmerdamPyData Amsterdam 2023talkThere are no bad labels, only happy accidents—
Vincent WarmerdamPyData Amsterdam 2023keynoteKeynote "Natural Intelligence is All You Need [tm]"—
Ines MontaniEuroPython 2023keynoteLarge Language Models: From Prototype to ProductionVideo
Ines MontaniPyData London 2023keynoteKeynote: Large Language Models: From Prototype to Production—
Ines MontaniPyCon DE & PyData Berlin 2023talkIncorporating GPT-3 into practical NLP workflows—
Victoria SlocumPyCon DE & PyData Berlin 2023talkYou are what you read: Building a personal internet front-page with spaCy and Prodigy—
Kádár ÁkosBudapest ML Forum 2022speakerSpanCat: Named Entity Recognition in spaCy and beyond—
Ines MontaniPyCon Colombia 2020keynote——
Ines MontaniPyCon India 2019keynote——