Companies
inovex
Product category: Consulting & services 99% confident
Org type: Consultancy 100% confident
Also listed as 3 other names
Inovex · Inovex GmbH · inovex GmbH
Conferences sponsored7
Events sponsored16
Speaker slots7542 distinct people
Conferences present at9sponsor or speaker
Years active2019–2026
Talks, past 12 months15#97 on the communication index · many voices · +67% this yearCircuit mix
Where inovex shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.
- Python & R data science33%11 events
- Enterprise, analyst & AI expos24%6 events
- AI engineering & MLOps17%6 events
- Vendor flagships & roadshows9%2 events
- Open-source data infrastructure7%2 events
- Microsoft data platform7%2 events
- Modern data stack & practitioner4%1 event
The year around now
Conferences where inovex sponsored or had speakers in the past 12 months, and the announced events it is already listed for. One row per conference, January to December; hover a mark for the event and the company's role.
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
Activity by year
Three measures on one year axis; each panel has its own scale.
Conferences present at
Distinct conferences each year, split by whether the company sponsored or only had speakers there.
- Sponsored
- Speakers only
4
2
1
4
4
4
4
7
Distinct speakers
People from this company on a program that year, each counted once.
8
2
7
10
9
10
14
Sponsorships by tier
Sponsorship rows per year (one per event and listing), stacked by normalized tier.
- Silver
- Bronze
- Other / unlabeled
1
2
1
2
2
3
5
Where they've grown or pulled back
UpSponsored 5 conferences in 2026, up from 2 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.
New 2
First sponsored in 2025 or later.
- Databricks Data + AI World Tourfirst sponsored 2025, Silver
- SQL Konferenzfirst sponsored 2026, Silver
Moved down 1
Best tier fell between the first and latest year with a ranked tier.
- Minds Mastering Machines (M3)Silver 2019 → Bronze 2026
Steady 2
Sponsored in most years of its span at the same tier.
Once or on and off 2
No clear direction, or a gap we can’t confirm because later sponsor lists are incomplete.
- Airflow Summitonce, 2020, Community tier
- Berlin Buzzwordsonce, 2020, unranked tier
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).
- Alexander Thamm GmbH0.87
- scieneers0.82
- OLX Group0.75
- GetYourGuide0.74
- Aleph Alpha0.73
- codecentric0.72
- Heidelberger Druckmaschinen0.72
- Kern AI0.71
4 Cluster: PyData · PyCon circuit →
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 16 this company sponsored).
| Company | Shared events | Share |
|---|---|---|
| EuroPython Society | 4 | 25% |
| INNOQ | 4 | 25% |
| PyData Berlin | 4 | 25% |
| PyLadies | 4 | 25% |
| QuantCo | 4 | 25% |
| Rosen | 4 | 25% |
| Accenture | 3 | 19% |
| Alexander Thamm GmbH | 3 | 19% |
| Blue Yonder | 3 | 19% |
| energy & meteo systems GmbH | 3 | 19% |
| 3 | 19% | |
| Gurobi | 3 | 19% |
| HMS Analytical Software | 3 | 19% |
| INFOMOTION | 3 | 19% |
| NumFOCUS | 3 | 19% |
Neighborhood: companies with nearby conference footprints
inovex (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.
Sponsorships 16
| Event | Date | Place | Tier as listed | Normalized tier |
|---|---|---|---|---|
| Data + AI World Tour Munich 2026 | Nov 4, 2026 | Munich, Germany | Enthusiast | Silver |
| data2day 2026 | Oct 6–8, 2026 | Cologne, Germany | Silber-Sponsoren | Silver |
| Minds Mastering Machines 2026 | Apr 21–23, 2026 | Karlsruhe, Germany | Bronze-Sponsor | Bronze |
| PyCon DE & PyData 2026 | Apr 14–16, 2026 | Darmstadt, Germany | Silver | Silver |
| SQL Konferenz 2026 | Mar 2–4, 2026 | Hanau, Germany | Silver Partner | Silver |
| Data + AI World Tour Munich 2025 | Nov 4, 2025 | Munich, Germany | Enthusiast | Silver |
| data2day 2025 | Nov 3–5, 2025 | Karlsruhe, Germany | Silber-Sponsor | Silver |
| PyCon DE & PyData 2025 | Apr 23–25, 2025 | Darmstadt, Germany | Silver | Silver |
| data2day 2024 | Sep 17–19, 2024 | Heidelberg, Germany | Silber-Sponsoren | Silver |
| PyCon DE & PyData Berlin 2024 | Apr 22–24, 2024 | Berlin, Germany | Silver | Silver |
| data2day 2023 | Oct 11–13, 2023 | Karlsruhe, Germany | Silber-Sponsoren | Silver |
| PyCon DE & PyData Berlin 2023 | Apr 17–19, 2023 | Berlin, Germany | Diversity & Financial Aid Sponsors | Other |
| data2day 2022 | Sep 19–21, 2022 | Karlsruhe, Germany | Silber-Sponsoren | Silver |
| Airflow Summit 2020 | Jul 6–17, 2020 | — | Community | Community |
| Berlin Buzzwords 2020 (vbuzz) | Jun 7–12, 2020 | — | Contributor | Other |
| Minds Mastering Machines 2019 | May 14–16, 2019 | Mannheim, Germany | Silber-Sponsoren | Silver |
Speakers 75
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Denise Hartmann | data2day 2026 | talk | Wenn der Weg das Ziel ist: Agenten-Loops systematisch tracen und evaluieren | — |
| Jan Trienes | data2day 2026 | talk | Deploy with Confidence: Generative KI systematisch evaluieren | — |
| Matthias Richter | data2day 2026 | talk | Deploy with Confidence: Generative KI systematisch evaluieren | — |
| Max Vieweg | data2day 2026 | talk | Wenn der Weg das Ziel ist: Agenten-Loops systematisch tracen und evaluieren | — |
| Florian Wilhelm | EuroPython 2026 | talk | The Problem with None: Sentinel Values and the Semantics of Absence | Video |
| Andre Ebert | PASS Summit Europe (Frankfurt) 2026 | speaker | Data and AI Governance in Microsoft Fabric under the EU AI Act | — |
| Alina Döring | Minds Mastering Machines 2026 | talk | Von Deep Learning zu vertrauenswürdigen Entscheidungen: Erklärbare Tumorerkennung im OP | — |
| Phuong Mai Mai | Minds Mastering Machines 2026 | talk | The AI Security Maze – KI-Sicherheit spielerisch verstehen und steuern | — |
| Simon Dreher | Minds Mastering Machines 2026 | talk | The AI Security Maze – KI-Sicherheit spielerisch verstehen und steuern | — |
| Stefanie Marx | Minds Mastering Machines 2026 | talk | Von Deep Learning zu vertrauenswürdigen Entscheidungen: Erklärbare Tumorerkennung im OP | — |
| Florian Wilhelm | PyCon DE & PyData 2026 | talk | Sentinel Values in Python: Semantics, Double Dispatch, and the Limits of Typing | — |
| Jonas Böer | PyCon DE & PyData 2026 | talk | Rediscovering single-node processing: When does it make sense to move from Spark to Polars? | — |
| Joshua Finger | PyCon DE & PyData 2026 | talk | Fight your garbage data: implementation of a pythonic data quality monitoring framework in PySpark | — |
| Niklas | PyCon DE & PyData 2026 | talk | Simulating the World using SimPy: A practical Example | — |
| Stefan Kraus | PyCon DE & PyData 2026 | talk | Ty mypy: The New Generation of Python Type Checking | — |
| Christoph Eßlinger | data2day 2025 | talk | Data Mesh Productivity Plateau: Erfahrungen & Best Practices mit Snowflake @ REWE digital | — |
| Constantin Lehmann | data2day 2025 | talk | Roboterdaten in der Google Cloud: Ein Praxisbeispiel mit Dataproc und BigQuery | — |
| Alina Döring | Minds Mastering Machines 2025 | talk | KI im OP: Nutzerzentriert, vertrauenswürdige KI-Technologie entwickeln | — |
| Clemens Hübner | Minds Mastering Machines 2025 | talk | Hands-on LLM Security: Schwachstellen und Gegenmaßnahmen | — |
| Florian Teutsch | Minds Mastering Machines 2025 | talk | Hands-on LLM Security: Schwachstellen und Gegenmaßnahmen | — |
| Robin Senge | Minds Mastering Machines 2025 | talk | KI im OP: Nutzerzentriert, vertrauenswürdige KI-Technologie entwickeln | — |
| Dr. Marisa Mohr | PyCon DE & PyData 2025 | workshop | Mini-Pythonistas: Coding, Experimenting, and Exploring with Zümi! | — |
| Florian Teutsch | PyCon DE & PyData 2025 | talk | Hands-On LLM Security: Attacks and Countermeasures You Need to Know! | — |
| Florian Wilhelm | PyCon DE & PyData 2025 | talk | Why Exceptions Are Just Sophisticated Gotos - and How to Move Beyond | — |
| Jonas Böer | PyCon DE & PyData 2025 | talk | Challenges and Lessons Learned While Building a Real-Time Lakehouse using Apache Iceberg and Kafka | — |
| Julian Beck | PyCon DE & PyData 2025 | talk | From Idea to Integration: An Intro to the Model Context Protocol (MCP) | — |
| Alina Döring | data2day 2024 | talk | Der Mensch im Fokus: nutzerzentriert, vertrauenswürdige KI-Technologie entwickeln | — |
| Florian Gräbe | data2day 2024 | talk | Praxisnahe Erfahrungen aus dem Data-Quality-Dschungel | — |
| Florian Gräbe | data2day 2024 | talk | DSGVO-Challenges und Best Practices aus der Data-Engineering-Perspektive | — |
| Marcel Spitzer | data2day 2024 | talk | Praxisnahe Erfahrungen aus dem Data-Quality-Dschungel | — |
| Marcel Spitzer | data2day 2024 | talk | DSGVO-Challenges und Best Practices aus der Data-Engineering-Perspektive | — |
| Anna-Lena Popkes | EuroPython 2024 | talk | When and how to start coding with kids | Video |
| Clemens Hübner | Minds Mastering Machines 2024 | talk | Threat Modeling für KI-Anwendungen | — |
| Phuong Mai Mai | Minds Mastering Machines 2024 | talk | Threat Modeling für KI-Anwendungen | — |
| Anna-Lena Popkes | PyCon DE & PyData Berlin 2024 | talk | When and how to start coding with kids | — |
| Clemens Hübner | PyCon DE & PyData Berlin 2024 | talk | Better safe than sorry: Threat Modeling for Python Developers | — |
| Florian Wilhelm | PyCon DE & PyData Berlin 2024 | talk | Streamlining Python Development: A Guide to a Modern Project Setup | — |
| Florian Wilhelm | PyCon DE & PyData Berlin 2024 | panel | Community Conferences under the Hood. Perspectives and Best Practices in Volunteer Organization | — |
| Lea Petters | PyCon DE & PyData Berlin 2024 | talk | Best of both worlds - How we built an AI-aided content creation tool for language learning | — |
| Marie-Kristin Wirsching | PyCon DE & PyData Berlin 2024 | talk | Next Stop: Insights! How Streamlit and Snowflake Power Up Data Stories | — |
| Anna Weißhaar | data2day 2023 | talk | Fluid Scrum Teams in Data Products | — |
| Clemens Hübner | data2day 2023 | talk | Sicherheit, aber mit System: Threat Modelling für Datenplattformen | — |
| Lea Petters | data2day 2023 | talk | Daten & KI-Strategie: Warum man einen Bauplan braucht, um KI-Lösungen zu bauen, die dem Hype standhalten | — |
| Sebastian Löfflath | data2day 2023 | talk | Von Chaos zu Erfolg: Datenqualität beherrschen | — |
| Tobias Maasland | data2day 2023 | talk | Fluid Scrum Teams in Data Products | — |
| Anna-Lena Popkes | EuroPython 2023 | talk | An unbiased evaluation of environment management and packaging tools | Video |
| Florian Wilhelm | EuroPython 2023 | talk | From Algorithms to Agendas: A Beginner's Guide to Integer Programming | Video |
| Lea Petters | Minds Mastering Machines 2023 | talk | What Could Possibly Go Wrong: ein (unvollständiger) Leitfaden zum Umgang mit Verzerrungen in Datenprodukten | — |
| Raphael Skuza | Minds Mastering Machines 2023 | talk | Data Orchestration: Worauf es in Zukunft ankommt | — |
| Sebastian Blank | Minds Mastering Machines 2023 | talk | Conversational AI – Dead or Alive? | — |
| Anna-Lena Popkes | PyCon DE & PyData Berlin 2023 | talk | An unbiased evaluation of environment management and packaging tools | — |
| Florian Wilhelm | PyCon DE & PyData Berlin 2023 | talk | WALD: A Modern & Sustainable Analytics Stack | Slides |
| Lea Petters | PyCon DE & PyData Berlin 2023 | talk | What could possibly go wrong? - An incomplete guide on how to prevent, detect & mitigate biases in data products | Slides |
| Tim Bossenmaier | PyCon DE & PyData Berlin 2023 | talk | Apache StreamPipes for Pythonistas: IIoT data handling made easy! | — |
| Dominik Benz | data2day 2022 | talk | Data (Mesh) is coming home: Ein Reisebericht mit Software- und Data-Architect | — |
| Pascal Fecht | data2day 2022 | talk | Große NLP-Modelle: Transfer Learning vs. Few-Shot Learning | — |
| René Lengwinat | data2day 2022 | talk | Data (Mesh) is coming home: Ein Reisebericht mit Software- und Data-Architect | — |
| Rostislaw Krassow | data2day 2022 | talk | Die Balance zwischen Self-Service und zentraler Governance auf einer Datenplattform finden | — |
| Stefanie Stoppel | data2day 2022 | talk | Der Mythos der Neutralität: Wie KI die soziale Kluft vergrößert | — |
| Marcel Kurovski | EuroPython 2022 | talk | Build your own Playlist Recommender System with Python using your GDPR Data | Video |
| Marcel Kurovski | Minds Mastering Machines 2022 | talk | Your Rediscover Past: Spotify-Personalisierung selbstgemacht | — |
| Florian Wilhelm | PyCon DE & PyData Berlin 2022 | talk | Honey, I shrunk the target variable! Common pitfalls when transforming the target variable and how to exploit transformations. | — |
| Stefanie Stoppel | PyCon DE & PyData Berlin 2022 | talk | The Myth of Neutrality: How AI is widening social divides | — |
| Anna-Lena Popkes | EuroPython 2021 Online | talk | Finding Magic in Python | Slides · Video |
| Stefanie Stoppel | EuroPython 2021 Online | talk | The Myth of Neutrality: How AI is widening social divides | Slides · Video |
| Kevin Exel | data2day 2019 | talk | Mit Metadatenmanagement hin zu reproduzierbaren und flexiblen Data-Science-Workflows auf Kubernetes | — |
| Nico Kreiling | data2day 2019 | talk | Entwicklung einer in-house AI-Plattform | — |
| Sebastian Jäger | data2day 2019 | talk | Mit Metadatenmanagement hin zu reproduzierbaren und flexiblen Data-Science-Workflows auf Kubernetes | — |
| Florian Wilhelm | PyCon DE & PyData Berlin 2019 | talk | Are you sure about that?! Uncertainty Quantification in AI | — |
| Hans-Peter Zorn | Berlin Buzzwords 2019 | talk | Querying Elasticsearch with Deep Learning to Answer Natural Language Questions | Slides · Video |
| Sebastian Blank | Berlin Buzzwords 2019 | talk | Querying Elasticsearch with Deep Learning to Answer Natural Language Questions | Slides · Video |
| Marcel Kurovski | Minds Mastering Machines 2019 | talk | Vom Prototyping zur Produktion – Portabilität für Deep-Learning-Modelle | — |
| Marcel Spitzer | Minds Mastering Machines 2019 | talk | Interpretierbarkeit von ML-Modellen | — |
| Nico Kreiling | Minds Mastering Machines 2019 | talk | Workflow mit Jupyter Lab | — |
| Nico Kreiling | Minds Mastering Machines 2019 | talk | Machine Learning Model Management – Ein Framework-Vergleich | — |