Qwak
Circuit mix
Where Qwak shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.
- Vendor flagships & roadshows43%3 events
- AI engineering & MLOps43%3 events
- Python & R data science14%1 event
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
| Conference | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 | 2027 | 2028 |
|---|---|---|---|---|---|---|---|---|---|---|
| Snowflake Summit | ||||||||||
| MLOps World (Machine Learning in Production) | ||||||||||
| ODSC (Open Data Science Conference) | ||||||||||
| Data + AI Summit | ||||||||||
| PyData |
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
- Silver
- Bronze
Where they've grown or pulled back
DownNothing recorded in 2026; sponsored 2 conferences 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.
Pulled out 1
Not sponsored since 2024 or earlier, though a later event published a complete sponsor list without them.
- Snowflake Summitlast sponsored 2024; the conference ran again in 2025–26
Once or on and off 4
No clear direction, or a gap we can’t confirm because later sponsor lists are incomplete.
- Data + AI Summitonce, 2022, Silver
- MLOps World (Machine Learning in Production)once, 2022, Gold
- ODSC (Open Data Science Conference)once, 2023, Gold
- PyDataonce, 2022, Gold
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).
0 Cluster: ODSC · MLOps World circuit →
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 7 this company sponsored).
Neighborhood: companies with nearby conference footprints
Qwak (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 7
| Event | Date | Place | Tier as listed | Normalized tier |
|---|---|---|---|---|
| Snowflake Data Cloud Summit 2024 | Jun 3–6, 2024 | San Francisco, United States | Snow Row | Bronze |
| ODSC West 2023 | Oct 31, 2023 – Nov 2, 2023 | Burlingame, United States | Gold Partners | Gold |
| Snowflake Summit 2023 | Jun 26–29, 2023 | Las Vegas, United States | Snow Row Partner | Bronze |
| ODSC East 2023 | May 9–11, 2023 | Boston, United States | Gold Partners | Gold |
| PyData NYC 2022 | Nov 9–11, 2022 | New York, United States | Gold | Gold |
| Data + AI Summit 2022 | Jun 27–30, 2022 | San Francisco, United States | Silver | Silver |
| 3rd Annual MLOps World 2022 | Jun 9–10, 2022 | Toronto, Canada | Gold Sponsors | Gold |
Speakers 3
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Pavel Klushin | 3rd Annual MLOps World 2022 | workshop | Deploy High Scale ML Models Without the Hustle | — |
| Yuval Fernbach | 3rd Annual MLOps World 2022 | speaker | The Critical Things you HAVE to Build to Transform Your Company to be ML Driven | — |
| Yuval Fernbach | 3rd Annual MLOps World 2022 | speaker | Crossing the Production ML Chasm: The 5 Biggest Challenges in Model Productionization and Practical Tools to Address them | — |