DAGWorks Inc
Also listed as 2 other names
DAGWorks · DAGWorks Inc.
Circuit mix
Where DAGWorks Inc shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.
- Modern data stack & practitioner33%2 events
- AI engineering & MLOps33%2 events
- Python & R data science33%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 |
|---|---|---|---|---|---|---|---|---|
| MLOps World (Machine Learning in Production) | ||||||||
| PyCon (national Python conferences) | ||||||||
| Budapest Data+AI Forum | ||||||||
| Data Council |
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
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.
- Other / unlabeled
Where they've grown or pulled back
DownNothing recorded in 2026; sponsored 1 conference in 2024.
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.
- PyCon (national Python conferences)once, 2024, 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).
- YData0.80
- Observable0.78
- Elementl0.77
- Ponder0.76
- Generali0.74
- Traveloka0.73
- Linode0.71
- DeepLearning.AI0.70
6 Cluster: PyCon · EuroPython circuit →
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 1 this company sponsored).
| Company | Shared events | Share |
|---|---|---|
| ActiveState | 1 | 100% |
| Algorand Foundation | 1 | 100% |
| Amazon Web Services | 1 | 100% |
| American Express | 1 | 100% |
| Anaconda | 1 | 100% |
| Ansys | 1 | 100% |
| Anvil | 1 | 100% |
| ASML | 1 | 100% |
| Astral | 1 | 100% |
| Awesomic | 1 | 100% |
| BeeWare Project | 1 | 100% |
| BeProud | 1 | 100% |
| Black Python Devs | 1 | 100% |
| Bloomberg | 1 | 100% |
| Bright Data | 1 | 100% |
Neighborhood: companies with nearby conference footprints
DAGWorks Inc (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 1
| Event | Date | Place | Tier as listed | Normalized tier |
|---|---|---|---|---|
| PyCon US 2024 | May 15–23, 2024 | Pittsburgh, United States | Associate | Other |
Speakers 4
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Stefan Krawczyk | 5th Annual MLOps World and Generative AI World Conference 2024 | workshop | Building Reliable AI: A Workshop to Build a Production Ready Multi-Modal Conversational Agent | — |
| Elijah Ben Izzy | Data Council Austin 2024 | talk | Move Fast and Don't Break Things -- how to build a data platform that scales with your organization | — |
| Stefan Krawczyk | 4th Annual MLOps World Conference & Expo 2023 | speaker | Getting Higher Roi on Ml Ops Initiatives: Five Lessons Learned While Building out The Ml Ops Platform for 100+ Data Scientists | — |
| Stefan Krawczyk | Budapest Data Forum + Budapest ML Forum 2023 | speaker | Feature engineering in Python with Hamilton | — |