Cherre
Circuit mix
Where Cherre 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%1 event
- Alt data & financial information33%1 event
- Postgres & open-source databases17%1 event
- AI engineering & MLOps17%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 |
|---|---|---|---|---|---|---|---|---|
| Data Council | ||||||||
| BattleFin Discovery Day | ||||||||
| MLCon (ML Conference) | ||||||||
| Nordic PGDay |
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.
- Silver
- Other / unlabeled
Where they've grown or pulled back
DownNothing recorded in 2026; sponsored 2 conferences in 2019.
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.
- BattleFin Discovery Daylast sponsored 2019; the conference ran again in 2020–26
Once or on and off 1
No clear direction, or a gap we can’t confirm because later sponsor lists are incomplete.
- Data Councilonce, 2019, 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).
- Crux0.84
- Komodo Health0.77
- Seek AI0.71
- Jefferies0.68
- Flywheel0.66
- Plume0.63
- Envestnet0.63
- TransUnion0.63
1 Cluster: Neudata Data Summits · BattleFin Discovery Day circuit →
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 2 this company sponsored).
| Company | Shared events | Share |
|---|---|---|
| Crux | 2 | 100% |
| Reonomy | 2 | 100% |
| 1010data | 1 | 50% |
| 7Park Data | 1 | 50% |
| AggData | 1 | 50% |
| AlphaSense | 1 | 50% |
| Amenity Analytics | 1 | 50% |
| Ascend.io | 1 | 50% |
| Berkower | 1 | 50% |
| BigOne Lab | 1 | 50% |
| Blackstone | 1 | 50% |
| Brandloyalties, Inc | 1 | 50% |
| Calcbench | 1 | 50% |
| Canalyst | 1 | 50% |
| Capella Space | 1 | 50% |
Neighborhood: companies with nearby conference footprints
Cherre (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.
- Neudata Data Summits · BattleFin Discovery Day circuit 24
- CDAO (Chief Data & Analytics Officer) Summits · The AI Summit circuit 3
- Data Innovation Summit · Nordic Data Science and Machine Learning Summit circuit 1
- AI Engineer · QCon circuit 1
- SQLSaturday · PASS Data Community Summit circuit 1
- ODSC · MLOps World circuit 1
Sponsorships 2
| Event | Date | Place | Tier as listed | Normalized tier |
|---|---|---|---|---|
| Data Council New York City 2019 | Nov 12–13, 2019 | New York, United States | Partner | Other |
| BattleFin Discovery Day New York 2019 | Jun 19–20, 2019 | New York, United States | Discovery Day Silver Sponsors | Silver |
Speakers 3
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Alyce Ge | MLCON 2023 New York | speaker | Common Ways Machine Learning Models Fail to Hit Production | — |
| John Maiden | Data Council New York City 2019 | talk | Building a Knowledge Graph Using Messy Real Estate Data | — |
| Renee Huinker | Nordic PGDay 2019 | speaker | Good data gone bad, bad data gone worse | — |