Evidently AI
Circuit mix
Where Evidently AI 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 science100%5 events
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 |
|---|---|---|---|---|---|---|---|---|---|---|
| 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.
Where they've grown or pulled back
Evidently AI has never sponsored a tracked conference, so this follows where its speakers appear instead.
DownNothing recorded in 2026; had speakers at 1 conference in 2023.
Counted per conference. 2026 is the latest year whose conferences have mostly happened. A conference counts as no longer seen only when later events published speaker lists.
Not on the company map: lookalikes are computed only for companies present at four or more conferences.
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 0 this company sponsored).
No co-sponsors: this company has no recorded sponsorships, or sponsored alone.
Sponsorships 0
No sponsorships recorded for Evidently AI.
Speakers 5
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Emeli Dral | PyData London 2025 | talk | AI agents testing: How to evaluate the unpredictable | — |
| Emeli Dral | PyData London 2024 | talk | The evolving conversation: How continuous testing keeps your LLM on track. | — |
| Emeli Dral | PyData Amsterdam 2023 | talk | Mind the language: how to monitor NLP and LLM in production | — |
| Emeli Dral | PyCon DE & PyData Berlin 2023 | talk | Staying Alert: How to Implement Continuous Testing for Machine Learning Models | — |
| Emeli Dral | PyCon DE & PyData Berlin 2022 | talk | Detecting drift: how to evaluate and explore data drift in machine learning systems | — |