Evidently AI vs MLflow
both compete in AI Infrastructure. Updated daily with live metrics.
Evidently AI: 1.1M downloads/mo (-14%), 7.3K GitHub stars, 2 active contributors, $2M funded vs
MLflow
Source: AI-Buzz. Updated daily from npm, PyPI, GitHub, and Hacker News.
Key Differences
For production adoption: Evidently AI is depended on by 19 packages. Evidently AI has 1.1M package downloads per month (-14% MoM). Evidently AI appears in 340 GitHub repositories.
For growth trajectory: Evidently AI has 7.3K GitHub stars.
For longevity/risk: Evidently AI has raised $2M in total disclosed funding. Evidently AI's most recent round was Seed. both companies operate in the AI Infrastructure category.
Bottom Line
Evidently AI leads on developer adoption with 1.1M monthly package downloads. Both compete in the AI Infrastructure space. For a deeper look, visit each company's full profile for trend charts, funding rounds, and community sentiment data.
Downloads (30d)
Disclosed Funding
GitHub Stars
Package Dependents
Repos Importing (code adoption)
Momentum (0-100)
Data freshness notice: MLflow: no data freshness timestamp available.
← Scroll to compare →
| Metric | Updated Mar 17 | MLflow |
|---|---|---|
| Website | evidentlyai.com → | mlflow.org → |
| Description | Open-source ML monitoring and observability framework | Open-source platform for the ML lifecycle including experiment tracking and model registry |
| Total Disclosed Funding Source: Public records / manual researchUpdates: Weekly | $2M✓ | N/A |
| Last Funding | Seed Oct 2021 | Not available |
| Developer Adoption | ||
| Momentum | 32Moderate✓ | N/A |
| npm Registry Downloads (30d) Source: npm registryUpdates: DailyNote: Includes all package installations including CI/CD pipelines and mirrors | 0 | N/A |
| PyPI Registry Downloads (30d) Source: PyPI (Google BigQuery)Updates: DailyNote: Includes all package installations including CI/CD pipelines and mirrors | 1.1M✓ | N/A |
| PyPI Trend (30d) | - | |
| Total Downloads (30d) Source: npm + PyPI registriesUpdates: DailyNote: Sum of npm and PyPI; excludes other package managers | 1.1M-14%✓ | Not tracked |
| Active Contributors/Day Source: GitHub APIUpdates: DailyNote: Tracks designated public repos per company, not all company GitHub activity | 2✓ | N/A |
| Contributors Trend | 0% | - |
| PyPI Dependents Source: Libraries.io APIUpdates: WeeklyNote: Counts direct reverse dependencies from PyPI | 19✓ | N/A |
| Code Adoption (repos) Source: ecosyste.ms Packages APIUpdates: DailyNote: Approximate count; excludes forks | 340✓ | N/A |
| Status | Private | Unknown |
| HN Mentions (30d) Source: Hacker News (Algolia API)Updates: Daily | 0 | N/A |
| Reddit Mentions (30d) Source: Reddit (search API)Updates: DailyNote: Counts posts/comments mentioning the company by name | 3✓ | N/A |
| GitHub Stars Source: GitHub APIUpdates: DailyNote: Stars are bookmarks — a popularity signal, not a usage indicator | 7.3K✓ | N/A |
| Founded | 2020 | Unknown |
| Primary Category | ||
| Data Last Updated | Unknown | |
* MLflow has no npm/PyPI packages tracked - download metrics unavailable. Signal score based on GitHub and community data only.
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