AgentOps vs MLflow
both compete in AI Infrastructure. Updated daily with live metrics.
AgentOps: 672.1K downloads/mo (+43%), 5.4K GitHub stars, 2 dependents, $3M funded vs
MLflow
Source: AI-Buzz. Updated daily from npm, PyPI, GitHub, and Hacker News.
Key Differences
For production adoption: AgentOps is depended on by 32 packages. AgentOps has 672.1K package downloads per month (+43% MoM). AgentOps appears in 1 GitHub repositories.
For growth trajectory: AgentOps has 5.4K GitHub stars. AgentOps received 10 Hacker News mentions in the last 30 days.
For longevity/risk: AgentOps has raised $3M in total disclosed funding. AgentOps's most recent round was Seed. both companies operate in the AI Infrastructure category.
Bottom Line
AgentOps leads on developer adoption with 672.1K 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)
HN Mentions (30d)
Momentum (0-100)
Data freshness notice: MLflow: no data freshness timestamp available.
← Scroll to compare →
| Metric | Updated Mar 17 | MLflow |
|---|---|---|
| Website | agentops.ai → | mlflow.org → |
| Description | Observability and testing platform for AI agents | Open-source platform for the ML lifecycle including experiment tracking and model registry |
| Total Disclosed Funding Source: Public records / manual researchUpdates: Weekly | $3M✓ | N/A |
| Last Funding | Seed Feb 2024 | Not available |
| Developer Adoption | ||
| Momentum | 55Moderate✓ | N/A |
| npm Registry Downloads (30d) Source: npm registryUpdates: DailyNote: Includes all package installations including CI/CD pipelines and mirrors | 350✓ | N/A |
| npm Trend (30d) | - | |
| PyPI Registry Downloads (30d) Source: PyPI (Google BigQuery)Updates: DailyNote: Includes all package installations including CI/CD pipelines and mirrors | 671.7K✓ | N/A |
| PyPI Trend (30d) | - | |
| Total Downloads (30d) Source: npm + PyPI registriesUpdates: DailyNote: Sum of npm and PyPI; excludes other package managers | 672.1K+43%✓ | Not tracked |
| Active Contributors/Day Source: GitHub APIUpdates: DailyNote: Tracks designated public repos per company, not all company GitHub activity | 0 | N/A |
| npm Dependents Source: Libraries.io APIUpdates: WeeklyNote: Counts direct and dev dependents | 2✓ | N/A |
| PyPI Dependents Source: Libraries.io APIUpdates: WeeklyNote: Counts direct reverse dependencies from PyPI | 30✓ | N/A |
| Code Adoption (repos) Source: ecosyste.ms Packages APIUpdates: DailyNote: Approximate count; excludes forks | 1✓ | N/A |
| HN Discussion Share Source: Hacker News (Algolia API)Updates: DailyNote: Share of HN mentions within the company's primary category | 0.7% of HN mentions | - |
| Status | Private | Unknown |
| HN Mentions (30d) Source: Hacker News (Algolia API)Updates: Daily | 10✓ | N/A |
| Reddit Mentions (30d) Source: Reddit (search API)Updates: DailyNote: Counts posts/comments mentioning the company by name | 1✓ | N/A |
| Job Mentions (30d) Source: Job board aggregationUpdates: DailyNote: Counts job listings mentioning the company's technology | 1✓ | N/A |
| GitHub Stars Source: GitHub APIUpdates: DailyNote: Stars are bookmarks — a popularity signal, not a usage indicator | 5.4K✓ | N/A |
| Founded | 2023 | 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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