Experiment tracking for ML teams
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Tracked since2025
0 reviews trackedThe Bottom Line
Entry price
Free plan available, paid tiers above
Biggest pro
Good experiment tracking
Biggest con
Expensive
TL;DR - Neptune.ai
- Neptune.ai is an ML experiment tracking and model registry platform
- It logs, organizes, and compares machine learning experiments at scale
- Free tier available, Team plans from $49/month
Pricing: Free plan available
Best for: Growing teams
What is Neptune.ai?
Neptune.ai tracks machine learning experiments with collaboration focus. Log experiments, compare runs, share results-MLOps for teams that work together. The collaboration features help teams. The tracking is comprehensive. The comparison is visual. ML teams wanting collaborative experiment tracking use Neptune for team MLOps.
Pros & Cons
Pros
- Good experiment tracking
- Clean UI
- Good integrations
- Team features
- Flexible logging
Cons
- Expensive
- Less known than W&B
- Smaller community
- Some features basic
- Storage limits
Key Features
Experiment trackingModel registryMetadata storeComparisonsTeam featuresEnterprise
Pricing Plans
Free TrialPricing checked Jul 9, 2026
Startup
$150 / user/month
- Unlimited tracked hours
- Unlimited users and projects
- 1B data points/month
- 1 TB storage
- 99.99% ingestion SLA
- SSO/LDAP
- Standard email and chat support
Lab
$250 / user/month
- Everything from Startup
- 10B data points/month
- 10 TB storage
- Forking of runs
- Role-based access control
- Priority email and chat support
- Dedicated Customer Success Manager
- User support Slack channels
Self-hosted
Custom
- Everything from Lab
- Deployment on own infrastructure or private cloud
- Dedicated instance deployments
- Custom ingestion speed and storage limits
- High reliability/availability options
- Site Reliability Engineer support
Reviews
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Neptune.ai FAQ
How does Neptune.ai support machine learning teams in their daily workflow?
Neptune.ai helps ML teams by providing collaborative experiment tracking, allowing them to log experiments, compare runs, and share results efficiently. This focus on team MLOps streamlines the process of working together on machine learning projects.
Which teams benefit most from using Neptune.ai?
ML teams that require collaborative experiment tracking and visual comparison of runs will find Neptune.ai most beneficial. It is designed for groups that need to work together on machine learning operations.
How does Neptune.ai compare to MLflow for experiment tracking?
Neptune.ai emphasizes collaborative experiment tracking with strong team features and a clean UI, while MLflow also offers experiment tracking capabilities. Neptune.ai provides flexible logging and visual comparison tools for shared ML projects.
What kind of limitations should users be aware of when considering Neptune.ai?
Users should be aware that Neptune.ai can be expensive, and it has storage limits. Additionally, some of its features are considered basic, and it has a smaller community compared to some competitors.
How is Neptune.ai priced?
Neptune.ai is available on a free tier, which allows users to get started without initial cost. For more extensive usage and additional features, paid plans are offered.
Can Neptune.ai integrate with existing machine learning tools?
Yes, Neptune.ai offers good integrations, allowing it to connect with various tools in a machine learning ecosystem. This flexibility supports existing workflows and enhances its utility for ML teams.
Source: neptune.ai