Neptune AI Alternatives: 5 Tools to Migrate After the Shutdown (2026)
If you’re still on Neptune, your data and experiments are at risk. You need to export your data and pick a replacement — the sooner the better. This guide covers exactly what to do.
Neptune AI was one of the better experiment tracking tools — clean UI, solid versioning, reasonable $35/month pricing. But with the shutdown confirmed, staying on it is not an option. The good news: several tools do everything Neptune did, and some do it better.
Here’s what this guide covers:
- The 5 best Neptune AI alternatives right now
- Which tool matches your budget and team size
- A step-by-step migration guide to export your data
- The fastest path to get back up and running
Quick comparison: top Neptune alternatives
| Tool | Price | Open source | Best for | Migration ease |
|---|---|---|---|---|
| MLflow | Free | Yes | Budget / self-hosted | Easy |
| Weights & Biases | $50/user/mo | No | Team collaboration | Easy |
| Comet ML | $35/user/mo | No | Production monitoring | Medium |
| ClearML | Free / $15/mo | Yes | Full MLOps platform | Medium |
| DVC | Free | Yes | Git-based workflows | Harder |
Why is Neptune AI shutting down?
Neptune AI was acquired in late 2025. Following the acquisition, the new ownership decided to wind down the standalone platform rather than continue developing it. New sign-ups have been closed, and the platform is shutting down completely in March 2026.
🏆 1. MLflow — best free Neptune alternative Top pick
Price: Free forever | Best for: budget teams, solo engineers
MLflow is where most Neptune users are landing — and for good reason. It’s free, framework-agnostic, and has been battle-tested in production at major companies for years. The migration from Neptune is straightforward: swap out your Neptune logging calls for MLflow equivalents and you’re running in an afternoon.
The UI is more functional than beautiful, but it covers everything: run comparison, parameter logging, artifact storage, and model registry. Most importantly, there are no usage caps and no surprise bills.
Pros: Completely free, no caps | Works with PyTorch, TF, sklearn, XGBoost | Huge community | Self-hosted = full data ownership
Cons: UI not as polished as Neptune | You manage the server yourself
📖 See how MLflow stacks up against W&B in depth — read our MLflow vs Weights & Biases comparison.
2. Weights & Biases — best for team collaboration
Price: $50/user/month | Best for: teams who loved Neptune’s UI
If what you valued most about Neptune was its clean dashboard and easy sharing with teammates, Weights & Biases is the closest like-for-like replacement. The UI is polished, stakeholder-friendly, and the community is large enough that you’ll never be stuck on a problem for long.
The tradeoff is cost. At $50/user/month, a team of five pays $250/month — significantly more than Neptune. The free tier is genuinely usable for solo projects, though.
Pros: Best-in-class dashboard & UI | Easy sharing | Large, active community | Excellent documentation
Cons: $50/user/month gets expensive fast | Free tier has storage limits
📖 W&B too expensive? See our full list of 7 best Weights & Biases alternatives — including options at $15/month and free.
3. Comet ML — best for production monitoring
Price: $35/user/month | Best for: teams tracking models after deployment
Comet ML is the strongest direct Neptune replacement on price — $35/month vs Neptune’s $35/month — and it adds something Neptune never had: production model monitoring. You can track model drift, data distribution shifts, and performance degradation after deployment, all inside the same tool you use for experiments.
The free tier includes 300GB storage, which is more than enough to evaluate whether Comet fits your workflow before committing.
Pros: Same price as Neptune was | Production monitoring built in | 300GB storage on free tier | Strong experiment visualizations
Cons: Steeper learning curve than Neptune | Dashboard layout takes adjustment
4. ClearML — best open source full-platform option
Price: Free tier / Pro $15/user/month | Best for: teams wanting full MLOps control
ClearML is the most underrated tool on this list. It’s not just an experiment tracker — it handles data versioning, pipeline orchestration, and model serving under one roof. The self-hosted version is completely free and gives you total ownership over your data, which matters if you’re in a regulated industry or dealing with sensitive datasets.
At $15/month for the Pro tier, it’s the cheapest paid option here and delivers more functionality than tools charging three times as much.
Pros: Full MLOps platform, not just tracking | Very generous free tier | Self-hosted for complete data control | Active open source community
Cons: Complex initial setup | Steeper config curve than Neptune
5. DVC — best for Git-native workflows
Price: Free forever | Best for: teams already living in Git
DVC takes a completely different approach to experiment tracking. Instead of a separate dashboard, experiments are versioned as Git commits. No external service, no account, no SaaS dependency. Your entire ML history lives in your repo, right next to your code.
This is the hardest migration from Neptune since the mental model is quite different — but for teams that care about reproducibility, data versioning, and CI/CD integration, there’s nothing better.
Pros: Works with any Git repository | Zero external dependencies or accounts | Best-in-class data versioning | Perfect for GitHub Actions pipelines
Cons: Very different from Neptune’s model | Limited visualization out of the box
How to migrate from Neptune right now (step by step)
- Export your Neptune data
Go to your Neptune dashboard → Settings → Export. Download all experiment logs, metrics, and artifacts. Save multiple copies — local and cloud backup. - Choose your replacement
Use the decision guide below. If unsure, pick MLflow — it’s free and you can always switch later. - Install your new tool
MLflow:pip install mlflowthenmlflow ui| W&B:pip install wandbthenwandb login - Re-run or re-import critical experiments
Your Neptune export serves as the historical record. Re-log the most important runs in your new tool so they’re searchable. - Update team docs and CI/CD configs
Replace any Neptune API keys, webhook URLs, or logging calls throughout your codebase and pipeline scripts.
Don’t wait until the last week. Data exports can be slow for large projects.
Which tool should you pick?
| Solo dev, tight budget | MLflow | Free, no limits |
| Team collaboration matters | Weights & Biases | Best dashboard, $50/mo |
| Need production monitoring | Comet ML | Same price as Neptune was |
| Want full MLOps control | ClearML | Free tier, $15/mo Pro |
| Git-first, hate SaaS | DVC | Free, Git-native |
| Genuinely not sure | Start with MLflow | Free, easy to switch later |
✨ Don’t panic — just pick one and migrate ✨
Neptune shutting down is disruptive, but it’s also a good forcing function to pick a tool that fits your team better in 2026. Export your data today, pick one from the list above, and be running again by tomorrow.