Chassis vs Izlo
A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.
Chassis Agents | Izlo Agents | |
|---|---|---|
| Tagline | Open-source tool that auto-packages ML models into production-ready Docker containers with a prediction API. | Prompt management platform with version control, collaboration, and an API for production deployment. |
| Category | Agents | Agents |
| Pricing | Free· Free, open source (Apache-style community project) | Paid· Solo $20/mo; Pro $25/user/mo; Enterprise $39/user/mo |
| Model | — | Model-agnostic |
| Editorial score | 6.9 / 10 | 6.9 / 10 |
| Use cases | model-packagingedge-deploymentml-containerizationmlopskubernetes-serving | prompt-managementversion-controlteam-collaborationprompt-testingproduction-deployment |
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| Cons |
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| Website | chassisml.io | getizlo.com |
Pick Chassis if
- ✅ One Python call turns a trained model into a Docker prediction container
- ✅ Cross-compiles for x86 and ARM, including Jetson and Raspberry Pi
- ✅ Framework-agnostic across Scikit-learn, PyTorch, TensorFlow
- ✅ Fully open source with no vendor lock-in to Modzy
Pick Izlo if
- ✅ Git-style version history and activity log for every prompt change
- ✅ Remix sandbox isolates experiments from production prompts
- ✅ REST API lets you swap prompts without redeploying the app
- ✅ Built for multi-user team editing, not just solo developers