Computer vision models built with PyTorch. Open-source LLMs like Mistral and Llama 3. Fine-tuned multimodal models.
No matter what you're building, Modelbit can help you deploy it in minutes.
You have full control over your environment. Deploy your code with git push, Modelbit will deploy it to an isolated container in minutes.
Learn MoreDeploying your model is as simple as calling mb.deploy right from your notebook. No need for special frameworks or code rewrites.
Models are deployed directly into your data warehouse, where making a model inference is as easy as calling a SQL function!
Modelbit models become REST APIs in the cloud. Your team can call them from websites, mobile apps, and IT applications.
Modelbit is backed by your git repo, where data is secure and version controlled, and CI/CD runs when changes are deployed.
We built a new compute framework that scales up and down as needed. Run on compute in our cloud or deploy Modelbit into your VPC.
Learn MoreModelbit is backed by your git repo. GitHub, GitLab, or home grown.
Code review. CI/CD pipelines. PRs and Merge Requests. Bring your whole git workflow to your Python ML models.
Once your models are deployed you'll get logging, monitoring, alerting, and all the tools you need to manage ML in production. Modelbit also integrates with your favorite ML tools like Weights & Biases, and many more.
Learn MoreUse Modelbit to deploy ML models into your cloud for maximum convenience paired with maximum security. Reach out to us to request access.
Request AccessFast, safe, and secure. Modelbit's managed cloud lets you run your models on the latest hardware that automatically scale up and down. Pay only for what you use.
Learn MoreFrom model experiment trackers, hosted data science notebooks, to feature stores and Snowpark ML.
Modelbit integrates with your ML stack.