Supercharge your ML from day one.
Startups and disruptors shouldn't focus their efforts on non-core projects, such as building their own infrastructure layers.
The Valohai MLOps platform enables you to focus on your core work: building models and deploying them to production.
The key benefits for startups
The Valohai MLOps platform supports the needs of your organization at every stage of your growth.
Streamline Infrastrucutre
Manage ML workloads across cloud providers, on-premise hardware, and private environments.
Trace and Reproduce
Automatically track every asset, making all experiments traceable and reproducible.
Futureproof Collaboration
Improve team productivity and ensure efficient onboarding cycles for new hires.Better outcomes for all functions
Your challenges might be different depending on your role. Here's how Valohai enables your success.
Product Owners
Deliver the product to the market with greater reliability and fewer resources.- Faster time-to-market
- More reliable product performance
- Higher team productivity
- Lower infrastructure costs
- No vendor lock-in
ML Engineers
Scale ML Operations and optimize model performance in production.- Auto-versinon models
- Schedule ML workloads
- Simplify handover
- Streamline troubleshooting
- Reproduce all runs
Data Scientists
Build state-of-the-art models through collaboration and expermentation.- Get access to compute
- Get access to data
- Manage datasets
- Compare experiments
- Reproduce local runs
Even with all the ready-made pieces we could use to build our solution, it just becomes an unreasonable budget and resourcing request to build and maintain our own custom MLOps solution. It wouldn’t make any sense to spend 90% of our time reinventing the wheel.
Thilo Huellmann, CTO and Co-Founder at Levity
Building a barebones infrastructure layer for our use case would have taken months, and that would just have been the beginning. The challenge is that with a self-managed platform, you need to build and maintain every new feature, while with Valohai, they come included.
Renaud Allioux, CTO and Co-Founder, Preligens
Large healthcare systems tend to run on Azure. For our own development, we prefer GCP. We don’t have to think too much about committing to one cloud provider. We can develop everything within the multi-cloud setup under Valohai with minimal changes to our code.
Petr Jordan, CTO and Co-Founder at Onc.AI
The MLOps platform purpose-built for ML Pioneers
Valohai is the first and only cloud-agnostic, MLOps platform that ensures end-to-end automation and reproducibility. Think CI/CD for ML.
Knowledge repository
Store and share the entire model lifecycle
Collaborate on anything from models, datasets and metrics.
With Valohai, you can:
- Automatically version every run to preserve a full timeline of your work.
- Compare metrics over different runs and ensure you & your team are making progress.
- Curate and version datasets without duplicating data.
Smart orchestration
Run ML workloads on any hybrid multicloud with a single click
Execute anything on any infrastructure with a single click, command or API call.
With Valohai, you can:
- Execute anything on any infrastructure with a single click, command or API call.
- Orchestrate ML workloads on any cloud or on-premise machines.
- Deploy models for batch and real-time inference, and continuously track the metrics you need.
Developer core
Build with total freedom and use any libraries you want
Your code, your way. Any language or framework is welcome.
With Valohai, you can:
- Turn your scripts into an ML powerhouse with a few simple lines.
- Develop in any language and use any external libraries you need.
- Integrate into any existing systems such as CI/CD using our API and webhooks.
Runs on but not limited to:
Integrates with these and many more:
