# Getting Started

Valohai is an MLOps platform that handles infrastructure complexity while you build production ML systems. Train models, run experiments, and deploy to production, all without DevOps overhead.

### Core Capabilities

#### Full experiment tracking and lineage

Every run becomes reproducible and auditable.

* **Automatic versioning** — Code, data, parameters, and environments captured on every run
* **Metric comparison** — Compare runs, spot regressions, track model drift
* **Dataset versioning** — Link datasets to experiments without storage duplication

#### Infrastructure abstraction

Run ML workloads on any compute with one command.

* **Multi-cloud execution** — AWS, GCP, Azure, Oracle Cloud Infrastructure, Scaleway, OVH, Slurm, Kubernetes, or on-premises hardware
* **Elastic scaling** — Same code runs on 1 GPU or 100 GPUs
* **Production deployment** — Batch inference, REST APIs, or streaming endpoints with built-in monitoring

#### Framework agnostic

Your code, your tools, zero lock-in.

* **Any ML framework** — PyTorch, TensorFlow, JAX, Hugging Face, or custom stacks
* **Simple integration** — Add a `valohai.yaml` to any project
* **API-first design** — REST API and webhooks for CI/CD pipelines

### Who uses Valohai?

**Data Scientists & ML Engineers** — Focus on model development instead of cloud configurations\
**MLOps Teams** — Standardize workflows across projects without forcing tool changes\
**Enterprise ML Teams** — Meet compliance requirements with full audit trails and data lineage

### Start Building

| Resource                                                                             | Description                                       |
| ------------------------------------------------------------------------------------ | ------------------------------------------------- |
| [Quickstart](https://docs.valohai.com/getting-started/quickstart)                    | Run your first execution in 5 minutes             |
| [🎓 Valohai Academy](https://learn.valohai.academy/)                                 | Interactive learning path with hands-on exercises |
| [Example: Computer Vision](https://docs.valohai.com/project-gallery/computer-vision) | Import a working computer vision pipeline         |
| [Example: Fine-tune LLMs](https://docs.valohai.com/project-gallery/nlp-and-llm)      | Adapt language models to your domain              |

> 💡 **First time with MLOps?** Start with [Valohai Academy](https://learn.valohai.academy/) for guided tutorials that build from basics to advanced workflows.