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Innovate at speed with compliant open source – from workstations to clouds and smart devices. Get all the enterprise AI solutions you need from a trusted partner at a predictable cost.
Canonical offers you the building blocks so you can innovate at your own pace. From getting started with data science on Ubuntu workstations to scaling your big data analytics with supported database and MLOps software. All on open source.
The first step is always the hardest, especially with AI expertise in such short supply. Canonical’s professional services will help you bridge the skills gap and overcome the barriers to AI adoption.
Upskill your team and lay the groundwork for your projects with a 5-day MLOps workshop, work with us to build a PoC, or completely offload the AI operational burden with managed services.
Canonical partners directly with leading silicon vendors to optimize and certify our open source software solutions with dedicated AI hardware to ensure Ubuntu runs optimally across all major architectures. You can pick the best AI accelerators for your use cases, and take full advantage of your hardware's capabilities.
With inference snaps, you can deploy well-known AI models ‐ like DeepSeek R1 and Qwen VL ‐ with a single command, and the model will be automatically optimized for your specific hardware.
Run your workloads anywhere, including hybrid and multi-cloud environments.
Choose the ideal infrastructure for your use cases – start quickly with no risk and low investment on public cloud, then move workloads to your own data center as you scale. Benefit from a consistent, optimized OS, tooling and GPU support throughout your entire AI journey.
Ubuntu is the OS of choice for data scientists. Develop machine learning models on Ubuntu workstations and deploy to Ubuntu servers. Continue with the same familiar Ubuntu experience throughout the AI lifecycle, across clouds and all the way to the edge.
Data is at the heart of every AI project, which is why our stack includes a suite of leading open source data solutions enhanced with enterprise features. Automate and scale while enjoying predictable pricing and 10 years of enterprise-grade security and support.
Simplify workflow processes and automate machine learning deployments at any scale with our modular MLOps solutions. Our supported Kubeflow distribution, integrated with a growing ecosystem of AI and data tooling, brings scalability, portability and reproducibility to your machine learning operations.
AI is set to transform our factories, our cars, and our homes. We enable the innovators behind that transformation. From compute to device management, we provide the tools to power your edge AI use cases while preserving security, and compliance.
Your models and sensitive data need to be secured at every stage of the ML lifecycle. With confidential AI on Ubuntu, you can protect your data and model at run-time with a hardware-rooted execution environment. Strengthen your compliance posture and safely fine-tune your model with your enterprise data.
Rapidly access all the open source software you need for AI, and run it with peace of mind. We maintain and support all of the key open source software in the AI lifecycle so you don’t have to. Leave the CVE fixes to us, so you can fast-track compliance and focus on your AI models.
What customers say
“We needed a cloud solution that was stable, reliable and performant. Canonical allowed us to do this by helping to design and deploy our cloud - and they helped us do this quickly.”
Peter Blain
Director of Product and AI, Firmus
“Partnering with Canonical lets us concentrate on our core business. Our data scientists can focus on data manipulation and model training rather than managing infrastructure.”
Machine Learning Engineer
Consumer entertainment company
LLMs and generative AI are dominating much of the current AI/ML discourse, and their potential goes far beyond chatbots. Our blog breaks down LLM use cases, challenges and best practices.
Go deeper on GenAI in this webinar explaining how to enhance your model outputs with RAG.
Explore how Canonical partners with silicon vendors to optimize our solutions with certified hardware.
Download the reference architecture for a detailed guide to infrastructure for machine learning use cases.
