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AI and ML

AI / ML from workstation to production

AI is going to disrupt your business. Let’s lead the AI race together.

Jigar systems is the platform to power your Artificial Intelligence ambitions — from developer workstations, to racks, to clouds and to the edge with smart connected IoT.

Canonical’s Kubeflow supports the most popular tools for machine learning — starting with JupyterHub and Tensorflow — in a standardised workflow running on Kubernetes.

Develop your AI Models on Ubuntu

Develop AI models on high-end Ubuntu workstations. Train on racks of bare metal Kubernetes or public clouds with hardware acceleration. Deploy to edge and IoT. All on Ubuntu, delivered by Canonical.

Kubeflow — AI on Kubernetes — anywhere

Google and Canonical collaborate on Kubeflow, a standardised machine learning solution for on-premise and on-cloud training. Leveraging Ubuntu, you benefit from perfect multi-cloud portability of AI/ML workloads.

/Workstation AI

Ubuntu-certified workstations from Dell and HP with NVIDIA, microk8s and Kubeflow

  • Accelerate data science
  • Lightest footprint
  • Laptop to workstation
  • GPGPU optional
  • Develop and test AI

/Bare metal AI

Kubernetes on bare metal with NVIDIA GPGPU acceleration

  • Highest performance
  • On-premise with local data
  • Hardware recommendations
  • Fully managed options

/Google Cloud AI

GKE on Ubuntu with NVIDIA GPGPU acceleration

  • Effectively infinite scale
  • Portable workloads
  • Fastest cloud ML

/Canonical Cloud AI

Kubeflow on Kubernetes on Openstack with NVIDIA GPGPU acceleration

  • Maximize benefits of OpenStack
  • On-premise with local data
  • Hardware recommendations
  • Fully managed options

Kubeflow features

Kubeflow brings together all the most popular tools for machine learning, starting with JupyterHub and Tensorflow, in a standardised workflow running on Kubernetes. Optimised on a wide range of hardware and cloud infrastructure, Kubeflow lets your data scientists focus on the pieces that matter to the business.

It is an extensible framework, which allows you to leverage the tools of your choice. Start with Tensorflow and JupyterHub or bring your own frameworks and tools. Combined with Kubeflow’s automation, this will accelerate your machine learning activities — from model development to model training to model sharing.

Install Kubeflow

Initiated by Google on Ubuntu for perfect portability of AI workloads from your workstation, to your data center rack on Canonical’s bare metal k8s or Canonical’s OpenStack virtualization, to Google’s Cloud Kubernetes service GKE which also runs on Ubuntu. Simple.

Canonical’s Kubeflow and Kubernetes on bare metal servers, with NVIDIA GPGPUs, provides an ultra high-performance machine learning cluster. Deployment, support, and optional remote management and remote operations make it the best way to accelerate your data science and machine learning.

AI add-on for Kubernetes Discoverer and Discoverer Plus

AI/ML Add-on


One additional day on Kubeflow, including Tensorflow and JupyterHub, covering everything your business needs to know to have a full on-prem/off-prem AI/ML game plan.

  • On site or remote options
  • Hands-on K8s and Kubeflow
  • Full pipeline view
  • ML / Data science assessment

Contact us

ML / Data Science Assessment


Canonical will leverage its network of data science partners to deliver an AI assessment as part of the workshop with options for ongoing engagement post-deployment.

  • Understand AI lifecycle
  • Preliminary AI discovery
  • Development assessment
  • Deploy and operate analysis
  • Finalize initial AI strategy

IoT and Edge AI

Train in the cloud. Act at the edge.

Cameras, music systems, cars, even firewalls and CPE are becoming smarter. From natural language processing to image recognition, from real-time high-speed autonomous navigation to network intrusion detection. Ubuntu gives you a seamless operational framework for development, training and inference all the way out to the edge.

JSL Consultants Worked At Fortune 500’S