UbiOps

UbiOps is an AI infrastructure platform that helps teams quickly run their AI and machine learning workloads as reliable and secure microservices without changing existing workflows. It provides ultra-fast pipelines with zero DevOps, optimized computing resources, support for LLMs and CV models, and other features. UbiOps supports hybrid and multi-cloud workload orchestration, allowing models to be deployed in private or public cloud environments, ensuring that data and models always remain in the user's environment. In addition, UbiOps provides built-in security features such as end-to-end encryption, secure data storage and access control to help enterprises comply with relevant regulations.

Demand group:

" UbiOps is suitable for teams that need to run AI and machine learning workloads quickly, reliably and securely. Whether you are a startup or a data science team in a large organization, UbiOps provides strong support. It is especially suitable for teams that need to deploy in private environments AI models, enterprises that need to dynamically scale computing resources and need to comply with specific regulations."

Example of usage scenario:

Reef Support uses UbiOps to train AI models for coral reef protection.

On-demand computer vision model inference for real-time workloads in digital agriculture.

The National Cyber ​​Security Center partners with UbiOps to innovate digital security in the Netherlands.

Product features:

Rapidly deploy AI models: Deploy models and features in 15 minutes, from fine-tuned LLMs to computer vision models.

Private environment deployment: Deploy ready-made models in UbiOps projects and run them on private infrastructure.

Out-of-the-box AI infrastructure: Run your first job in minutes, manage multiple AI workloads, no DevOps experience required.

Security and compliance by design: Provides end-to-end encryption, secure data storage and access control to ensure business compliance.

NVIDIA AI Enterprise Partners: Provide the best infrastructure and capabilities to help data science and AI teams run and manage their AI workloads.

Dynamically expand computing resources: Dynamically expand AI workloads based on usage to accelerate model training and inference.

Supports hybrid and multi-cloud environments: Deploy models in private or public cloud environments to optimize cost, compliance and computing resources.

Usage tutorial:

1. Visit the UbiOps website and register an account.

2. Integrate UbiOps into the data science workbench and start using it.

3. Select the AI ​​model or machine learning model to deploy.

4. Configure the deployment environment of the model, including computing resources and security settings.

5. Deploy the model and test its functionality.

6. Monitor the performance and usage of the model and make adjustments as needed.

7. Leverage UbiOps ’ automated scaling capabilities to cope with workload peaks.