UbiOps

What is UbiOps?

UbiOps is a comprehensive AI infrastructure platform designed to simplify the deployment, scaling, and orchestration of machine learning and AI models. It enables teams to transform AI algorithms into reliable, scalable microservices with dedicated API endpoints, supporting seamless integration into production environments. The platform supports multi-cloud, hybrid, and on-premise setups, allowing organizations to maintain control over compute resources, reduce costs, and avoid vendor lock-in. UbiOps includes advanced MLOps capabilities such as model versioning, workflow pipelines, monitoring, security, and governance, making it suitable for industries with strict compliance requirements.

Key Features

• Production-Grade Model Deployment

  Deploy AI and ML models as scalable microservices with dedicated APIs, enabling easy integration and reliable production use.

• Workload Orchestration and Auto-Scaling

  Automatic horizontal scaling, traffic load balancing, and resource orchestration across multiple compute environments including cloud, on-premise, and hybrid setups.

• Model Management and Version Control

  Manage multiple models with versioning, monitoring, debugging, and automatic rollback capabilities to maintain model reliability.

• Modular Workflow Builder

  Create and manage complex AI pipelines by combining models, functions, and operators, each scalable and accessible via unique API endpoints.

• Comprehensive Monitoring and Governance

  Track model performance with custom metrics, detailed logging, and enforce team roles and permissions for secure collaboration.

• Flexible Deployment Options

  Operate UbiOps as SaaS, within your own Microsoft Azure tenant, or in hybrid-cloud environments to optimize compliance, cost, and control.

Use Cases

• AI Model Deployment for Enterprises : Deploy and scale AI models reliably across diverse infrastructure setups to support business-critical applications.
• MLOps and Workflow Automation : Streamline AI development cycles with modular pipelines and automated model management for faster iteration and deployment.
• Hybrid and Multi-Cloud Orchestration : Run AI workloads seamlessly across on-premise servers and multiple cloud providers, avoiding vendor lock-in and optimizing resource use.
• Secure and Compliant AI Applications : Build AI solutions that meet strict security and privacy standards with robust governance, encryption, and access controls.
• AI Training Job Management : Manage and track batch training jobs and experiments efficiently within the platform.

FAQs