UbiOps is a powerful AI infrastructure platform designed to help teams deploy and serve the next generation of AI products without the usual engineering complexity. With UbiOps, data scientists can deploy all of their machine learning models as scalable inference APIs, including large, off–the–shelf AI models like LLMs. Built with scalability, security, and robustness in mind, UbiOps serves as a foundation for many AI applications across different industries.

🚀 WHAT IS UBIOPS?

UbiOps is an AI serving and orchestration platform that enables your team to run your AI and ML workloads as reliable, secure microservices and deploy modular applications, across local and (hybrid)cloud environments.

UbiOps takes care of containerization of your code, deploying it as a microservice with its own API endpoint, request handling and automatic scaling. UbiOps also has advanced MLOps features for creating modular pipelines, model version management, job scheduling, monitoring, security and governance.

UbiOps integrates with Microsoft Azure infrastructure so users can let UbiOps orchestrate AI workloads in their Microsoft Azure tenant.

🎯 WHO IS IT FOR?

UbiOps is the ideal solution for:

• Data Scientists & AI teams: Streamline the deployment and management of your AI and ML models.
  

• IT Teams: Ensure a simple and secure integration with the rest of your infrastructure and tech stack.
  

• CTOs or Heads of Data Science: Accelerate AI product development while optimizing cost efficiency.
  
  

🌟 KEY PRODUCT FEATURES

The UbiOps platform comes with the following features

• Production grade ML / AI model deployment
  UbiOps is your turn-key production environment to deploy and run your ML & AI models and algorithms. Integrate them easily with products and systems. Turn your AI algorithms and code into scalable services with their own API.
  

• Workload Orchestration & Scaling
  UbiOps takes care of automatic horizontal scaling of model containers, traffic load balancing and API management. Above all the UbiOps orchestration engine guarantees efficient orchestration of all containers across available compute resources, ensuring reliability and cost effectiveness. You can connect multiple compute environments to your UbiOps projects including on-premise, multi & hybrid-cloud setups. Connect Kubernetes clusters, cloud providers APIs, single VMs or on-premise servers simultaneously. UbiOps will take care of orchestrating models and workloads across all your environments from a single interface.
  

• Model Management (catalog)
  Manage countless AI models simultaneously. UbiOps offers tools for version control, monitoring, and debugging of deployed models, as well as automatic rollbacks in case of errors.
  

• Model Training
  UbiOps supports running your AI training workloads as batch jobs. Manage and track multiple experiments and evaluate outcomes.
  

• Workflow Builder (Pipelines)
  Create modular workflows with multiple models, functions and operators. All the modules are version controlled and individually scalable. Every pipeline has it's unique API endpoint.
  

• Monitoring, logging & governance
  Monitor models in production, track custom metrics and use the logging functionality for debugging. If you're working in a larger team, you can define different projects, assign roles and give granular permissions to people.
  

• Cloud, on-premises or hybrid
  UbiOps can be used as Software-as-a-Service (SaaS) or installed in your own Microsoft Azure tenant. UbiOps also supports a hybrid-cloud setup which helps you run AI & ML models in environments and regions of choice, optimizing for compliance and costs.
  

• Security and Reliability
  Being ISO27001 certified, UbiOps provides robust security features help businesses comply with data privacy regulations such as GDPR.