Simplify & Optimize Your ML Apps at Scale

Quali Torque simplifies and automates the creation, deployment, and optimization of AI model and Machine Learning applications at scale.

Streamline ML Ops with
Reusability & Automation

Reduce the manual work required to build, deploy, and maintain performance and accuracy for your ML applications.

See How Quali Torque Optimizes ML Ops

Streamline ML Ops with Quali Torque

Leverage Your App Resources

Quali Torque leverages your Infrastructure as Code and other application resources so you can create Environment as Code templates that can be launched on-demand.

AI Infrastructure Orchestration

Submit natural language AI prompts describing how your IaC resources should be configured and Quali Torque will automatically design that environment and generate a reusable Environment as Code template to provision it.

Self-Service Access

Give your internal teams role-based access to deploy AI application environments and execute critical actions–such as testing and monitoring for adversarial robustness, data quality assurance, inference accuracy–in just a few clicks.

Automated Actions

Create triggers to automate the execution of mission-critical applications needed to maintain AI application performance and accuracy in response to specific events or recurring schedules.

AI Cloud Cost Controls

Track all activity and associated costs by the users and teams responsible while automating the enforcement of custom guardrails to prevent wasted cloud costs due to over-sized, idle, or otherwise inefficient infrastructure deployments.

Visit the Torque Playground to Try it For Free

With no email or credit card required, you can build & launch real cloud environments from IaC.

Frequently Asked Questions

Torque connects to the user’s repositories and leverages the code defined in their Infrastructure as Code, Configuration Management, and other resources to provision the infrastructure needed to deliver an application.

Once connected to the repository, Torque creates reusable Environment as Code templates for application environments. In Torque, these are called blueprints.

Blueprints contain the code to generate the environment, which enables users to launch those applications by simply clicking “launch” in the platform (or via integrations with GitOps or CI/CD tools).

These blueprints can include the creation of GPUs to run AI applications, which eliminates the learning curve by eliminating the infrastructure nuances and enabling the provisioning of AI clodu infrastructure in just a few clicks.

Similar to environments, Quali Torque defines Day-2 actions as code.

The user can define the action as a “Workflow” in Torque, which includes the code needed to execute the action.

This can include the actions required to ensure that AI models are accurate and performing as expected.

For AI applications, some examples include:

  • Adversarial robustness testing
  • Data quality assurance
  • Monitoring for model drift, inference accuracy, or resource utilization
  • AI model explainability & interpretability

Learn more about automated Day-2 actions with Quali Torque here.

Since Quali Torque initiates the creation of the cloud resources powering the application environment, the platform monitors all resources that are deployed and how long they are run.

This allows the platform to enforce rules for cloud resource deployment. Known as Policies in Torque, these can include cost-optimization policies such as restrictions on instance size, allowed cloud regions, and maximum runtimes.

Any attempt to deploy a resource that violates these policies will be denied until the violation is corrected. Administrators in Torque can also set approvals so that admins can allow/deny this activity in a single click.

Learn more about cloud cost optimization with Quali Torque here. 

Still have questions? Our team is here to help

Book a demo to learn more about how Quali Torque for ML Ops.