Reusability & Scalability for Nvidia AI Enterprise Resources
Quali Torque creates easy-to-use modules defining Nvidia AI Enterprise Software resources that can be orchestrated into managed environments quickly and easily.
Simplify How You Leverage Nvidia AI Enterprise Software
Accelerate how you build, run, and maintain all layers of your AI solutions with an intuitive platform to leverage Nvidia AI Enterprise Software.
Reusable Modules
Eliminate redundant configuration and scripting with reusable modules defining Nvidia AI Enterprise solutions.
AI-Powered Orchestration
Submit natural-language AI prompts to orchestrate your Nvidia AI Enterprise resources into ready-to-run blueprints defining the infrastructure, data, and models needed to power your AI solutions.
Day-2 Optimization
Deploy, monitor, and automate routine tasks for all layers of your AI solution so your teams can spend less time on orchestration and maintenance.
See How Quali Torque Supports AI Workloads
Watch this video to see how Torque manages each layer of the tech stack support Agentic AI solutions.
Ready to learn more? Book a demo to go deeper
Browse Documentation on Torque’s Support for AI Workloads
Quali Torque Leverages Nvidia AI Enterprise Solutions to Accelerate Operations
Easy-to-Use Infrastructure Modules
Torque creates interchangeable “building blocks” defining code for frameworks, models, and other tools made available via Nvidia AI Enterprise, which can be deployed repeatedly and easily orchestrated together to deliver any layer of the stack supporting your unique AI solutions.
AI-Powered Orchestration
Based on the inventory of reusable modules defining Nvidia AI Enterprise resources, Torque’s AI Copilot automatically designs and creates an executable blueprint to define the infrastructure, data, models, and agentic layers of the AI tech stack.
Self-Service Access
Torque allows users to deploy and integrate each layer of the AI tech stack and provides an intuitive user experience for end users to access outputs as well as for operations teams to monitor an understand configuration and performance of those resources.
Dynamic GPU Scaling
Torque treats each layer of the AI tech stack as a managed environment and scales GPU resources dynamically to provide capacity for resource-intensive phases, while also preventing over-provisioning for less resource-intensive phases.
Day-2 Automation
Torque automatically executes routine tasks to maintain high-performing AI solutions, such as training and data quality assurance, so your teams can spend less time on maintenance and can monitor the execution of these actions on-demand.
Frequently Asked Questions
Torque manages the entire lifecycle of the tech stack supporting AI solutions, including the design and orchestration of Nvidia AI Enterprise resources.
To accomplish this, Torque creates reusable modules defining the code for individual Nvidia AI Enterprise resources that can be provisioned individually and orchestrated together easily.
For example, users can submit natural-language prompts to Torque’s AI Copilot describing how to configure the models and data science frameworks supporting an Agentic AI solution. Torque’s AI Copilot will leverage its inventory of modules defining those resources to automatically design the layer of the tech stack described in the prompt, and will also generate a new “blueprint” defining the code needed to provision it.
Torque can then execute the code to deploy that layer, then monitor the state of those resources. This allows Torque to identify provisioning errors, configuration drift, and unexpected updates so users can reconcile these issues proactively.
Torque also automates critical tasks, such as training and data quality assurance, to reduce the effort needed to maintain AI solutions. Torque defines these actions as code, known as Workflows in the product, and can automatically execute them based on custom triggers. When these actions occur, Torque automatically scales GPUs to align with the workload needs.
For a brief overview, watch this video.
Both! Torque treats all infrastructure equally, regardless of where it’s hosted. This simplifies orchestration, delivery, and maintenance to reduce the time and budget spent on GPUs, data services, and other infrastructure supporting AI solutions.
Torque users can leverage any number of agents to deploy their GPU infrastructure, including AWS, Microsoft Azure, Nvidia DGX, Nebius, Coreweave, Oracle Cloud Infrastructure, and Kubernetes.
For questions about support for GPUs, book a demo with our team.