Streamline Delivery of AI Agents & Applications
Quali Torque simplifies the delivery and management of AI models and Machine Learning services to accelerate the delivery of AI solutions.
Don’t Let Complexity
Slow Down Your AI Strategy
Self-Service Access
Empower your data science teams with a self-service experience to access actively deployed AI models, databases, Machine Learning services, and GPU infrastructure.
Automated Actions
Ensure AI models and services are up to date with automation for training and other critical phases of the lifecycle.
Full-Stack Integration
Streamline the development of AI applications and agents with an intuitive experience to integrate infrastructure, data, AI models, and your application development pipelines.
See How Quali Torque Works
This brief demo shows how Quali Torque helps DevOps teams accelerate productivity while optimizing cloud costs.
How Quali Torque Uses AI to Support Data Science Teams
Streamlined Orchestration
Torque allows users to submit natural-language prompts to generate reusable blueprints defining the infrastructure, models, data services, and development environments needed to build AI solutions.
Self-Service Access
Torque provides data scientists self-service access to deploy live models via an intuitive, role-based experience so they can access the resources they need without submitting a ticket or relying on an engineer.
Automated Actions
Torque streamlines the day-to-day maintenance of AI models and ML services with workflows that can execute routine tasks like training, data quality assurance, and drift monitoring automatically or on-demand via a single click in Torque’s native UI.
Scalable GPU Infrastructure
Torque automatically scales GPU allocation to ensure sufficient capacity as AI models transition into resource-intensive phases like training, then reduces GPUs for less resource-intensive activity to prevent costly over-provisioning.
Tracking & Visibility
Torque dashboards track all activity, performance, and cloud infrastructure costs for AI workloads so data science teams can identify and reconcile anomalies that disrupt productivity or efficiency for their AI solutions.
Take Torque for a Test Drive
The Torque Playground allows you to build & launch real cloud environments with no email or credit card required.
Take a Deep Dive on Torque’s Support for AI Workloads
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Frequently Asked Questions
Torque helps data scientists leverage and maintain AI models and other services by making those services reusable and easy to manage at scale.
Today, many data scientists rely on engineering teams to build, provision, and maintain the AI models and other services they need. This creates a bottleneck and leads to delays for data scientists as engineers orchestrate, validate, and deliver those services.
Torque eliminates these delays by creating reusable blueprints defining each component of the AI tech stack–from infrastructure and data services to AI models, ML services, and applications–that data scientists can deploy, access, and maintain via Torque’s intuitive self-service experience.
This reusability also extends to the work that data scientists perform on live AI models, such as training or data quality assurance. Torque defines these routine actions as code that can be executed automatically based on custom schedules (e.g. once per day) and initiated on-demand via a single click in Torque’s self-service catalog.
Meanwhile, Torque’s native role-based access controls, secrets management capabilities, and streamlined provisioning experience reduces the risk of misconfigurations or security vulnerabilities. This ensures data science teams can only access the AI resources they need, without the ability to deploy anything that violates the organization’s standards.
Through this approach, data science teams can deliver higher-performing, more accurate, and more efficient AI models faster and more easily.
Quali Torque automates a wide range of infrastructure and environment-related tasks to help data science teams accelerate AI development and streamline operations.
For example, Torque can automatically perform:
- Adversarial robustness testing to help maintain accuracy
- Data quality assurance to make it easier to maintain high-quality data
- Monitoring for model drift and inference accuracy to prevent errors and maintain performance
Torque defines these actions as code using pre-defined workflows which can be executed repeatedly via automation or enacted via a single click in Torque’s native UI.
This enables data science teams to eliminate time-consuming manual processes, reduce the risk of environment misconfigurations, and rapidly iterate on AI models without waiting on DevOps support.
As a result, teams can focus more on data experimentation and model training while maintaining full visibility and control over cloud usage and spend.
Yes. Torque makes NVAIE resources available via the user’s inventory, which enables the user to generate a blueprint for any stack of an AI application by simply submitting AI prompts.
This helps NVAIE move faster by simplifying and accelerating the delivery of live environments that include NVAIE resources.
Learn more about Torque’s support for NVAIE here.