New integrations lower the barrier to adoption for Agentic Artificial intelligence (AI) by automating management across development resources, including Large Language Model (LLM) (LLMs), data services, GPU infrastructure, and more to deliver high-performing AI agents.

Quali, a provider of platform engineering solutions for infrastructure automation and management, announced its integration with NVIDIA AI Enterprise software. This includes NVIDIA NIM™ microservices and NVIDIA AI Blueprints, aimed at simplifying the creation and management of Agentic AI solutions.

Agentic AI offers opportunities for enhancing internal operations and customer experience. Utilizing NVIDIA NIM microservices and NVIDIA AI Blueprints included in NVIDIA AI Enterprise software, the Quali Torque Software-as-a-Service platform streamlines the orchestration and management of each layer of the Agentic AI tech stack, including accelerated infrastructure, cloud services and data pipelines, LLMs, AI models, and applications.

Torque provides unified orchestration, lifecycle management, and cost optimization, ensuring reliability, accuracy, and efficiency across the development stack.

The platform manages the entire infrastructure lifecycle using Environments as Code (EaC)—a model that converts cloud resources into fully managed environments for mission-critical operations, including AI workloads, software development, and training.

Quali can deploy and manage the entire tech stack for Agentic AI solutions, facilitating faster adoption and scalability for organizations.

Key highlights of this release include:

  • Easy-to-Use Modules of NVIDIA AI Enterprise & Other NVIDIA Resources: Torque creates reusable modules for each AI agent component, accelerating delivery and adoption of Agentic AI.
  • AI-Driven Environment Design, Creation, & Reusability: Torque’s AI Copilot designs environment blueprints in response to user prompts, facilitating easier deployment and maintenance.
  • Simplified Provisioning & Maintenance: Torque provisions each tech stack layer, monitors resources, and alerts users about anomalies for proactive management.
  • Streamlined Integration of Each Layer: Managed environments in Torque allow users to access resources seamlessly, enhancing the development experience.
  • Automating Critical Tasks: Torque workflows automate maintenance tasks crucial for high-performing AI solutions, reducing manual effort.
  • Dynamic GPU Scaling: Torque adjusts GPU capacity according to application demands, ensuring efficient resource allocation.

“Complexity has always been at the core of the problems we solve for our customers and partners,” said Lior Koriat, Quali CEO. “As more organizations look to embrace AI, the ability to cut through complexity is the key to delivering the kinds of AI experiences that customers expect. We’re thrilled to develop a streamlined approach for delivering impactful AI solutions leveraging NVIDIA AI, and we look forward to helping our community unlock these opportunities.”