Here’s what our business customers are saying:
They have GPUs, they have executive sponsorship, and they have compelling use cases. But they’re still 12, 14, even 16 weeks into an AI project, manually piecing together the infrastructure and software stack. Their best talent is debugging vendor compatibility instead of building something that is supposed to transform the business.
It’s not an infrastructure issue. This is an operational issue and is the biggest obstacle to deploying AI at scale. That’s why this week at Cisco Live 2026 in Las Vegas, we’re introducing two major steps toward operationalizing enterprise AI.
Cisco compatible solutions for AIa growing ecosystem of AI software and solutions vetted and tested on Cisco AI Infrastructure.
Stack Automation with Qualiis a new deployment automation platform developed in collaboration with Cisco that enables customers to move from rack to application in hours instead of weeks.
They are designed to help companies reduce the operational complexity that slows AI adoption.
The era of operation has begun
For the past two years, the conversation around enterprise AI has centered around infrastructure acquisition. Can GPUs be deployed fast enough to meet demand? But the challenge is no longer just about purchasing the hardware. We are operationalizing AI at scale. This is where the real work begins.
AI now requires orchestrating accelerated compute, networking, storage, AI software frameworks, security tools, observability, and industry-specific applications, all integrated into production-ready systems that can run reliably, consistently, and at scale.
This is the foundation behind the Cisco AI POD, part of the Cisco Secure AI Factory in collaboration with NVIDIA. A pre-validated architecture that integrates compute, networking, storage, security, and observability to reduce deployment complexity from the beginning.
However, infrastructure alone cannot bridge the gap between adoption and business value. Organizations also need confidence that the software, development frameworks, and AI or agent AI applications running on their infrastructure will work reliably in production.
Cisco-compatible solutions for AI are designed to address just this.
Bridge the gap with Cisco-compatible solutions for AI
Cisco-compatible solutions for AI are a new differentiator for developer solution partners in the Cisco 360 Partner Program. This new model makes it easier for customers to discover and use AI applications across a growing and curated ecosystem of third-party AI software vendors across vertical industries such as manufacturing, retail, and healthcare, as well as horizontal categories such as AI development and agent platforms on Cisco AI Infrastructure.
When organizations choose a Cisco-compatible solution for AI, they don’t start from scratch. They get a pre-vetted solution that is tested for compatibility with Cisco AI infrastructure from core to edge.
Our work with SumerSports is a powerful example of how this is already happening in an industry where trust and speed directly impact results. The goal is simple. Our goal is to help organizations bridge the gap between AI and business value by reducing the integration complexity that slows enterprise AI adoption.
And we took it a step further.
From rack to app in hours with Quali’s Stack Automation
This week, we introduce Stack Automation by Quali, a new deployment automation platform co-designed with Quali, an agent AI accelerator for infrastructure operations, and exclusively provided by Cisco.
Quali’s Stack Automation embeds Cisco Validated Designs, automation intelligence, and repeatable blueprints directly into your deployment workflow. This enables organizations to automate infrastructure configuration, AI tools, software layers, security, and rack-to-application observability to operate full-stack AI environments.
Instead of spending weeks manually building an AI environment, organizations can deploy reproducible, manageable full-stack environments in hours. This includes:
- Physical infrastructure: compute, networking, storage configuration
- Infrastructure Software: Cisco Validated Designs in collaboration with strategic partners
- AI Development Tools: Frameworks and blueprints available with NVIDIA AI Enterprise to accelerate application development
- Ready-to-deploy AI applications: Deliver industry-specific results to production with Cisco-compatible solutions for AI
- Security and observability: built in at every layer
Over time, these capabilities will be made available through Cisco Cloud Control, creating a single plane of operations for deploying, managing, securing, observing, and automating your AI environment through one login, one inventory, one assistant, and one agent workspace.
It’s a fundamentally different way of operating.
What does this look like in the real world?
Let’s explain this specifically.
A manufacturer wants to implement computer vision on its production line. Currently, it takes several months of integration work before the model recognizes the camera feed. These deployments can be completed in days using a proven operational approach that combines infrastructure, AI tools, security, and automation into a repeatable system.
Or seek medical care. Providers want to use AI to speed up diagnostic workflows, but standing up infrastructure, integrating applications, and validating security and compliance are manual and time-consuming tasks. A full-stack operational environment allows these critical systems to be up and running much faster and with the safety precautions healthcare organizations require.
Other challenges arise in the retail industry. Running AI-powered customer experience applications across hundreds of locations can lead to configuration drift and operational instability. Repeatable deployment blueprints and automated workflows allow organizations to deploy a consistent environment across all sites.
These are not future scenarios. These are what Quali’s Cisco-compatible solutions for AI and stack automation are built to deliver today.
Enterprise AI enters the operational era
The fastest organizations are not just the ones with the most GPUs. These enable you to reliably deploy, manage, secure, and scale AI across real-world production environments. That is the direction we at Cisco are heading.
And this week on Cisco Live, we’re taking some leaps forward to make that possible.
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