Upwind Brings Realtime Intelligence to Cisco Cloud Control

Jun 02, 2026

We are thrilled to announce that Upwind has been selected as a launch partner for Cloud Control Studio, part of Cisco Cloud Control, bringing realtime intelligence on cloud and AI security into the platform. Unveiled at Cisco Live Las Vegas on June 2, 2026, Cisco Cloud Control is the unified platform for agentic IT operations.

Upwind is integrated with Cloud Control Studio via Model Context Protocol (MCP), enabling customers to access Upwind’s cross-platform skills and get realtime intelligence, including security findings, vulnerability data, API security telemetry, and AI visibility, within the Cisco AI Canvas.

(Learn more about the Upwind MCP Server in our announcement blog post)

The Challenge Facing Modern Security Teams

Modern cloud security teams don’t struggle to find vulnerabilities. They struggle to prioritize and close them fast enough.

AI has accelerated the pace of attacks, shrinking the time between exposure and exploitation. Security teams are buried in alerts, most of which point to theoretical risks that are dormant, unreachable, or low priority in practice. Meanwhile, the findings that actually matter, the ones tied to code that is actively running, services that are publicly reachable, and identities that are overprivileged and in use, get lost in the noise.

AI is also reshaping the attack surface itself. As organizations adopt AI-powered applications and agentic workflows, new risks emerge across visibility, runtime behavior, and model-to-model communication that traditional security tools were never built to handle. The challenge is no longer just identifying issues. It is understanding which ones actually matter, and resolving them safely before attackers move.

Where Upwind Fits

Upwind delivers deep runtime visibility across cloud and AI environments, continuously monitoring workloads, identities, APIs, and runtime behavior in production. Instead of overwhelming teams with theoretical findings, Upwind surfaces high-confidence risks that are actually exposed, reachable, and exploitable, enriched with realtime intelligence, remediation guidance, and the operational data teams need to act.

That capability extends across the full AI stack. As AI models, agents, and agentic workflows become core infrastructure, the attack surface expands in ways that static tools and posture scanning alone cannot address. Upwind is purpose-built to secure it, organized around improving visibility, reducing risk, and providing context at runtime.

AI agents are only as good as the data they can reason on. When that data includes realtime context about what is actually running, what is reachable, and what is actively under threat, investigations produce better answers and resolutions happen faster. That is what Upwind brings to Cisco Cloud Control.

How the Integration Works

Upwind connects to Cloud Control Studio, part of Cisco Cloud Control, using Model Context Protocol (MCP). Joint customers can use Upwind’s findings and telemetry inside Cisco AI Canvas, the multiplayer workspace inside Cisco Cloud Control where IT teams and AI agents can investigate, correlate, and resolve issues.

When an operator opens an investigation in Cisco AI Canvas, the AI agents working in that session can reason on Upwind’s context alongside everything else in the environment. No manual exports, no switching tools. The context is already there.

Why Runtime Context Changes the Investigation

Most security investigations stall not because teams lack alerts, but because they lack signal. Static snapshots tell you what exists. Runtime context tells you what’s happening — what code is executing, what processes are communicating, what APIs are live, and what threats are active right now.

Upwind is built inside-out, starting with runtime context that provides continuous, real-time visibility into workloads. That depth is what makes Upwind’s findings useful not just in our own platform, but as an input to broader agentic operations workflows.

When AI agents in Cisco AI Canvas can ground their reasoning in runtime-verified data, they produce better answers. Teams stop jumping between tools to reconstruct what happened. The investigation happens in one place, with the context that matters most already there.

What This Integration Enables

AI agents are only as effective as the context they can reason on.

By connecting Upwind to Cloud Control Studio, through MCP, AI agents working in Cisco AI Canvas gain access to authoritative runtime cloud and AI security intelligence — not just static findings.

That means investigations can reason on what is actually happening in production:

Runtime threat detections from live workloads, identities, APIs, and cloud infrastructure.
Vulnerabilities prioritized by real runtime exposure, exploitability, and workload relevance.
API security intelligence including discovered endpoints, authentication gaps, anomalous behavior, and runtime-correlated risks.
AI workload and MCP visibility, including agent communication paths, model usage, and suspicious interactions.
Cloud posture, identity risk, container behavior, and runtime attack signals across the environment.

This fundamentally changes the quality of investigation.

Instead of treating every alert as a theoretical problem, AI agents can distinguish between static exposure and active operational risk, helping teams focus on what is actually reachable, exploitable, and worth acting on.

For joint customers, this means faster investigations, better decisions, and quicker resolution with far less manual context switching.

Example prompts customers can use

Security teams can ask:

“Show me the top critical vulnerabilities currently running in production, ranked by runtime exposure, exploitability, and available remediation.”
“Which production workloads have the highest concentration of exploitable runtime risk?”
“List internet-facing API endpoints with weak or missing authentication and correlate them with runtime activity.”
“Show AI workloads communicating over MCP with anomalous or unexpected behavior.”
“Which identity-driven runtime events represent the highest active security risk right now?”

(Check out the Top 10 MCP Use Cases for Upwind in our recent blog)

What Security and IT Teams can Expect

As part of Cisco Cloud Control, Upwind’s realtime intelligence becomes a native part of how AI agents investigate and resolve issues.

AI agents investigate with more context. Upwind’s realtime intelligence is part of what agents reason on inside Cisco AI Canvas, alongside networking, observability, identity, and compute signals.
Less context-switching. Security findings surface directly in the workspace where the rest of the investigation is already happening.
Faster, more accurate resolution. When agents can correlate a security alert with live runtime behavior, root cause analysis that once required multiple tools and manual correlation can happen in a single session.

Upwind in the Cisco Cloud Control Platform

Upwind’s integration with Cloud Control Studio reflects a broader belief: that cloud security context belongs wherever security and IT teams are doing their work. We are proud to be part of the Cisco Cloud Control ecosystem, and to share a vision with Cisco that the future of security operations is agentic, and that it only works when AI agents have access to the runtime data that tells them what is actually happening. As organizations build and expand agentic operations on Cisco Cloud Control, runtime cloud security is a foundational input, not an afterthought.

Cisco Cloud Control is built to bring every operational domain into one environment. Upwind extends that environment with the runtime security layer it needs: continuous visibility into cloud workloads, applications, APIs, and AI agents, all correlated in realtime. Security and IT teams get a more complete picture of their environment and the context to act on it with confidence.

For more information on Cisco Cloud Control, visit the new Cloud Control Studio webpage.

If you’d like to explore how Upwind can help you prioritize and remediate risk more effectively, schedule a customized demo with us. We’ll walk through your use cases, integrations, and security goals to show how Upwind delivers actionable cloud security at scale.