Gluware has launched Gluware Labs, a groundbreaking Intelligent Network Automation Builder Program that enhances engineering productivity. Explore its features!

Gluware has appointed Alex Henthorn-Iwane, a seasoned marketing executive, as Senior VP to enhance brand awareness and drive demand for its network automation solutions.

The integration will provide customers with Gluware’s automation capabilities and NetBox’s network data modeling.

Anthropic’s Claude Mythos Preview, released earlier this year, showed that AI systems could identify and probe network vulnerabilities at a speed that traditional patch management cycles were not designed to match. Security teams that had operated on 30-to-90-day remediation windows began reassessing that assumption. That’s the challenge that network automation vendor Gluware is taking on. This week the company announced Titan Exposure Management, a closed-loop agentic capability that determines which devices on a network are actually exposed to a given vulnerability and automates remediation. The announcement extends the Titan platform that Gluware first announced in late 2025 as a framework for coordinating multiple AI agents safely on enterprise networks. Titan is built on Gluware’s proprietary Device Interface and Automation Layer (DIAL), focused on preventing conflicting changes from simultaneous agent actions. Titan Exposure Management applies the same foundation to a more pressing problem. “What we wanted to make sure and get out was a use case, a solution that is critically important for all customers that need to be able to respond, especially in a new Mythos, or other AI, attack-driven world, Jeff Gray, Gluware CEO and co-founder, told _Network World_. ## The vulnerability visibility gap The Mythos release focused attention on a problem that’s familiar to network teams. When a vulnerability surfaces, determining actual device exposure across a large enterprise network is a slow, manual process. A team running 10,000 devices on an affected OS must go device by device to determine whether the specific feature is enabled, actively configured, and in production use. Plugging an LLM into that problem does not solve it. Gray argues that while an LLM might understand what a particular vulnerability is, it will not understand how relevant it is to an organization’s network. The consequence is that many CVEs go unremediated. CVEs (Common Vulnerabilities and Exposures) are identified vulnerabilities that have been publicly disclosed. The CVE framework also does not account for vulnerabilities detected directly by AI models, which may never appear in any advisory or bulletin. “Every model is just going to get smarter. This is not a one-time thing. This is constant,” Gray said. “The only way to be able to respond and hope to be one step ahead, if that’s possible, is to be able to have the capability of a machine response.” ## How Titan Exposure Management works Titan Exposure Management is built on Gluware’s DIAL, which maintains a continuously updated model of network state across the entire fleet. * **Network intent, not configuration snapshots.** DIAL performs continuous discovery of device configurations, operating states, and feature-level network intent across 56+ operating systems from 22 vendors, including legacy environments with years of pre-automation history. * **Feature-level CVE scoring.** When a CVE or model-detected vulnerability is received, Titan Exposure Management maps it against vendor and OS-specific feature data to produce a per-device exposure score rather than a blanket OS-version match. * **External threat intelligence.** The platform integrates EPSS (Exploit Prediction Scoring System) and KEV (Known Exploited Vulnerabilities) data to weight scores against real-world exploitation activity, producing a ranked view of actual fleet exposure. * **Compensating controls.** Where patching cannot happen immediately, Titan Exposure Management can deploy ACL changes or network segmentation to reduce the attack surface and buy time. Pre-checks and post-checks are applied through the same DIAL layer at every step. * **Coordinated patching.** For high-availability environments, the platform understands HA topology and sequences patches so one device fails over while its peer is updated. “Patching is the answer, and just being able to do it according to what the business needs and in a safe and predictable manner is key, and that’s not going out and doing it manually. That’s part of the machine response,” Gray said. ## OpenClaw and the road ahead Gluware is positioning Titan Exposure Management as one component in a broader platform direction. Frameworks such as OpenShell, NemoClaw, and OpenClaw are expanding the number of agents that can initiate network changes, and not all of those agents will originate within the network team. Gluware’s MCP server architecture, introduced with the original Titan launch, is designed to serve as the coordination layer for that ecosystem. Third-party agents submit change requests through the MCP interface, and Gluware’s validation engine determines whether those changes are safe to execute before anything touches the network. “There’s going to be more agents, more vibe coding, that’s out there. How do you get all of this to be able to work together?” Gray said. “There’s got to be a layer that is the arbiter of anything that agents want to do, that developers are going to create.”

When Jeff Gray and his co-founders showed their first network automation prototype to a major network equipment manufacturer over a decade ago, the response was dismissive. The vendor questioned why anyone would want a system that constantly modified network configurations, calling it something that would get “really really busy.” The prevailing wisdom held that networks should be set-it-and-forget-it, with changes avoided to prevent cascading outages. The modern networking landscape sees things very differently. The threat landscape has fundamentally altered the industry’s approach to network changes. Nation-state actors, vulnerability exploits and evolving attack vectors now force enterprises to constantly patch, remediate and tune their networks. Gray’s company was founded as Glue Networks and later evolved into Gluware. The company began with Cisco-only WAN automation before expanding into multi-vendor networking support that progressed from human-approved remediation to fully automated self-operating networks. Early customers required manual approval for each automated change. Today’s deployments automatically remediate configuration drift the moment it’s detected. With the rise of AI, the industry now faces a new challenge: coordinating multiple AI agents that want to make simultaneous network modifications. Observability platforms, service management tools and security systems are all deploying their own AI agents. Without an arbiter, conflicting changes could trigger the very cascading outages that made network teams cautious about automation in the first place. Gluware is addressing this coordination problem with the launch of Titan. “If all these companies are building their own agents, which agent is in charge?” Gray told _Network World_. “What we’re saying is that with Titan, it’s a validated framework. You’re able to fully abstract the network and trust it with Gluware and DIAL technology, and we can be the arbiter of what is safe and predictable.” ## From configuration management to AI agent coordination Gluware’s automation capabilities evolved through three distinct operational phases that built the foundation for Titan’s multi-agent coordination. The first phase focused on configuration management and drift detection. Gluware’s system identified when network devices deviated from approved configurations and proposed fixes, but network operations teams manually reviewed and approved each remediation. The second phase introduced automatic remediation. As customers gained confidence, they allowed the system to automatically correct devices that drifted from approved standards without human approval for each action. Current deployments represent what the industry calls self-operating networks, where configuration drift triggers instant automated correction. Titan represents the third phase: system-determined operations where AI identifies new changes needed and executes them within defined risk parameters. This differs fundamentally from drift remediation, which restores known-good states. Titan handles new modifications from multiple AI systems that may conflict with each other. The platform coordinates between observability platforms, service management tools and security systems, each deploying AI agents that want to make simultaneous network changes. The validation framework extends from preventing configuration drift to preventing conflicts between competing AI agents. ## Titan’s architecture for network and agentic AI coordination Titan consists of a series of integrated components working together to solve the multi-agent coordination problem. The Intelligent MCP Server uses the Model Context Protocol to coordinate between Gluware’s automation capabilities and external AI agents. The Gluware Agent executes the actual automation work between the MCP server and network devices. The Co-Pilot provides a natural language interface for network operations teams. The MCP Server implements what Gluware calls a validation engine. Every action passes through verification before execution. This architecture allows third-party agents from observability platforms or service management tools to request network changes while Gluware maintains control over execution. Initial MCP service integrations include NetBox and ServiceNow. ## Validated automation built on DIAL foundation At the foundation of the automation is Gluware’s Device Interaction Automation Layer (DIAL), representing over one million developer hours across more than 300 releases. DIAL enables bidirectional communication with physical and virtual network devices across vendors and platforms, handling device-level complexity at scale. The validation framework builds on the trust Gluware established through a decade of customer deployments. The same logic that convinced network teams to move from human-approved changes to automatic remediation now extends to coordinating multiple AI agents. Each proposed change passes through verification before execution, regardless of which AI system initiated the request. “DIAL is underneath, Titan is on top, and then it’s a trusted framework for other third-party MCP servers to plug into,” Gray said.

Gluware is expanding its AI platform with Titan Exposure Management, an agentic capability that maps live network device configurations directly to CVE advisories. Titan is built to slay Mythos — and ...

Gluware has launched Titan Exposure Management, an advanced capability for network security that dramatically improves vulnerability detection and remediation processes.

Gluware, a leader in intelligent network automation, has won two Gold Stevie Awards at the American Business Awards 2026, recognizing its innovative technology.

Gluware emerged as a leader in intelligent network automation, earning top honors for its groundbreaking automation product at the 2026 SiliconANGLE CUBEd Awards.

Gluware has been honored as a finalist in two crucial categories of SiliconANGLE Media's Tech Innovation CUBEd Awards for 2026, emphasizing their innovative approach in network automation.

Vandis Inc has teamed up with Gluware, enhancing network automation practices. This partnership promises better security and operational efficiency for clients.

Gluware partners with Vandis to transform network automation, enhancing operational efficiency and compliance in complex environments.

Gluware has unveiled Titan, a groundbreaking agentic AI platform for enterprise networking, ensuring secure and reliable operations at scale.

Gluware has appointed John Donelan as their Chief Revenue Officer, aiming to enhance sales and strategic partnerships as they scale.

Gluware has secured the Silver Globee® Business Award for its innovative enterprise network automation solutions, revolutionizing multi-vendor integrations securely and effectively.

Gluware announces the launch of Gluware 5.6, introducing advanced features aimed at revolutionizing network automation and enhancing operational efficiency for businesses.

Gluware has announced its collaboration with Red Hat, introducing an Ansible Certified Content Collection designed for fast and intelligent network automation across varied infrastructures.

Gluware showcases its latest Network Automation Without Limits campaign at AutoCon 3, featuring new tools, workshops, and case studies dedicated to empowering network automation builders.

The recent launch of Gluware 5.5 introduces vital integrations and features, streamlining enterprise network automation and enhancing operational efficiency.

Gluware has made its NetBox integration available, streamlining network automation solutions for engineers while enhancing operational efficiency.

Julie Keith of Gluware has received the APPEALIE 2024 SaaS Customer Success Leader Award, recognizing her commitment to customer support and success.

Gluware has secured a significant investment from Cuadrilla Capital, aiming to enhance network transformation and extend its global market presence.

Explore Cuadrilla Capital's acquisition of Gluware, a pioneering network automation firm, marking a significant step in enterprise technology advancements.

Gluware was awarded the top honor in network automation at the inaugural BENNY Awards, showcasing its innovative solutions for enterprise networks.