New platform helps organizations securely adopt AI agents, whether they are bought off the shelf or built in house
Aurascape announced a major expansion of its AI security platform to help organizations securely adopt the next wave of enterprise AI: AI agents.
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As companies rush to deploy AI agents across employee productivity, business applications, and internal workflows, the security challenge is changing fast. Unlike earlier AI tools that mainly generated responses, AI agents can connect to systems, access data, invoke tools, and take action. That creates a new class of risk for security teams, especially as agents spread through both off-the-shelf products and internally built applications.
Aurascape’s expanded platform is designed to solve that problem. The company already helps organizations secure how employees use commercial AI and embedded AI. Now Aurascape is extending that same platform to help organizations securely build, test, and govern AI agents and custom AI applications, giving security teams one control point for both AI use and AI build.
“During the first wave of AI, security was about controlling prompts and protecting sensitive data. That is no longer enough,” said Moinul Khan, CEO of Aurascape. “AI agents can access systems, use tools, and take action on behalf of the business. That changes the security problem completely. Organizations need a way to securely unleash AI agents, whether they buy them or build them. Aurascape gives them one platform to do that.”
At the center of the announcement is Aurascape’s new Zero-Bypass MCP Gateway, designed to address one of the biggest emerging gaps in agent security. As Model Context Protocol (MCP) becomes a standard way for AI agents to connect to tools and enterprise systems, many standalone gateway approaches can only secure the traffic explicitly sent through them. Aurascape combines its MCP Gateway with its AI Proxy to help organizations govern trusted tool use, identify risky MCP-related activity visible to the platform, and reduce bypass risk across agent interactions.
The expanded platform also adds new capabilities for organizations building AI agents and AI applications, including visibility into MCP servers and tool calls, testing before release, production guardrails for live AI interactions, and detection of code and dependency weaknesses surrounding AI systems. Together, these capabilities help security teams see how agentic systems are connected, uncover issues before deployment, and enforce policy once those systems are live.
Aurascape is also expanding the AI use side of its platform with broader AI app coverage, faster discovery, custom app signatures, and local agent discovery. That gives organizations better visibility into the growing mix of commercial AI, embedded AI, and on-device agents already operating across the enterprise.
The result is a single AI security platform designed for both sides of the agent problem: securing the AI agents organizations buy and securing the AI agents organizations build. Instead of stitching together separate tools for AI usage control, gateway enforcement, testing, and runtime protection, security teams can apply one platform across the full AI environment.
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