Operant AI has released Agent Protector, the first comprehensive security solution designed specifically for the agentic AI era.
Agent Protector delivers complete visibility into both managed and unmanaged agents, real-time threat detection with inline blocking, and zero-trust enforcement purpose-built for autonomous AI systems.
The launch comes at a time when AI agent adoption is accelerating far beyond the capabilities of existing security frameworks. While AI agents are enabling significant productivity gains and automation, they are simultaneously introducing complex challenges around visibility, governance and control — areas where traditional security approaches often fall short.
According to Gartner, by the end of 2026, an estimated 40 per cent of enterprise applications will integrate task-specific AI agents, up from less than 5 per cent today. As these deployments scale, organizations require more advanced security tools to maintain visibility and control over autonomous systems operating across their infrastructure. The central challenge for enterprises lies in establishing governance that mitigates risk without limiting the transformation and productivity AI can unlock.
“Agentic AI is forcing financial services to redraw trust boundaries — perimeter-first security breaks down when autonomous agents can traverse apps, APIs, and data stores without a human in the loop. Operant’s real-time protection across the full agent toolchain — from MCP clients and endpoints to live, interactive agentic applications — lets technology leaders move fast without compromising customer privacy, making it a foundational control, rather than an afterthought,” said Suhel Khan, Industry Veteran Head of Cybersecurity, Chargebee.
One of the core capabilities of Agent Protector is real-time rogue agent intent detection with inline protection. The platform identifies and blocks advanced threats in real time by analyzing agent risk profiles, trust levels and behavior patterns. It detects anomalous tool usage, blocks unauthorized privilege escalation and identifies signals of persistence or data exfiltration before execution. Inline detection mechanisms also flag over-permissioned and over-scoped agent activities that could enable lateral movement, while zero-click attacks, including shadow escape attempts, are blocked before they breach designated security boundaries.
“AI agents are proliferating across enterprises faster than security teams can track them. From cloud-based agents to SaaS environments and custom implementations, organizations face an explosion of autonomous systems with access to sensitive data and critical tools. Agent Protector gives security teams the real-time visibility and inline control they need to safely enable AI innovation.” ,” said Vrajesh Bhavsar, Co-founder and CEO of Operant AI,” said Vrajesh Bhavsar, Co-founder and CEO of Operant AI.
Beyond detection and prevention, the platform enables discovery of shadow agents and identities, mapping unmanaged agents across cloud and SaaS environments, development tools and previously invisible MCP servers and dependencies. It builds comprehensive catalogs of user and service account agentic identities, providing complete visibility across the organization’s infrastructure.
For enterprises developing custom agents, Agent Protector integrates with leading agent platforms including LangGraph, CrewAI, n8n and ChatGPT Agents SDK. The solution automatically discovers agents, tools, models, context usage and memory patterns, while offering runtime security scanning and embeddable security primitives designed to make agents secure by design.
The product also introduces cloud-native observability and monitoring capabilities, delivering real-time tracing from prompts to tools and memory stores. It continuously analyzes agent intent and behavior, generates execution telemetry with detailed activity timelines and produces tool activity graphs that map dependencies across the agent ecosystem. Observability data is captured and analyzed in real time, enabling immediate threat detection and response.
Agent Protector further implements zero trust enforcement tailored to each agent and identity, ensuring least-permissioned access with continuous runtime re-authorization based on intent, behavior and context. Inline prompt security guardrails, real-time data loss prevention and protection against memory and context poisoning are embedded within sandboxed environments. Intelligent rate-limiting and inline enforcement mechanisms prevent malicious actions before they can impact enterprise systems.
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