Operant AI, a leading startup in AI security, today announced the launch of Operant Semantic Firewall, the first product that understands an AI agent's intent in real-time and enforces it inline. Modern AI agents take sensitive actions inside enterprise systems, including running code, modifying records, calling external tools, and moving sensitive data. When an agent is compromised or pursues its goal down a path no one authorized, static and pattern-based defenses can't catch it.
Operant Semantic Firewall detects the actual intent behind every prompt, tool call, command, and data movement in real-time and returns an allow, block, or redact decision as the agent acts, giving enterprises their first enforceable real-time control over the entire agent loop.
In today's probabilistic agentic world, there is no known bad pattern to match against an action that has never existed before, leaving signature and pattern-based controls unable to secure live agents as they operate. The Operant Semantic Firewall addresses this by understanding intent across four dimensions of agent activity, unified under a single control plane and enforced inline.
Tool Intent Guard reads the real-world impact of every tool call and blocks data exfiltration, bulk data dumps, credential access, and unauthorized sharing, even when the request itself looks routine. Code Intent Guard distinguishes ordinary code from malicious execution, injection, shell breakout, privilege escalation, and hidden directives across everything a coding agent does. Data Intent Guard classifies files and data as confidential or business-sensitive using built-in classifiers and integrations with enterprise data-governance tools such as Microsoft Purview. Scope Guard holds an agent to the purpose it was given, whether it strays by manipulation or on its own initiative.
Policies in natural language allow administrators to express scope and restrictions the way they already describe risk, and the firewall enforces that intent on every turn with a clear explanation.
Enterprises already insist on sovereignty over their data, and agentic AI extends that requirement from data to decisions. Sovereign AI means the enterprise, not its model provider, decides what its agents are permitted to do and enforces that decision inside its own perimeter.
Operant Semantic Firewall makes that boundary operational in three ways. It runs where you run, with every decision made inside the enterprise's own environment, including VPC, on-premises, and air-gapped deployments. It reaches its own verdicts using Operant's own models, without routing decisions to an external frontier provider. It survives a model change because enforcement sits above the model and works across frameworks.
For teams operating under data residency requirements, the EU AI Act, Singapore MAS framework, or other sector regulators in financial services and healthcare, that means AI governance that can be evidenced to an auditor.
Because one consistent understanding spans user prompts, model responses, commands, tool calls, and data movement at inline speed, an action that gets past one stage is caught at the next, whether it originated in an attacker's manipulation or the agent's own reasoning. A jailbreak slipped into context mid-session or an agent improvising beyond its task both fail the instant the agent tries to run code or move data.
"Watching agents and filtering keywords were fine for early experiments. Enterprises putting agents into revenue, customer data, and production systems need a layer that understands intent and enforces it in real time," said Vrajesh Bhavsar, CEO and co-founder of Operant AI. "This year showed that agents don't only go off course because someone pushed them — they do it on their own, chasing a goal down whatever path they can find. Semantic Firewall understands the intent behind every agent action and enforces your policy inline, inside your perimeter, no matter whose model is running underneath."
Alongside Operant Semantic Firewall, Operant AI is shipping several major updates to its AI Defense Platform. Live Browser AI Protection reads the conversation itself in real-time, allowing, sanitizing, or blocking sensitive content inline on ChatGPT, Claude, Copilot, and Gemini. Broader Claude coverage now includes Claude Cowork cloud-mode sessions and the rest of the Claude family via inference-hook integration. Operant Token Meter provides near-real-time metrics by user, team, agent, and model, plus budget limits enforced mid-session across deployments including Bedrock, Vertex, and Foundry.
All capabilities are available today as part of Operant AI's AI Defense Platform, empowering enterprises to scale business-critical, production-grade AI faster and safer.
About Operant AI
Operant AI is the industry's most comprehensive real-time security platform for AI, Agents, and MCP — the only vendor listed across six of Gartner's key AI and MCP security reports in the last year. Founded by veterans of Apple, VMware, and Google, and backed by Felicis and SineWave Ventures, Operant delivers the only inline, runtime AI defense platform that discovers, detects, and defends the full spectrum of AI workloads — from endpoints to cloud, across LLMs, APIs, orchestration layers, MCP servers, tool integrations, and autonomous AI agents. At its core, the Operant Semantic Firewall enforces every agent's intent, scope, and behavior in the loop — securing prompts, interactions, agents, and all data-in-use as it flows through live application stacks at agentic speed, while keeping the trust boundary inside the enterprise's own perimeter to enable sovereign AI. Together, these capabilities empower enterprises to scale business-critical, production-grade AI faster and safer.
