Identity management, RBAC, and threat detection for your AI fleet. Powered by the AgentControlLayer platform, we protect your core from prompt injection and data exfiltration.
Integrates with your security stack
Purpose-built security infrastructure for autonomous AI. Identity, access control, and threat detection—all in one platform.
Every agent gets a cryptographic identity. Know exactly who did what, with unforgeable attribution across your entire fleet.
Fine-grained RBAC for agents. Control which tools, APIs, and data each agent can access—with least privilege by default.
Detect prompt injection, jailbreaks, and data exfiltration in real-time. Stop attacks before they succeed.
Traditional security tools weren't built for AI. Agents create new attack surfaces that require purpose-built defenses.
Most agents run with shared credentials or environment variables. When something goes wrong, you can't trace it back to the source.
Agents typically get access to everything the developer has. That's not least privilege—that's a breach waiting to happen.
Prompt injection, jailbreaks, and data exfiltration are real threats. Traditional security tools don't see them coming.
Stay ahead of the threat landscape with our deep dives into agent security.
Security isn't a feature—it's a foundation. We partner with you to keep your agents protected.
We analyze your current workflows and identify the highest-ROI opportunities for agentic automation.
Our architects build your agents on the AgentControlLayer platform, ensuring security and scalability.
We deploy to production and train your team on how to manage the Human-in-the-Loop approval flows.
We stay on as your AgentOps partner, reviewing logs and optimizing prompts weekly to prevent drift.
We focus on teams who already ship or operate agents and now need a proper AgentOps control plane.
Product and platform teams adding agents into their SaaS products—support bots, onboarding agents, lead routing, and other embedded workflows.
Central teams that support multiple agent use cases across the business and need one place to control prompts, policies, and observability.
Shops that build agents and workflows for clients and want to offer them as reliable, audited services instead of one-off scripts.
Under the hood, AgentControlLayer is a full AgentOps control plane: a workflow engine, agent identity system, and observability layer that treat agents as first-class principals.
A LangGraph-powered workflow engine with schema-based IO, support for multi-agent patterns, and built-in Human-in-the-Loop nodes so you can pause, review, and resume critical steps.
Agents are treated as their own principals with permissions, histories, and versions—not just prompts in code. This aligns with emerging best practices from Google/Kaggle and others.
Designed to support Promptsmith-style atomic prompt boxes and AI-assisted reviews of prompts and workflows so you can continuously improve quality without losing control.
Traditional security treats agents as extensions of user sessions or service accounts. Agent-as-Principal is different—it treats each agent as its own security principal with unique identity, explicit permissions, and complete accountability.
Every agent gets a cryptographically verifiable identity. No more shared API keys or ambient credentials.
Agents only get the permissions they need for their specific task. Permissions are enforced at runtime.
Every action is logged to the specific agent that took it. Audit trails that actually mean something.
Common questions about zero-trust security for AI agents.
Agent identity means each agent has a unique, cryptographically verifiable credential—like a service account, but for AI. This enables attribution (know who did what), access control (enforce least privilege), and audit (prove compliance).
Define roles (researcher, writer, admin) with specific permissions (allowed tools, data scopes, action limits). Assign roles to agents. Permissions are enforced at runtime—agents can't exceed their granted access.
We detect prompt injection attempts, jailbreak patterns, PII in outputs, unusual tool usage patterns, and behavioral anomalies that suggest compromise or drift. Alerts integrate with your existing SIEM/SOAR.
Yes. AgentSecurityPlatform federates with Okta, Azure AD, and AWS IAM. Agent identities can be managed alongside human identities in your existing identity provider.
One AgentOps control plane to build, secure, and observe your agent fleet.
Stop pasting strings into code. Our visual Prompt Builder UI allows you to design, test, and version complex prompts with variables, conditional logic, and model comparisons side-by-side.
Treat agents as first-class citizens with their own IAM roles. Manage permissions, enforce budget limits, and maintain complete audit trails of every decision your AI makes.
Bring DevOps discipline to LLMs. Version control your entire agent configuration—workflows, prompts, and RAG settings. Implement Human-in-the-Loop (HITL) checkpoints before critical actions.
Ready to deploy agents that actually work? We are accepting a limited number of enterprise clients for our Managed Agent Program. Get a custom roadmap, a dedicated AI Architect, and access to the AgentControlLayer platform.