Unleash the full power of AI agents through secure workloads, credentials, and computation

Agent Command secures your most sensitive data and systems, enabling powerful AI automation without risks.

The problem

AI agents are being deployed into enterprise environments without proper monitoring and security solutions.

Corporate anxiety about autonomous agents is rising:

Identity sprawl and ungoverned access.

Agents hold credentials and take actions, but most enterprises lack visibility into their agentic workforce, cannot verify AI agent identities, and do not govern access to and permissions in sensitive systems.

Data leakage and prompt injection.

Sensitive data is fed into agent context windows, logs, memory, and third-party models. Malicious prompts or un-audited agentic instructions can hijack agent behavior, leak private data, and widen the attack surfaces for bad actors.

Compliance and audit exposure.

AI agents do not natively log actions, and when prompted for an auditable record, agents can hallucinate. Enterprises are unable to produce audit trails for compliance or to diagnose agentic misbehavior, leading to non-conformance with industry regulations like the EU AI Act and the NIST frameworks.

Agent Command

Monitor every agent. Seal every secret. Audit every action.

Monitor every agent, all programmed permissions, and all protected actions from a single dashboard.

Seal every secret in hardware, so that private credentials, keys, and data are never exposed to AI agents or their model context.

Audit every action on a tamper-proof ledger, cryptographically signed and verifiable by any regulator.

How it works

Secure and monitor every agent, ensured by network consensus

With Terminal 3, data and security teams can:

Issue every agent a verifiable identity.

Identities are cryptographic and portable across enterprise SSO (Okta, Ping, Entra, Google Workspace) and open agent protocols (Google A2A, Anthropic MCP, SPIFFE/SVID, ERC-8004), verifiable without a shared trust anchor.

Set permissions that an agent can never exceed.

Enforced in hardware, beyond the reach of bad actors or a compromised agent; every action is bound to a signed intent.

Hide your organization's secrets from agents.

Credentials, keys, and private data are sealed in hardware, substituted at the boundary, and never exposed to agents or their model context.

Prove and audit what every agent has done.

Every action is logged to a cryptographic Merkle-tree ledger, immutable and independently verifiable, export-ready for examinations and SOC 2 audits.

Connect and watch agents across multiple ecosystems.

Interoperate via APIs or MCP, so you can monitor and secure agents across your technology stack and across multiple ecosystems.

Days, not months, to secure agents handling sensitive workloads

Deploy agentic identities, secrets management, policy enforcement, and audit trails in days. Hardware-attested, SOC 2 and ISO-ready from day one, with SSO and programmable permissions out of the box.

Compliance scope that does not expand with growth

As AI agent deployments grow, your governance overhead stays fixed with programmable permissions and hardware-ensured secrets management.

Evidence for regulators, not just assurances

When regulators or compliance ask what your agents did, when, and under whose authority, the answer is readily available as a verifiable audit trail.

Use cases

Build agents that act within authorized bounds

AI agents can execute real-world tasks on behalf of employees. Every action is bounded by a signed intent, cleared against procurement or compliance policies, and logged to the hardware-locked audit ledger.

Visa applications submitted by an agent on verified intent

The agent fills in forms using secure identity data injected at the boundary, submits the application, and records the full submission into an audit trail.

Policy-bound travel booking from a single signed intent

An employee signs a bounded intent credential (class, destination, budget cap), and the agent books a compliant itinerary, with every decision and action written to an audit trail.

Authorized payroll processing via signed instruction

The agent verifies the requester's identity, enforces processing rules, executes an automation run inside T3 Network, and logs every action.

Corporate purchases cleared against procurement policy

The agent checks each item against hardware-attested procurement policies before checkout, while every purchase is logged to an immutable audit trail.

Security & compliance

Security and compliance, built into the infrastructure

We take security seriously and have implemented robust measures to protect your data.

FAQs

01What's included in Agent Command?

Agent Command is the enterprise AI governance platform that includes: a real-time discovery layer that surfaces every AI agent across your organization (including shadow AI), a policy engine that inspects and enforces data handling rules on every prompt in-flight, TEE-secured data processing that keeps sensitive data inside your compliance boundary, and a cryptographic Merkle-tree audit ledger that is immutable, independently verifiable, and export-ready for regulatory examinations.

02How is Agent Command different from general AI security tools?

Most AI security tools address model-level risks: jailbreaking, prompt injection, and hallucination. Agent Command addresses enterprise governance risks: shadow AI operating outside IT visibility, sensitive data crossing compliance boundaries to third-party models, and the absence of a verifiable audit trail for regulatory examination. It is a governance infrastructure layer.

03How fast can Agent Command be deployed?

The governance plane deploys in days. Agent Command ships pre-hardened with SSO, a policy engine, and SOC 2 and ISO-ready configurations. Discovery begins surfacing your AI agent estate immediately after deployment. There is no per-agent configuration required. Governance is an infrastructure-level property.

04How does prompt filtering work without breaking agent workflows?

Agent Command inspects every prompt against your policy rules and redacts or blocks only the specific data elements that violate policy: PII, secrets, AML flags, and health records. The redacted prompt continues to the model; the agent workflow completes without interruption. The model receives intent without the sensitive data. Policy violations are logged but do not require human intervention unless configured to do so.

05What regulatory frameworks does Agent Command support?

Agent Command's architecture is aligned with MAS AI governance guidelines, GDPR (data minimization and purpose limitation applied at the prompt level), PDPA, SOC 2 Type II (audit trail generation), and ISO 27001. The audit export function generates structured packages suitable for regulatory examination under each of these frameworks.

06Is Agent Command suitable for enterprises outside financial services?

Yes. The shadow AI problem, the need for data policy enforcement on AI prompts, and the requirement for a verifiable audit trail apply to any enterprise deploying AI at scale — healthcare-adjacent businesses, professional services, technology companies, and government agencies. The policy engine and discovery layer are configurable to any regulatory framework or internal data governance standard.

READY TO DEPLOY

Monitor every agent, seal every secret.

Deploy agentic identities, secrets management, policy enforcement, and audit trails in days.