OpenClaw is the first supported release. Claude Cowork is next.
TrustClaw does not require Swif MDM to get started. For company devices, Swif MDM is required for bulk deployment and management
TrustClaw is Swif.ai’s security layer for AI agents. It helps teams monitor agent behavior, capture structured audit trails, and apply controls before risky actions happen.
Starting with OpenClaw, TrustClaw uses memory context for audit trail ingestion and logging, while also capturing tool activity, sessions, and execution context in a clear timeline. It gives teams a reliable way to understand what the agent saw, what it tried to do, and what actually happened.
Why it matters: once agents can take action, the risk is no longer just bad answers. It becomes unauthorized reads, writes, edits, and command execution. TrustClaw is built to reduce exposure to two major classes of agent risk: behavioral control traps that push an agent toward attacker goals, and systemic traps that create larger failures across multi-agent workflows.
Ingest memory context, session activity, tool usage, and execution context from agent runs. Turn raw behavior into a searchable audit trail.
Control actions at the tool layer. Because OpenClaw operations break down into tools like read, write, edit, and exec, TrustClaw lets you allow safe actions, deny risky ones, or require approval for sensitive commands.
Normalize activity inside Swif so teams can review events, investigate incidents, tune controls, and export structured logs into SIEM and analytics workflows.
Prevent unsafe behavior before it executes by blocking high-risk tools, restricting dangerous capabilities, or requiring approval for sensitive actions.
Capture what the agent saw, which tools it used, what it attempted, what was approved, and what happened next in one structured timeline.
Give IT and security teams searchable evidence for incident response, control validation, and compliance reviews without relying on fragmented logs.
TrustClaw integrates with AI agent frameworks like OpenClaw to capture security-relevant activity where actions actually happen. Activity is structured inside Swif as a clear timeline for review and investigation, then exported to SIEM and analysis workflows to support existing security operations.
TrustClaw does not replace your SIEM. It makes AI agent activity visible, enforceable, and understandable, then feeds that intelligence into the rest of your security stack.
TrustClaw also does not require Swif MDM. For company devices, Swif MDM is used for bulk deployment and management.
AI agent security monitoring tracks how an agent behaves across context, tools, approvals, and actions so teams can understand risk, investigate issues, and maintain visibility.
Yes. TrustClaw can block specific tool actions, deny high-risk capabilities like exec, or require approval before an action runs.
TrustClaw captures memory context, session activity, tool usage, execution context, approval events, and action outcomes in a structured timeline.
TrustClaw works at the tool level. That means teams can allow tools like read, write, and edit, while denying exec entirely or setting tighter approval rules around it.
Teams can allow exec while requiring approval for every command. In that setup, the agent can request command execution, but nothing runs until a user approves it.
Yes. OpenClaw is the first supported release. TrustClaw is designed to monitor and control OpenClaw-based agents using native tool permissions and approval flows.
No. TrustClaw can be used without Swif MDM. For company devices, Swif MDM is required for bulk deployment and centralized management.
TrustClaw is built to reduce exposure to behavioral control traps that steer agents into harmful actions and systemic traps that create broader failures across multiple agents or workflows.
Monitor activity, enforce tool-level controls, and maintain a complete audit trail with TrustClaw.
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