DeClaw is the secure runtime for AI agents that combines sandbox isolation, network controls, AI guardrails and agent audit trail into a single runtime environment. Unlike traditional approaches that require stitching together multiple tools, DeClaw provides an integrated solution where every outbound byte can be configured to be inspected, redacted or blocked, and every agent action is logged.
The platform offers isolated sandboxes per agent session, ensuring that each AI agent operates within its own secure environment. It includes AI guardrails that provide data exfiltration protection and prompt injection defense, preventing sensitive information from silently leaving the agent's environment. The system maintains a full agent audit trail, allowing complete visibility into agent actions and behaviors.
DeClaw addresses the common problem of securing AI agents in production by eliminating the need to duct-tape multiple tools together. Traditional approaches require combining separate sandbox vendors, guardrail solutions and observability tools, creating potential security gaps. DeClaw fuses these capabilities into one runtime, providing comprehensive security without the complexity of managing multiple integrated systems.
The runtime is delivered through a single SDK that developers can integrate into their AI agent deployments. This approach simplifies implementation while ensuring that security controls are built into the foundation of the agent's operating environment rather than added as external layers. The system has achieved the #1 position on the public ComputeSDK sandbox benchmark, demonstrating its effectiveness in providing secure agent execution environments.
DeClaw is designed for production deployments where AI agents need to operate securely while maintaining full observability and control. The platform is particularly relevant for organizations deploying AI agents that handle sensitive data or operate in regulated environments where data protection and audit trails are critical requirements.
Key Features
- •Firecracker Sandboxes: Isolated microVMs with ~40ms startup, configurable CPU/memory/disk, and full Linux environment provide hardware-isolated execution for each AI agent session, ensuring security and performance as a drop-in replacement for existing sandboxes.
- •Persistent Filesystem: Read, write, and watch files inside sandboxes with state persistence across sessions, allowing agents to maintain continuity and pick up where they left off for long-running tasks and data management.
Publisher
A
admin
Launch Date2026-05-09
Platformapi
Pricingfree
Domain Authority
Ahrefs DR11/100