Clam is a Y Combinator-backed (W26) security platform that lets you run OpenClaw AI agents safely. It wraps your agent's environment in a Semantic Firewall, a network-level checkpoint that scans all inbound and outbound messages for personal data leaks, prompt injection attempts, and malicious code. API keys and secrets are injected at the network level so the AI never sees or stores your credentials. Built by former engineers from HappyRobot and Augment Code, Clam is designed for both enterprises and individuals who want the power of autonomous AI agents without the security risks.

• Semantic Firewall: A network-level security checkpoint that monitors everything your AI agent sends and receives, catching threats before they become problems.
• Data Leak Prevention: Automatically scans messages for exposed personal information like SSNs, credit card numbers, and private keys.
• Prompt Injection Detection: Identifies and blocks jailbreak attempts, instruction overrides, and other prompt manipulation tactics targeting your agent.
• Malicious Code Blocking: Detects reverse shells, encoded execution payloads, and other dangerous code patterns in agent communications.
• Credential Isolation: API keys and secrets are injected at the network level, so the AI agent never directly accesses or stores your sensitive credentials.
• Fast Deployment: Set up a secure OpenClaw environment in minutes with easy onboarding and step‑by‑step integration support.
• Network‑Level Security: Protect your AI agent at the network layer so threats are blocked before they reach the agent’s system or data.

• Protection Against Known Agent Security Risks: Clam addresses documented vulnerabilities in OpenClaw-style AI agents, including exposed instances and threats that can leak data or execute unsafe actions.
• Network-Level Protection Layer: By providing security at the network layer rather than inside the agent, Clam creates a boundary that is significantly harder for malicious instructions and leaks to cross.
• Built-in Credential Safety: Keeping API keys and secrets out of the reach of the AI helps prevent the leakage and misuse of sensitive credentials.
• Founders with Relevant AI Security and Tooling Experience: The team includes engineers who previously worked on AI observability and agent systems, providing them with first-hand experience regarding the challenges Clam is designed to solve.
• Y Combinator Backed: Part of the W26 batch, providing credibility and access to the YC network.

• Tied to the OpenClaw ecosystem: Clam is specifically built for OpenClaw agents. If you use a different AI agent framework, it may not be applicable.

• Enterprise OpenClaw Deployment: Your company wants to adopt OpenClaw for internal automation but can't risk credential exposure or data leaks. Clam's Semantic Firewall sits between the agent and your systems, scanning every interaction for sensitive data before it leaves your environment.
• Solo Developer Running a Personal AI Agent: You want an always-on OpenClaw assistant handling tasks across your apps, but you're nervous about giving an AI access to your API keys and accounts. Clam injects credentials at the network level so the agent never stores them.
• Security Teams Managing Shadow AI: Employees are already spinning up OpenClaw instances on company machines. Clam gives your security team a way to wrap those agents in a protective layer that blocks prompt injection, data exfiltration, and malicious code execution.
• Regulated Industries Exploring AI Agents: If you work in finance, healthcare, or legal, you need strong controls before deploying autonomous agents. Clam's scanning for PII leaks (SSNs, credit cards, private keys) helps meet compliance requirements around data protection.
• AI Agent Builders Testing Security: You're building custom OpenClaw skills or integrations and want to test how they behave under security constraints. Clam provides a controlled environment where you can monitor what your agent sends and receives.