Validates agent outputs in multi-agent systems to prevent coordination failures, with tools for schema verification, hallucination detection, and freshness checks, all with zero LLM cost.
Fact-checks and fixes AI outputs by catching hallucinations, repairing broken JSON, and correcting errors before they reach users, with tools for verification, validation, and correction.
Protects AI agents from prompt injection attacks, jailbreak attempts, and common web vulnerabilities by screening untrusted input through semantic LLM analysis and static pattern matching.
Runtime governance proxy for MCP tool calls. Inspects tool results for prompt injection and capability abuse before they reach your agent, blocking attacks that exploit the MCP trust boundary.
Protects AI agents from threats like prompt injection, jailbreaks, and SQL injection through a multi-layer scanning pipeline. It also enables PII redaction and rehydration to ensure data privacy during LLM interactions.