Use Cases
How Superagent protects AI agents from real-world failures.
Stop agents from generating harmful SQL or code mutations
Coding agents can propose insecure SQL, unsafe schema migrations, or destructive code edits. Tests simulate risky prompts and catch these patterns before customers see them.
Stop agents from sending sensitive data into logging pipelines
Even if the core output is filtered, agents can leak PII into logs, error traces, or monitoring dashboards. Guardrails restrict what reaches observability systems.
Stop cross-user data leakage in customer support agents
Support agents that generate Jira tickets or internal records may copy user emails, account IDs, or personal details into third-party systems. Guardrails remove prohibited fields before any action is executed.
Validate that agents do not hallucinate compliance claims
Agents often invent GDPR, HIPAA, or SOC2 statements. Tests catch fabricated policies and misrepresentations that could create regulatory exposure.
Verify incoming emails to prevent phishing-style exploits
If an agent processes email or inbox data, attackers can exploit this as an entry point. Guardrails analyze sender metadata and content patterns to detect phishing attempts.
Your use case title here
A 1-2 sentence summary of the problem and how guardrails solve it.