Use Cases
How Superagent protects AI agents from real-world failures.
Ensure internal agents don't expose roadmap, credentials, or HR data
Enterprise assistants often have access to Notion, Jira, Drive, or SharePoint. Guardrails prevent spillover of internal information into conversations or outputs.
Ensure no PII is stored in vector databases or embeddings
RAG pipelines often accidentally store names, phone numbers, or identifiers in vectors. Guardrails run pre-embedding PII scanning and enforce safe ingestion.
Ensure PII is not sent to model providers in violation of GDPR
Teams often rely on ZDR but still send raw PII into the LLM. Guardrails filter personal data before it goes to the model, addressing the gaps ZDR does not cover.
Prevent API key leakage in coding agents
Agents can accidentally include API keys or secrets in generated output or commit them into repos. Guardrails catch and block these disclosures before they leave the system.
Redact PII or PHI from ingested PDFs before processing
Documents can contain personal or sensitive data. Guardrails detect and remove PII or PHI before the model reads or uses the file, ensuring GDPR-safe ingestion.
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.