Security
Router-level guardrails, sovereignty posture, and compliance evidence. Every prompt and every response passes through us — this is where the wall gets shown.
Data hygiene
What's leaving via prompts and what's coming back.
Scans prompts sent to models for PII (email, phone, SSN, passport, health ID) and redacts before the model sees them.
Scans model responses for PII synthesized or regurgitated by the model and redacts before returning to the user.
Detects and blocks credentials in prompts before they leave the workspace: AWS access keys, GitHub tokens, DB URLs, JWTs, generic API keys.
Customer-defined regex + classifier patterns for sensitive company data (customer lists, compensation, contracts, product roadmaps).
Classifies model responses for policy violations (violence, self-harm, illegal activity) and blocks or logs based on policy.
Attack detection
Prompt injection, jailbreaks, and adversarial patterns — blocked before the model sees them.
Detects user-typed instruction-override patterns ("ignore all previous instructions", role-play jailbreaks, system-prompt extraction).
Detects malicious instructions embedded in retrieved RAG documents (indirect prompt injection via Drive/SharePoint content).
ML classifier for adversarial prompt patterns that don't match a static rule (novel jailbreaks, DAN variants, encoded payloads).
Detects base64, hex, ROT13, and other encoded payloads used to exfiltrate data or smuggle jailbreak prompts past the classifier.
Data placement
Where your data lives, under whose keys, and whether inference runs in a Trusted Execution Environment.
Compliance evidence
Control coverage across the frameworks your regulator asks about.
Recent incidents
Latest security-category events from the audit log.