The AI Observability Challenge

Traditional APM tools monitor system health but remain blind to the "Intent Layer". AIxSafe fills this gap by capturing the semantic content of every model transaction.

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Opaque Interactions

Standard logs show an HTTP 200 OK even if a model generates incorrect financial advice or hallucinations.

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Token Fragmentation

Cost and usage data is often disconnected from the security context, making efficiency audits impossible.

Evidence Streams Captured

  • Prompt Context: The exact instructions provided to the model.
  • Model Outputs: The unfiltered response generated by the LLM.
  • Policy Outcomes: Records of redaction, blocking or routing decisions.

Transitioning from Logs to Evidence

For organizations operating under frameworks like CPS 230, raw logs are insufficient. They must be transformed into actionable evidence.

Deterministic Auditing

AI telemetry turns unpredictable generative systems back into deterministic software processes. By correlating interactions with user identities and risk policies, security teams can trace actions directly back to specific session parameters.

Compliance FAQ

Immutable Records

Decision telemetry is hashed and stored in tamper-evident formats to satisfy regulatory requirements for operational evidence.

Governance Protocol

Real-time Alerting

Telemetry feeds directly into internal SIEM/SOAR platforms for immediate response to policy violations.

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