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Compliance 2 min read

AI Compliance: SOC2 and GDPR for LLM Applications

What SOC2 and GDPR mean for AI applications, and how to build compliance into your AI stack from day one.

Elliot Nordin Building SignalVault · Stockholm
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As AI features move from prototypes to production, compliance teams are asking hard questions: What data is being sent to AI providers? Is it logged? Can we audit it?

SOC2 and AI

SOC2 requires that you demonstrate controls over data processing. For AI applications, this means:

  • Logging: Every AI interaction must be recorded
  • Access controls: Who can see the logs?
  • Data classification: Is PII being sent to AI providers?
  • Retention policies: How long are logs kept?
  • Encryption: Are logs encrypted at rest?

GDPR considerations

Under GDPR, sending personal data to AI providers (especially those based in the US) requires:

  • Lawful basis: Do you have consent or legitimate interest?
  • Data minimization: Are you sending only what's necessary?
  • Right to erasure: Can you delete a user's AI interaction history?
  • Data processing agreements: Does your AI provider have a DPA?

Building compliance in

Instead of retrofitting compliance, build it into your AI stack from the start:

  1. Log everything — encrypted audit trails for every AI interaction
  2. Detect PII — block or redact personal data before it leaves your infrastructure
  3. Set retention policies — automatically delete old logs based on your plan
  4. Export on demand — provide compliance teams with CSV/JSON exports

SignalVault handles all of these out of the box. The encrypted audit trail, PII detection, retention policies, and export features are designed specifically for compliance use cases.

See this on your own traffic

SignalVault sits in front of your OpenAI or Anthropic client with a one-line URL change and writes the trace — tool calls, guardrail decisions and redactions included.

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