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Trust Center

Security at KnownBase

Your team's conversations are sensitive. Here's exactly how we protect them.

How we handle your data

🔒 Zero-Retention LLM Processing

Messages are processed in-memory by LLM APIs (Anthropic, Google) with zero data retention agreements. Your data is never stored by AI providers and never used for model training.

🏠 Workspace Isolation

Each workspace gets an isolated data partition. Data from Company A can never be accessed by Company B. Neo4j graph, S3 storage, and vector indexes are namespace-separated.

🔐 Encryption

AES-256 encryption at rest. TLS 1.3 for all data in transit. API keys and tokens stored in AWS Secrets Manager, never in code or environment files.

👁️ Permission-Aware Memory

KnownBase respects your Slack/Teams channel permissions. If a user can't see a channel, KnownBase won't use that channel's data when answering their questions.

What we explicitly do NOT do

  • Train AI models on your data — ever
  • Read DMs or private channels you haven't approved
  • Share data between workspaces
  • Track individual employee productivity or behavior
  • Detect emotions or sentiment of individual employees (banned by EU AI Act)
  • Expose raw messages to managers — only aggregated insights
  • Sell, share, or monetize your data in any way

Compliance

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GDPR Ready

Data deletion on request. DPA available. EU data residency option.

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SOC 2 Type II

In progress for Enterprise tier. Expected Q3 2026.

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EU AI Act

Compliant. No emotion detection. Transparency labels on all AI output.

Infrastructure

Cloud providerAWS (us-east-1), EU option available
Knowledge graphNeo4j Aura (dedicated instance per workspace)
Vector storageAWS S3 + Bedrock embeddings
LLM providersGoogle Gemini (primary), Anthropic Claude (fallback) — both with ZDR
AuthenticationOAuth 2.0 (Slack/Teams), SAML/OIDC SSO (Enterprise)
Audit loggingImmutable audit trail for all AI actions and data access

Need more details?

Request our full Security Whitepaper or schedule a call with our security team.