Data Retention Policies for Chat Assistants

data-retention • compliance • ai-assistant

Data Retention Policies for Chat Assistants

Regulators and customers expect clear retention rules. This guide helps you define per-artifact policies and implement deletion workflows that stand up to audits.

Classify your data

ArtifactExampleDefault retention
Chat transcriptsConversations, citations, feedback90 days
Analytics eventsImpressions, opens, fallback logs90 days
Audit configsPrompt versions, crawl manifests, threshold changes365 days
Backups/snapshotsDatabase or storage snapshotsPer backup policy

Tenant overrides

  • Allow enterprise tenants to extend retention up to 730 days for analytics/audit needs.
  • Store retention policies per tenant and per artifact type.
  • Reflect retention in your pricing tiers; longer retention impacts storage costs.

Deletion workflow

  1. Request: Tenant triggers deletion via UI/API; capture reason and scope (single tenant or per user).
  2. Queue: Add job to compliance queue; include retention policy and deadlines.
  3. Delete: Remove data from primary databases, search indexes, and backups (or mark for purge).
  4. Evidence: Store hash of deleted content, actor, timestamp, and scope to prove deletion occurred.
  5. Notify: Send confirmation to tenant admins and log the event.

Automation tips

  • Use time-to-live (TTL) indexes where databases support them.
  • Run daily jobs that prune expired documents and emit summary metrics (records deleted, bytes freed).
  • Integrate with backups: mark entries for purge and ensure they are removed within backup retention windows.

CrawlBot policy

CrawlBot enforces 90/90/365 defaults, supports tenant overrides up to 730 days, and logs every deletion. Use this framework to keep assistant data compliant and audit-ready.***