Automated scanner that flags stale KB articles by update date and content signals, routes them to owners for refresh or kill. No more zombie docs.
Your knowledge base is a liability the moment it stops being updated. A single outdated troubleshooting step tanks support efficiency; a deprecated API example in your docs becomes a support ticket factory. The Knowledge Base Freshness Agent runs on a schedule, scans every article for staleness signals (last-modified date, version references, deprecated product mentions), and surfaces the rot before customers find it. The workflow is simple: agent crawls KB, flags articles older than your threshold (typically 6–12 months depending on product velocity), cross-references against known deprecations or version bumps, and routes flagged docs to content owners via Slack, email, or your ticketing system. No manual audit. No guessing which docs are poisoned. Why this matters: support teams spend 15–20% of their time answering questions that are already answered—but answered wrong. Stale docs create a trust tax. Customers assume your product is outdated if your docs are. Operators who run this agent see a measurable drop in support volume within 30 days because the docs actually reflect reality. The agent doesn't delete anything. It flags, routes, and waits for human approval. You decide whether to refresh, deprecate, or archive. The approval gate is critical: a bot that auto-deletes docs is a bot that will delete something important on a Friday.
Privacy notes
Agent scans article text and metadata only; does not access customer data or support tickets. Requires read access to KB platform and write access to notification system (Slack, email, ticketing). If KB contains sensitive information (internal-only docs, customer PII in examples), ensure agent is scoped to public-facing KB only or configure exclusion rules. No data is stored or logged beyond freshness reports (which are typically retained for 90 days for audit purposes). Check your KB platform's data residency and retention policies before deploying.