FAQ
Frequently asked questions
Clear answers about wallet credit, usage, subscriptions, and how Tycoon charges for work.
Our product changes weekly. Can the KB really keep up?
Yes, because the KB maintenance runs on the same release cadence as the product. Every release-notes entry (from /workflows/release-notes-production) triggers a KB check: what articles reference the changed feature? AI Head of Content updates affected articles the same day the feature ships. For major UI overhauls, a bigger refresh batches 10-30 article updates. The KB stays current because it's wired into the release pipeline, not treated as 'documentation we'll update later'.
What about embedded video tutorials — those are expensive and go stale too.
Video is the one place AI doesn't auto-fix. Videos become stale when UI changes but re-recording isn't cheap. AI Head of Content handles this two ways: (1) flags videos referencing deprecated UI and adds a text overlay note ('UI has changed slightly — current path: Settings > Data > Export'), and (2) prioritizes video refresh for articles with >1000 views/quarter, leaves lower-traffic videos as-is. For new tutorials, AI Head of Content writes the script + storyboard; you or a contractor does the recording. Saves 70% of production time.
How does it handle multi-language support — we have customers in EN, ES, JA, DE?
Full i18n workflow. New article drafted in primary language first (usually English), then translated via DeepL + human review for the supported locales. Updates to the primary article propagate to translations with version tracking (so a JA translation doesn't silently diverge from EN). SEO optimization per locale — different keywords rank in different languages. Locale-specific KB search configured in Algolia or your help-center's built-in search.
Our customers are developers. They prefer docs in GitHub README vs a help center. Does this apply?
Developer-facing docs are a different pipeline — more like /workflows/api-docs-maintenance. Tycoon distinguishes: developer docs live in the repo (README, docs/ folder, OpenAPI spec), end-user help lives in Intercom/Mintlify help center. Workflow principles are the same (gap detection from tickets, staleness detection from product changelog, SEO optimization) but the tools and tone differ. Teams with both usually run both workflows — developer docs for integrations, help center for admin/billing/account questions.
Can it actually improve deflection rate or is it just busy work?
Deflection improvements are measurable but take 90+ days to show. The mechanism: articles become discoverable (SEO + in-app search), accurate (match current product), and comprehensive (cover patterns from real tickets). Typical trajectory: month 1-2, minimal change (new articles indexing, old articles cleaned up). Month 3-6, deflection rises 5-15 points (30% → 40%, for example). Month 6+, compound gains as customers learn to search your KB first. The ones who don't see gains usually have an in-app search or help-widget problem, not a KB content problem — AI Customer Support flags which is the bottleneck.