Multi-tenant SaaS: one cache, many customers, zero leaks
Caching across customers multiplies savings and multiplies risk. Tenant isolation has to be architecture, not a WHERE clause.
SaaS platforms embedding LLM features face a sharp dilemma: per-tenant caches waste the repetition that crosses customers (everyone asks how exports work), while a shared cache risks the unforgivable — customer A's answer surfacing in customer B's session. Most teams resolve it by not caching, which resolves it by overpaying.
Crowkis dissolves the dilemma with namespacing as physics: every entry carries its tenant, lookups cannot cross the wall, and isolation is additionally scored at write time, so an entry that smells cross-tenant never enters the cache at all. Platform-level content can live in a deliberate shared tenant; customer-specific answers stay locked to their namespace.
Five stages score every write before it can ever be served.
The control plane speaks SaaS fluently: per-tenant hit rates and savings in the dashboard (your customers' ROI story, ready-made), per-tenant budgets that turn AI features into governable line items, and Enterprise virtual keys that let you meter your own customers' usage with hard walls.
The bottom line
Community edition covers your first three tenants free — a startup-friendly on-ramp — and the Enterprise license removes the ceiling when your logo wall grows. The leak you never have is the feature you'll never see in the dashboard, which is exactly the point.