Multi-tenant architecture, white-label, BYOK, envelope encryption, and billing. 8 articles, written by the engineers building AI App Lab.
AI platform audit logging: immutable append-only audit trails, HMAC-SHA256 tamper detection, SHA-256 integrity chains, SIEM integration, compliance retention, and enterprise AI governance logging patterns.
Multi-tenant AI architecture: tenant isolation patterns for LLM SaaS, per-tenant vector databases, RAG data isolation, GPU sharing, RBAC, cost tracking, and enterprise SaaS AI platform design.
AI platform role hierarchy: multi-tenant RBAC with platform admin, tenant admin, and user roles, hierarchical resource scoping, permission inheritance, agent identity, and enterprise SaaS access control patterns.
Per-tenant cost tracking and quotas: token budgets, reserve-commit pattern, multi-level quota horizons, atomic Redis counters, cost attribution, noisy neighbor prevention, and AI SaaS FinOps best practices.
LLM usage metering and billing: token-based pricing models, Stripe billing integration, hybrid subscription plus usage, metering architecture, credit systems, invoice generation, and AI SaaS revenue infrastructure.
SaaS tenant suspension: lifecycle state machine, grace periods, data retention, reactivation, access revocation, dunning workflows, offboarding, and enterprise AI SaaS tenant lifecycle management patterns.
White-label AI platform: rebrandable AI SaaS with custom domains, per-tenant theming, reseller hierarchy, pricing controls, multi-tenant architecture, and enterprise white-label AI deployment patterns.
BYOK multi-tenant AI: bring your own key patterns for LLM SaaS, AES-256-GCM encryption, per-tenant key vault, credential resolution chain, gateway vs embedded SDK vs hybrid, and enterprise key management.