AI SaaS Adds New Architectural Concerns

Traditional SaaS already requires authentication, authorization, tenant isolation, billing, and reliable deployments. AI introduces additional concerns such as model usage, token or request costs, asynchronous processing, and provider availability.

Core Design Areas

• Strong tenant isolation
• Role-based access control
• Per-tenant usage tracking
• Queue-based processing
• Provider abstraction
• Cost and rate controls
• Audit logs

Scale What Actually Needs Scaling

Keep interactive requests fast and move expensive tasks into workers. Caching can reduce repeated work, while usage controls protect both the customer experience and the platform's operating costs.

Good AI SaaS architecture creates a clear boundary between customer data, AI processing, and platform operations.