AIaaS

AIaaS is the AI equivalent of what cloud computing did for servers. Instead of hiring data scientists, buying GPUs, and training models in-house, companies subscribe to AI capabilities delivered over an API or managed product. OpenAI's API, Anthropic's Claude API, and Google's Vertex AI are the big provider examples, but the category extends to specialized services: AI search, AI document processing, AI voice, and so on.

For startups and mid-sized companies, AIaaS dramatically lowers the barrier to deploying AI. You do not need a machine learning team to build a product with AI capabilities; you call an API. The business model for AIaaS providers typically layers usage-based pricing on top of a tiered subscription, charging for compute consumed or requests made.

From a builder's perspective, relying on AIaaS introduces both vendor risk and inference cost exposure. If a provider changes pricing or deprecates a model, it affects your product directly. This is part of why BYOK (bring your own key) and model routing have become important architecture patterns: they let builders route between providers and hedge against single-vendor dependency.