Solo BusinessImportance: Low

How solo SaaS builders choose which AI models to use

r/SaaSJul 15, 2026 · 4h ago

A discussion among solo SaaS builders raises the question of how to choose AI models when adding AI as a feature inside a product, rather than building an itself. Two questions are at the center: whether to stick to one provider (Gemini, Anthropic, or OpenAI) or mix models from different providers depending on the feature, and whether to call each provider's API directly, go through (a service that lets you access many providers' models through one ), or use a cloud platform's AI service such as or Google Vertex. The poster also notes that Google's model catalog service, referred to as Foundry, is unpleasant to use.

Radar's take

This is a genuinely practical question for anyone running a one-person SaaS. Sticking to a single provider keeps things simple but may mean missing a cheaper or better-suited model for a specific feature, while mixing providers adds flexibility at the cost of managing multiple API keys and comparing pricing. A router service like can smooth that over, though it may add its own fee or latency.

Worth noting is the real complaint about going through big like Bedrock or Vertex — a signal that their AI offerings can be less developer-friendly than calling APIs directly or using a router. For a bolting AI onto a product for the first time, starting with a direct or a router service, rather than locking into a cloud platform's AI stack, may be the lower-friction path.

Key points

A solo SaaS builder asks how others choose AI models for a feature inside their product
Debate: stick to one provider (Gemini, Anthropic, OpenAI) versus mixing providers per feature
Comparing direct API calls, , and like or Google Vertex
The poster says Google's model catalog service (Foundry) is unpleasant to use

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How solo SaaS builders choose which AI models to use

Key points

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