How We Ship AI Features Without Blowing the Budget

The real cost of AI features

Adding AI to your product is easy. Keeping the inference costs predictable is the hard part.

Cache aggressively

The most expensive AI call is the one you make twice for the same input. Use Redis to cache AI responses with a TTL based on how often the underlying data changes.

Route by complexity

Not every query needs GPT-4. Use a routing layer: simple classification to GPT-3.5-turbo, complex reasoning to GPT-4o, real-time features to a self-hosted Mistral 7B. This alone reduces costs by 60-70%.

Streaming and early stopping

Stream responses to users. If they navigate away, you stop generation and stop paying for unused tokens.

Set hard spend limits

Always set monthly spend limits in the OpenAI dashboard. Set an alert at 80% and a hard cap at 100%.