Many AI startups see gross margins evaporate because every user request sends a 30,000-token prompt to a frontier reasoning model or routes blank PDF pages to a $0.03/page OCR API. With disciplined AI cost engineering, you can cut monthly OpenAI, Anthropic Claude, Google Gemini, and Document AI bills by 50% to 90% without sacrificing accuracy.
If you need to hire a freelance AI cost reduction and LLMOps programmer, I am Aldian Fazrihady.
Production AI Cost-Optimization Case Studies
- Model Routing & Prompt Caching (90% Savings): AI Cost Engineering: Cutting LLM & Speech API Bills by 90% with Model Routing and Caching
- OpenAI Batch API Pipelines (50% Savings): Reducing OpenAI Bills by 50% with the OpenAI Batch API
- Pre-Upload Document AI Filtering: The $0.03 Per Page Trap: Optimizing GCP Document AI Costs with Pre-Upload Filtering
- Client-Side WebAssembly / ONNX Inference ($0 Cloud Cost): Running Embeddings Locally with ONNX Runtime Web