Developers using multiple AI models waste time deciding which one to use for each task. Performance and cost vary dramatically between models.
Build a proxy layer that analyzes queries and routes them to the optimal model (e.g., GPT-4 for complex reasoning, Claude for document processing). Include cost tracking and fallback logic.
Sell to engineering teams through a usage-based API. Offer better results and lower costs than using single models directly.
Start with a CLI tool that wraps major model APIs with simple routing rules. Gradually add more sophisticated analysis.
Risk is big players (like GitHub Copilot) building this in-house, so differentiate with transparency and control.