Model Routing
Automatically selecting the best AI model for each query based on task type, complexity, cost, and latency requirements. Smart routers analyze your prompt and route it to the optimal model — saving money on simple tasks and ensuring quality on complex ones.
Why it matters
No single model is best at everything. Some are cheap and fast, others are slow but brilliant at hard reasoning. Model routing automatically sends each request to the right one, so you don't overpay for simple tasks or get weak answers on complex ones. For anyone running AI at scale, this quietly cuts costs and raises quality without users noticing anything except better, faster results.
In practice
A support app gets two questions: "What are your hours?" and "Explain why my invoice math is wrong." A router sends the first to a tiny, cheap model that answers instantly, and the second to a powerful reasoning model that can work through the numbers. Users get quick replies to easy questions and thorough ones to hard questions, while the company avoids paying premium rates on every single message.
Related terms
AI Dubbing
Automated translation and re-voicing of audio/video content into other languages while preserving the original speaker's voice characteristics, timing, and emotional delivery.
AI Orchestration
Coordinating multiple AI models, tools, and data sources in a unified pipeline. An orchestration layer manages prompt routing, context passing, error handling, and output aggregation across different AI services.
API (Application Programming Interface)
A way for software applications to communicate with each other. AI APIs let developers integrate AI capabilities into their own applications programmatically.
Attention Mechanism
A technique that allows AI models to focus on the most relevant parts of input data when generating output. In language models, attention determines which words in a sentence are most important for understanding each other word.
Diffusion Model
A type of generative AI that creates images by gradually removing noise from a random starting point. Powers tools like Stable Diffusion, DALL-E, and Midjourney. Works by learning the reverse of a noise-adding process.
Distillation
A technique where a smaller 'student' model learns to replicate the behavior of a larger 'teacher' model. Produces compact models that retain most of the teacher's capability while being faster, cheaper, and deployable on smaller devices.