Auto Efficient: The Right Model for Every Request, Automatically

- Kilo AI is a startup building infrastructure to route AI queries to the most cost-effective large language model (LLM) for each task — automatically selecting between cheap/fast models (like Llama 3 8B) and expensive/powerful ones (like GPT-4 or Claude 3.5 Sonnet). - The core idea: not every request needs a top-tier model. Simple tasks (summarization, classification) can be handled by smaller models, saving cost and latency without sacrificing quality. - "Auto Efficient" is Kilo's routing system: it analyzes each incoming request and either picks the best model upfront or falls back to a stronger model if the initial answer is uncertain — similar to how a "mixture of experts" architecture works, but across entirely separate models. - This approach addresses a real pain point for developers: the explosion of available LLMs (hundreds now) makes it hard to manually tune which model to use for which task. Kilo automates that decision. - The company competes with other model-routing services (e.g., OpenRouter, Portkey, Unify) and with the broader trend toward "model routers" that optimize for cost/quality tradeoffs.