An AI smart router sits between your tasks and the model market. It scores each incoming task and sends it to the cheapest model capable of doing the job — a frontier API for hard reasoning, a fine-tuned local model for routine patterns — instead of sending everything to one expensive model.
Most teams send nearly every task to a frontier model by default and overpay for the routine ones. On our benchmark workload, Toto's routing cuts token cost about 63% with no loss in output quality — and the savings scale with task volume.
When it's a pattern your workload repeats: classification, extraction, enrichment, templated drafting. Toto fine-tunes local models on those patterns. High-novelty or high-stakes tasks still escalate to frontier models.
Yes. Toto builds, fine-tunes, evaluates, and maintains local models for your specific use cases from your task history. Your code and prompts never touch Toto's cloud — the models deploy where you control them.
Toto is in private pilot. Drop your email on toto.tech or write to hello@toto.tech and we'll reach out.