ModelRoute – Auto-switch models by task complexity

A local proxy that picks the right model for each task, saving cost and avoiding outages

Problem

Developers find that not every task needs the most expensive model—simple bug fixes work fine with cheaper ones—but manual switching and quota tracking are a pain. Meanwhile, quotas run out mid-task, models get silently downgraded, and services suddenly slow down, causing work interruptions.

Solution

A local-first LLM router that automatically selects the most cost-effective model based on task type (completion, refactoring, debugging, long-form generation), monitors per-model quotas and response quality in real time, and falls back to backup models when the primary is unavailable or degraded.

Users

Indie developers and small-team programmers who use multiple AI coding tools daily

MVP

Local proxy supporting OpenAI/Claude/DeepSeek APIs; keyword-based routing to different models; quota and latency dashboard; fallback rule configuration; CLI and simple web panel

Revenue

Free basic tier + subscription for advanced routing rules and team quota pooling; or take a cut per API call

Why now

Model variety is exploding with huge price differences, and developers are anxious about degradation and quotas, yet existing tools only monitor without smart routing—an indie developer can quickly enter with API aggregation and a local proxy