WhatA coding agent middleware that intelligently routes tasks between local models (for simple completions, private code, low-latency needs) and cloud APIs (for complex reasoning, large context tasks), optimizing for cost, speed, and quality.
SignalDevelopers are torn between running local models and paying for cloud APIs — many describe migrating use cases to services like OpenRouter while still wanting local inference for certain workflows. The economics of pure-local don't work for complex tasks, but pure-cloud is expensive for heavy users spending hundreds per month on tokens.
Why NowLocal models have just crossed the threshold of being genuinely useful for simple coding tasks (autocomplete, lint fixes, small functions) while remaining clearly inferior for complex reasoning — creating a natural split that didn't exist when local models were useless for everything.
MarketProfessional developers spending $20-800/month on AI coding tools. Competes with Claude Code, Cursor, Codex but differentiates by optimizing the local-cloud split. TAM is the entire AI-assisted development market, roughly $10B+ and growing rapidly.
MoatAccumulated routing intelligence — learning which task types perform well locally vs. cloud across different hardware profiles creates proprietary optimization data that improves with scale.
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