WhatAn intelligent routing layer that automatically sends sensitive prompts to local models and non-sensitive work to cloud APIs, optimizing for both privacy and cost without developer intervention.
SignalDevelopers strongly value privacy and control but acknowledge that local models aren't SOTA for all tasks — they want a system that gives them the best of both worlds by keeping sensitive data local while routing complex tasks to the cloud, without manual decision-making each time.
Why NowLocal models have reached quality parity with cloud for routine coding tasks (tests, queries, boilerplate) while cloud models still lead on complex reasoning — creating a natural split point that didn't exist a year ago.
MarketSoftware development teams and enterprises with data sensitivity requirements; $2B+ developer tools market; no incumbent cleanly solves the local/cloud routing problem with privacy as the primary axis.
MoatClassification model for prompt sensitivity improves with usage data, and integration into developer workflows (IDE plugins, CLI tools) creates meaningful switching costs.
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