WhatA platform that automatically routes AI API calls across models (DeepSeek, Claude, GPT, etc.) to minimize cost while maintaining a user-defined quality threshold for each task type.
SignalDevelopers are finding that cheaper models like DeepSeek perform comparably to premium models for many tasks, but the cost differences are staggering — sometimes 30x to 200x — and people are manually benchmarking and switching between providers with no systematic way to optimize spend across their workloads.
Why NowThe proliferation of near-parity models at wildly different price points (DeepSeek V4 at pennies vs GPT 5.5 Pro at dollars per call) has created a genuine arbitrage opportunity that didn't exist when there were only one or two frontier models.
MarketAny company spending $1K+/month on AI API calls; TAM is the entire AI inference market ($10B+ and growing fast). Competitors like Martian and OpenRouter do basic routing but lack task-specific quality-aware optimization.
MoatProprietary quality-cost dataset built from routing millions of real production calls across model providers, creating an increasingly accurate prediction of which model delivers acceptable quality at lowest cost for each task pattern.
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