When you call an LLM API, you pick a model and hope it's the right one. Claude for reasoning, GPT for...
Flint decomposes prompts and routes sub-tasks to specialized models (DeepSeek, Qwen, Kimi, 30+) in parallel. Automates model selection and maintains OpenAI API compatibility while cutting latency—crucial for CTO teams deploying cost-effective multi-model stacks.
When you call an LLM API, you pick a model and hope it's the right one. Claude for reasoning, GPT for code, Gemini for long context... you're doing the routing manually.
I got tired of this, so I built Flint — a smart routing engine that does the model selection for you.
How It Works
Instead of forwarding your prompt to a single model, Flint:
Decomposes — analyzes your prompt and identifies which capability domains it needs (research, analysis, code, content, math...)
How I built a harness-agnostic model router for Cursor and Claude Code and what broke along the...
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When I shipped the Neuron AI official router package a few weeks ago I received the same question...
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How to Build a Cost-Aware LLM Routing System with NadirClaw Using Local Prompt Classification and Gemini Model Switching
If your LLM costs are climbing, the instinct is almost always the same: swap to a cheaper model....
