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Token-efficiency Obsessed AI R&D Lab

Tokenmaxxingis for suckers.

Enterprise AI runs on infinite budgets.
We build token-efficient developer tools for people who still have to care what the API bill says.

01 / Philosophy Tokenmaxxing is for suckers

The AI industry has a fundamental conflict of interest.

Labs like Google, OpenAI, Anthropic, Microsoft, etc derive massive revenue from the margin on token consumption. It is mathematically against their financial interest to reduce the number of tokens their tools burn. That's why their mainstream wrappers dump your entire codebase into a context window just to change a single line of code.

You can't ask the wolf to protect the herd.

We are the antidote to that. We are an Applied AI lab focused entirely on building tools for developers who don't want AI to become a massive new line item in their annual budget.

Throwing more tokens at a problem is a brute-force solution we just don't believe in. Instead, we build tools that work towards deterministic outcomes through intelligent architecture, treating AI as the commodity worker it is.

Try LucenaCoder

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Total Tokens Consumed

Same multi-file task. Same model.

See Benchmark
Lucena
34,102
Pi
117,002
OpenCode
317,304
Copilot
395,334
Continue
415,091
Kilo Code
540,075