[ COMPANY ]
Renice AI changes how large models are run.
We build the bridge, not the ends.
[ THE CONSTRAINT ]
Nobody designed the AI stack.
It grew layer by layer. Models, software, chips, memory and networking are each owned by a different part of the industry, and each locked in choices that were rational at the time but were never made for serving. Sparse architectures were adopted to save training compute, back when compute was the scarce resource. That saving moved the cost into memory, and the memory bill now shapes all the hardware. Today's chips, in turn, carry more computing power than the models can use, so the scarce part — memory — sets the pace. Every one of those decisions made sense on its own. Together they cap how many tokens the world can make, and the few companies that could redesign the whole stack do it only for themselves.
[ OUR APPROACH ]
We tune both ends.
We do not train frontier models and we do not fabricate chips — the two most capital-intensive things in this industry. We buy the chips and the weights, integrate them the way Apple integrates parts, and tune both ends: keep what a model has learned, reshape it for the machine that will run it, and put each piece of it in the cheapest memory fast enough to serve it. What those models teach us becomes the specification for the next generation of chips, which we co-design with the companies that build them.
Build with Renice
We are hiring engineers who want to measure, redesign, and ship across the AI stack.
View open roles