01
Discovery
We review your existing harness, map the workflow, and work with you to define metrics that describe product quality. Before anything changes, we agree on what better means.
Own your intelligence
Train custom models on your data. Have them learn as they go. Run faster and cheaper inference. Own the weights.
Programmable again
Software has shifted from programming to an orchestration of models. Carefully crafted functions once gave us behavior we could shape, test, and improve. Now, it is captured in long prompts of instructions and examples we hope the model follows.
Reliable software cannot be built on hope. We must take programmability back.
This means changing the model from the inside, so it fits the work we need done. Your system already records the data for this. Every output, correction, failure, and success is a lesson to learn from. At Chonkie, we use these signals to train specialists that natively understand your software. These specialists run faster, cost less, and keep learning from new signals. You stop hoping your model follows your rules, because now it is designed to.
Let the frontier reason. Hand the real work to specialists.
Intelligence learned from your product
02
Refine
Based on our findings, we improve the current system: better context, clearer prompts, model upgrades, and plumbing fixes. You get measurable lift in days, and better production examples for the model we train next.
03
Specialize
Next, we train a model fit for your workflow. Training reflects real production behavior and covers the rare, critical cases you cannot afford to miss. The result is a reliable specialist that performs well even on the hardest paths.
04
Compound
The model keeps learning. Once in production, new cases feed back into a training loop, teaching the specialist new tricks and improving performance as your product changes
Open Source
Improving an agent near you
Chonkie started as an open-source context layer, giving developers the best way to clean data, split it with intent, embed it, and move it into retrieval. Today, our tools supply context to millions of agents, ensuring they have the information they need to succeed.
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