TODAY
Train or call
Curate a dataset and train on expensive GPUs, or call a frontier model and pay for every image.
The thesis
Foundation models have already learned rich representations from vast amounts of data. ijk puts that learning to work in small models built for specific tasks.
01 / THE CONSTRAINT
Many AI use cases are constrained by network access, compute, privacy, or data.
02 / THE COMPILER
Foundation models already contain rich representations of the world. The ijk compiler turns that learned structure into models for specific tasks.
Define what matters in natural language, then test and refine the result without retraining the underlying model.
Train a small model to speak the shared representation.
Create new tasks without a task-specific labeled dataset.
Produce a specialist without another training cycle.
03 / BUILT TO SHIP
PASSIO NUTRITION-AI
Developed edge neural networks that recognized more than 4,000 food types at up to 30 FPS. Used by millions through partners including MyFitnessPal and Elevance Health.
MINDSEYE
Compiled text-defined image classes into downloadable edge models.
~30 MB / 2,000 sign-upsBYTEGPT
Built a compact language model designed for edge AI.
~85 MB / 1,000 Hugging Face downloadsQUANTUM BASE
Customized a contrastive neural network for quantum authentication.
Head of Software, Quantum Base PLCJames Kelly, PhD • Founder, ijk.ai • Former CTO, Passio
Google for Startups Alumni member with access to mentors across Google.
04 / THE THESIS
ijk compiles that learned structure into small models for specific tasks.
The resulting models solve real problems in environments constrained by compute, connectivity, privacy, or cost, where running a foundation model is impractical.
05 / SEE IT WORK
Start with a description, test a model in the browser, and refine it through conversation.
Build your model