Models in a few lines
A high-level interface over your chosen backend.
We have no published Keras build. Keras 3 runs on JAX, TensorFlow or PyTorch, and we say plainly that our Python back ends do not train models.
A high-level interface over your chosen backend.
JAX, TensorFlow or PyTorch, picked with your team.
A FastAPI service in front of a trained model.
Projects moved off older Keras releases.
Illustration. A dashed outline marks where the technology would sit. We have no published build on it.
Source: Keras, Getting started, keras.io/getting_started, checked 5 November 2026. You also need to install the backend framework.

Python 3.13 and FastAPI with an AI engine that writes a graded brief through a Claude-compatible API.
A Python 3.13 back end on FastAPI with telematics ingest and PostGIS.
TensorFlow
PyTorch
Python
Docker
scikit-learn
OpenCVJAX, TensorFlow and PyTorch. You pick one and install it separately.
No. We say so on the first call and show the nearest work, which is a Python 3.13 back end and an AI product that calls a model API.
Keras 3 can run on PyTorch, so the question is how much interface you want. We say which fits on the first call, and we have no published build on either.
You do, from the first commit. Repositories and cloud accounts stay in your name.
Thirty minutes on your data, your backend and your Keras version. No sales pitch.