Capsa quantifies model uncertainty and de-risks outputs, enabling AI quality assurance and compliance.
import torch
import capsa_torch
_model = Model()
# Wrap your model
model = capsa_torch.wrapper(_model)
# Your model is now uncertainty-aware
pred, risk = model(input, return_risk=True)
import tensorflow as tf
import capsa_tf
# Add a decorator
@capsa_tf.Wrapper()
@tf.function
def model(...):
...
# Your model is now uncertainty-aware
pred, risk = model(input, return_risk=True)
Capsa, our proprietary technology, is built to be compatible with any ML model, seamlessly working in a matter of seconds at any stage of development.
Capsa enables users to detect and correct unreliable outputs produced by ML models, ensuring consistent high-quality results.