Know what your model does not know.

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)

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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)

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Capsa makes any model safe and reliable in seconds.

Capsa: a model-agnostic uncertainty quantification platform.

Capsa, a model-agnostic uncertainty estimation library.

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.

Explore Capsa

import torch import capsa_torch _model = Model () model = capsa_torch.wrapper (_model) pred, risk = model (input, return_risk=True) import tensorflow as tf import capsa_tf @capsa_tf.Wrapper () @tf. function def model (...): pred, risk = model (input, return_risk=True)

import tensorflow as tf import capsa_tf @capsa_tf.Wrapper () @tf. function def model (...): pred, risk = model (input, return_risk=True) import torch import capsa_torch _model = Model () model = capsa_torch.wrapper (_model) pred, risk = model (input, return_risk=True)

Selected Use Cases

Know what your model does not know.

Capsa makes any model safe and reliable in seconds.

Capsa: a model-agnostic uncertainty quantification platform.

Selected Use Cases

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