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The First Self-Explainable
Deep Learning Framework

Xpdeep revolutionary DL framework generates simultaneously the deep model and its precise, complete and intelligible explanations, offering an unprecedented transparent view inside the AI black box, with no compromise on performance.

Build Deep Learning Models with Confidence and Efficiency

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Easy to Implement

Simply substitute our engine components library in your code to start building self-explainable deep models.

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Improved Trust

Understand deep learning decisions with plain language explanations and interactive visualization.

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Simplified Adoption

Bridge the gap between AI and non-technical teams with our API, fostering trust and confidence.

A Deep Learning Engine For All

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Data Scientists and Developers

  • Accelerate your deep learning model training process with complete visibility into the learning journey.
  • Be ensured the engine avoids regression and overfitting, enhancing its accuracy

  • Reduce the amount of input data by eliminating unnecessary sources, optimizing the efficiency of your model.

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Compliance Authorities and Regulatory Institutions

  • Detect vulnerabilites and biases in your deep learning model.
  • Understand how the model operates from within, for real-world applications.
  • Get decision robustness and performance indicators for individuals, groups or the entire dataset, ensuring high accuracy.
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Vertical Application Users

  • Be autonomous in understanding AI decisions and recommendations, moving away from the black box paradigm.

  • Input data with trust and take data-driven decisions with full understanding.

  • Share output results transparently with non-technical stakeholders, backed up by robust justifications for actions and decisions taken.

Get explanations for deep models based on temporal data

The intricacies of time series have long presented a roadblock to achieving true explainability in deep learning. Xpdeep shatters these limitations by being the first to offer a comprehensive, understandable, and adaptable solution to this complex challenge.

Become a Partner

Consultants, Integrators, Application Developers, Independent Software Vendors, OEMs: Partner with Xpdeep.

Take Your Customers to the Forefront of AI Innovation, Ethics, and Performance

Unveil Xpdeep's self-explainable deep learning framework to your customers, leaving behind the opacity of the black box. Address their operational and regulatory requirements for trust, explainability, and superior accuracy in deep learning.

Our visualization module provides transparent explanations for deep neural networks they have never seen before, enhancing model performance and opening up new avenues of opportunity.

Let Your Customers Finally Access Deep Learning Explanations

Deploy Xpdeep-generated self-explainable deep learning models into your customers' applications or the machines/software you provide.

Let them access explanations through our visualization module or APIs, empowering them to harness the potential of high-accuracy explainable, and trustworthy AI, uniquely tailored to their needs, and complemented by your expertise.

"Users would prefer a self-explainable deep learning engine over me because it provides understandable explanations for its outputs, offering transparency, interpretability, and building trust in the decision-making process."
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Key Features of the Xpdeep Engine

Robust & Efficient

Models performance is on par with or higher than standard deep learning engines such as PyTorch or TensorFlow. No additional computing required to access explanation as they are generated at the same time as the model.

Ethical & Regulator-Friendly

Foster compliance with RGPD and AI European laws by ensuring your deep learning models maintain transparency and conformity in AI decisions while delivering accurate and reproducible results.

Generic & Flexible

Designed to work with any architecture, any type of data (tabular, time series, images...) and excelling in a wide range of tasks, including classification, clustering, forecasting, generative modeling, and uplift modeling.