Wavium

Wavium: Open-Source Deep Learning Platform

Deploy AI models into production with Wavium, an open-source deep learning platform for computer vision, NLP, speech recognition and more on cloud and edge devices.

What is Wavium?

Wavium is an open-source machine learning operations (MLOps) platform designed to help teams streamline the deployment of deep learning models into production environments. It provides infrastructure, services, and tools that facilitate the full model development lifecycle from data preparation to continuous integration/continuous delivery (CI/CD) pipelines for deployment on cloud infrastructure or edge devices.

Key capabilities of Wavium include:

• Integrated development environment (IDE) - Wavium Studio provides data scientists and engineers a user-friendly interface to build, version, and deploy models using popular frameworks like TensorFlow, PyTorch, and Keras.
• Model management - Track experiments, compare model versions, view lineage, and store a central catalog of productionized models.
• Model monitoring - Monitor key performance metrics of models post-deployment and get alerts for model drift or degraded performance.
• MLOps orchestration - Automate model building, testing, validation, staging, and deployment with reusable CI/CD pipelines tailored for machine learning.
• Edge and cloud deployment - Package trained models and deploy them to distributed edge devices or scale them on cloud platforms like AWS, GCP, and Azure.
• Model governance - Apply model risk analysis, explainability techniques, adversarial robustness testing, and data quality checks.

With its end-to-end platform, Wavium aims to make the process of taking deep learning models to production more efficient, robust, and scalable for data science teams across industries like manufacturing, telecommunications, healthcare, and more.

Wavium Features

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