The many reasons why your team needs Zetane


Work smarter, not harder.

Get the next generation of software tools for your enterprise and industrial applications of machine learning bundled in one powerful Zetane Engine. All members of your team will benefit from software made for current day workflows in data science and multi-stakeholder business projects.

You get improved means to debug your models, assess datasets and gain insights into your workflow faster.

Your non-technical colleagues can make more impactful contributions to your project through better visual and less abstract representations of your models, their outputs and their inner workings.

Your projects are sure to get approval with your strengthened abilities to explain the value and impact of your AI projects to clients and decision-makers in your department.

Machine learning and data science professionals

  • Visually inspect your model architecture and access internal tensors with one click. Obtain detailed analytics for every component of your neural networks as they interact with your data.

  • Detailed visuals and metrics enable you to understand sooner what is working and identify problems from the start. You save time by reducing the need for iterations and guess work.

  • More intuitive representations of machine learning projects make it possible for software developers to contribute to your projects.

  • Integrate with ease popular xAI libraries and other tools in your Python project.

  • Intuitive and less-abstract representations of your models enables non-technical members of the business to finally understand what you're working on.

Supervisors, managers and department decision-makers

  • Complete machine learning projects faster by reducing the number of iterations of your models by seeing in real-time how modifications to neural networks affect outcomes and key metrics.

  • Dramatically improve communications with your AI team; provide better and more targeted feedback to help your team progress through their machine learning projects.

  • More intuitive renditions of machine learning projects make it easier to collaborate with non-technical stakeholders.

  • Use rich visuals to avoid descriptions of your projects that are otherwise rife with confusing AI jargon. Clients and executives will buy-in and understand the value you provide.

Domain experts and business leaders

  • Visual and intuitive representations of AI builds a bridge for collaboration between your technical team, domain experts and regulators.

  • Diverse professionals can now evaluate a machine learning solution with greater ease to ensure it meets quality and safety standards set by industry.

  • Gain feasible means to look inside “black-box algorithms” so you better understand and can assess the risks inherent to complex machine learning solutions before deployment.

  • New abilities to conduct simulations and prototyping enable you to foresee the return on investment for AI innovations.

  • Test and evaluate AI models before they go into production, ensuring high quality projects that meet real world needs.