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Datatron logo old and new

Datatron Re-Brand Reveal & What It Means to AI/ML

There’s been a lot of significant momentum with Datatron in the past two years that led us to where we are today.

Today, we are announcing a new branding for Datatron. We feel the updated brand speaks to the audience we have been working with over the last few years.

We are also taking up the mantle of Reliable AI™.

It is a tagline that makes perfect sense from our customers’ perspectives. What they are looking for in an enterprise-ready MLOps solution is a way to deploy and scale their AI models rapidly. And once they are running in production, they need assurance that their AIs are operating as designed. AI models need to run reliably. And therefore, Reliable AI™.

The logo itself evolved from our former logo’s (green) cube look and feel. In the new logo, the three new colors around the cube’s edge represent the three key stakeholders who are critical to the successful deployment of AI models into production.

Datatron logo old and new

Think of each of the colors as a hand; we now have three hands surrounding the cube. The cube represents AI models. The three hands around the cube symbolize the importance of the three stakeholders collaborating to deploy, scale, manage, and govern AI models reliably. The three stakeholders are: Data Scientists, DevOps / Engineering / IT, and Business Executives.

The other way of looking at the three “hands” is how Datatron can operationalize AI models in any cloud environment. Be it on-premises, public cloud, and even air-gapped. Truly providing the flexibility for which businesses are looking.

We have also introduced refreshing new colors to represent the diverse and constantly evolving ML languages, frameworks, & tools used by businesses and how Datatron can support such diverse technologies with ease.

Datatron listens very intently to our clients about their business challenges. We observe that the notion of standardizing on a single ML tool for end-to-end is simply unrealistic. We believe in the freedom of data scientists to use their preferred tools to create the best working AI models possible.

The world of machine learning is still in its infancy, and there’s a new crop of tools that come up regularly. What a modern end-to-end ML workbench is today will quickly become outdated tomorrow.

Not only that, no single toolset today can solve all business problems; some ML languages are superior to others in certain use cases.

I liken building ML to building a skyscraper. The analogy is crude, but it gets the point across. The architects will use whatever design tools they see fit to design the building. Have you ever seen a tool that encompasses the design of the skyscraper all the way to construction? Probably not. In fact, it’s not realistic.

AI projects are no different. As a matter of fact, it is way too early at this stage of AI development to force a single end-to-end workbench for everything.

That’s why we’ve built Datatron to support the vast array of tools today and the exciting future that we’ll all build together ahead. We’re glad to be on this journey with you!

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Datatron 3.0 Product Release – Enterprise Feature Enhancements

Streamlined features that improve operational workflows, enforce enterprise-grade security, and simplify troubleshooting.

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Datatron 3.0 Product Release – Simplified Kubernetes Management

Eliminate the complexities of Kubernetes management and deploy new virtual private cloud environments in just a few clicks.

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Datatron 3.0 Product Release – JupyterHub Integration

Datatron continues to lead the way with simplifying data scientist workflows and delivering value from AI/ML with the new JupyterHub integration as part of the “Datatron 3.0” product release.

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Success Story: Global Bank Monitors 1,000’s of Models On Datatron

A top global bank was looking for an AI Governance platform and discovered so much more. With Datatron, executives can now easily monitor the “Health” of thousands of models, data scientists decreased the time required to identify issues with models and uncover the root cause by 65%, and each BU decreased their audit reporting time by 65%.

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Success Story: Domino’s 10x Model Deployment Velocity

Domino’s was looking for an AI Governance platform and discovered so much more. With Datatron, Domino’s accelerated model deployment 10x, and achieved 80% more risk-free model deployments, all while giving executives a global view of models and helping them to understand the KPI metrics achieved to increase ROI.

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5 Reasons Your AI/ML Models are Stuck in the Lab

AI/ML Executive need more ROI from AI/ML? Data Scientist want to get more models into production? ML DevOps Engineer/IT want an easier way to manage multiple models. Learn how enterprises with mature AI/ML programs overcome obstacles to operationalize more models with greater ease and less manpower.

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Our Latest *** RELEASE ***

Datatron 3.0

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Datatron continues to innovate and improve data scientist workflows with our latest release, which includes a JupyterHub Integration, Kubernetes Management and more Enterprise-grade features.

See the Release Notes!