Get More ROI from AI

Executives & AI/ML Team Leads Generate More Revenue,
Operationalize More Models, and Harmonize their Teams with

The Problem

Business leaders in the AI/ML space are at the vanguard of delivering business value. However, in this nascent space a clear path to profitability is not clearly defined. Best practices are still being developed with numerous pitfalls en route to profitability & proliferation within the Enterprise.

Not Getting ROI from
AI/ML Program

Governance, Compliance, & Explainability

Internal Discontent Between DS and DevOps & Multiple Teams/Stacks

The Solution

Enterprise at Scale

Empower your team to deliver more models to production faster. A recent study found that 80% of AI/ML models never make it out of the lab and into production.

Get Your Models into Production

AI Monitoring & AI Governance

Have you had an audit lately? It’s not a matter of IF, but WHEN – it’s coming. Datatron monitors your models for drift, bias, and other performance issues, delivering explainability critical to your Enterprise.

Get ready for an Audit

Model Operationalization (ModelOps)

Is your Data Scientist doing double-duty as a DevOps Engineer? Is your DevOps Engineer trained in MLOps? Is there enough blame to go around when models don’t perform as expected? Even if these aren’t issues in your organization, your IT team needs a Reliable AI™ platform that is development environment agnostic to support different stacks from different LOBs. Datatron delivers.

Learn More about Operationalization

Datatron Learning

Enhance Your ML Ops Expertise

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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