Deploy AI/ML Models in 90% Less Time and Cost!
Built with enterprise scale and security, Datatron MLOps integrates model development seamlessly with your existing CI/CD process. Enabling businesses to deploy models securely and at scale in 90% less time and cost compared to homegrown solutions!
- JupyterHub Integration
- Simplified Kubernetes Management
- Enterprise Feature Enhancements
Datatron’s MLOps Platform
Datatron is an Enterprise AI Platform that Streamlines Machine Learning Operations & Governance Workflows
Streamline Model Deployment
Catalog, Provision, & Manage Models in One Week without Ad Hoc
Scripting or Manual Processes
- Accelerate time-to-market by being able to deploy more models into production rapidly
- Avoid manual scripts and custom coding for model deployments, reducing time and effort
- Track, manage, and monitor all models in the enterprise in one place
Observe & Govern Models In Production
Simplify the process of deploying models into production, including cataloging, provisioning, and managing. Eliminate ad hoc scripting and manual processes.
- Actionable Model Catalog – Monitor models for bias, drift, & performance anomalies in real-time
- AI Governance – “Explainability” and “Observability” reports in one place; satisfy Risk/Compliance audit requirements
- A/B Testing & Health Score – Optimize performance and model health
Enterprise-Ready and at Scale
Manage More Models in Production Faster, Easier, & For More Teams
- Eliminate long-term supportability issues with open-source or internally built systems
- Allow business and IT to ensure interoperability with existing infrastructure
- Reduce significant capital and operation overhead building custom systems
- Focus resources to solve business critical needs
Datatron Solves YOUR AI Problem
- Revenue – Get more ROI from your ML program investment
- Progress – Stop starting over – works with your existing stack
- Productivity – Improve efficiency with an enterprise-wide solution
- Effectiveness – Get more models into production
- Time – Spend more time creating, and less time maintaining models
- Expertise – Stop wearing multiple hats moonlighting as DevOps
ML Engineering & DevOps
- Domain-Expertise – MLOps is not DevOps – Avoid post-deployment blame
- Reliability – Get a solution that just works
- Consistency – Use one development-agnostic MLOps platform for any model
Datatron’s customers can rapidly and confidently leverage AI/ML to capture new business gains
Through Datatron’s platform automation, we were able to save four full-time people in addition to business value being created through Datatron’s Monitoring module.
Head of Insfrastructure, Comcast Corporation
It’s challenging to manage models, especially when there is a high rate of model growth each year. With Datatron, we were able to scale, manage and monitor all of our models on one centralized platform.
Zack Frogoso, Data Science & AI Manager, Dominos Pizza
Enhance Your MLOps Expertise
Frequently Asked Questions
Datatron helps answer important questions about
ML model operations
I've built our MLOps internally or on open source, why do I need Datatron?
You’ve probably expended countless resources building your homegrown MLOps solution, and yet it may not be consistently, reliably, or economically getting your models into production.
No one wants to regret their “build” versus “buy” decision by starting over.
This is where Datatron comes in. Datatron was built from the ground up to work with any IT configuration, stack, or platform. Leverage Datatron’s API to integrate only the features you need to remedy deficiencies.
Starting from scratch? Install on-prem or in the cloud. Datatron is the new paradigm in the evolving MLOps “best practice” of build AND buy. Datatron is FLEXIBLE MLOps.
Our organization is "early" in AI/ML. Why and when should we consider Datatron?
If you want to build AI/ML “right” from the beginning, you should consider Datatron in the planning phase of your journey, even if you have only a single model in the development phase (and none yet in production).
Most people today focus on the appeal of developing AI models and have not understood the complexity of operationalizing these models. They initially opt to build their own MLOps solution, but quickly encounter complexities that cause models to sit in the lab and never deliver the promised ROI from AI/ML. The abundance of open source tools make it seem like homegrown MLOps is a no-brainer – don’t take the cheese. Skip the steep, frustrating (and costly) learning curve required to deploy your first model into production via a homegrown solution.
Leverage Datatron so your team can focus on BUILDING models and delivering business value, instead of the experiencing the pitfalls of DIY MLOoops (pun intended)!
How quickly can I deploy a model on Datatron?
You often hear of businesses spending up to 12 months before a model can be deployed into production. Datatron accelerates model deployment velocity. Our clients deploy models in a few days, down to a few hours or even a few minutes.
Does Datatron monitor models for Bias and Drift? Does it offer alerts?
Datatron monitors models for Bias, Drift, Performance Anomalies, and even Custom Metrics, which can be tailored and configured for your specific model and business needs*.
Set thresholds and receive alerts. Clicking into the AI Governance Dashboard displays charts that can provide queues that Data Scientists can use to begin root cause investigation.
*Might require additional configuration.
How to ensure models are performing as expected?
There are a few key elements needed to ensure models are performing as expected. For example, model explainability must work with real-world production data, instead of lab research, to capture potential issues. In addition to model explainability, it is also important to understand how the underlying infrastructure supports these models for the most optimal performance.
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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.
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.
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.
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%.
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.
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.