Datatron Fixes MLOps

Remedy Homegrown MLOps or Build Right from the Start. On-prem, in Any Cloud, or Feature-by-Feature Via API. Datatron is Flexible MLOps & AI Governance.

*** WEBINAR ***



“Our Homegrown MLOps Isn’t Cutting It…
What Now?”

Fixes and Remedies Without Starting Over

In conversations with dozens of ML programs, one theme is constant – We’ve built MLOps in-house, but it’s not perfect.

In this webinar, we’ll walk through the most common journeys for homegrown or open source MLOps, inherent gaps, and solutions to remedy them without starting over.

 

Thurs. July 14, 11 am PT/ 2 pm ET)

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Datatron’s MLOps Platform

Datatron is an Enterprise AI Platform that Streamlines Machine Learning Operations & Governance Workflows
modelops
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
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machine learning model monitoring dashboard
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
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model validation
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
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Datatron Solves YOUR AI Problem

AI Executive


  • 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
Get More ROI

Data Scientists


  • Effectiveness – Get more Models into Production
  • Time – Spend more time creating, and less time maintaining Models
  • Expertise – Stop wearing multiple hats moonlighting as DevOps
Produce More Models

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
Manage Models Easily

Your AI Program Deserves Liberation.
Datatron is the Answer.

See what major Enterprise Brands have already discovered about
Datatron’s production-proven, Enterprise-grade AI Platform.

Success Stories

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 ​

Datatron Learning

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?

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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.

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)!

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.

Absolutely.

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.

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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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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whitepaper

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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whitepaper

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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whitepaper

Life Cycle of Machine Learning Models

Production-grade machine-learning models require strong deployment framework in order to reduce the time it takes to iterate a model faster, deploy new features quickly, and train on incoming data faster.

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whitepaper

Unique Challenges Of Machine Learning Models In Production

Production-grade machine-learning models require strong deployment framework in order to reduce the time it takes to iterate a model faster, deploy new features quickly, and train on incoming data faster.

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whitepaper

Model Deployment

Production-grade machine-learning models require strong deployment framework in order to reduce the time it takes to iterate a model faster, deploy new features quickly, and train on incoming data faster.

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Our Latest Content

Self-Guided In-Product Tour (7 Mini-Videos)

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Experience “The Datatron” product for yourself in this self-guided series of seven, concise, mini-videos that highlight key features, like the “Model Catalog,” and “Health Dashboard,” as well as Use Cases for Data Scientists (Part III), ML Engineers/DevOps (Part IV), and AI Executives & BU/LOB leaders (Part VII). Enjoy! And, when you are ready, Book a Demo

Watch the Product Videos!