Toggle Menu

Insights / / Capitalize on Machine Learning at Scale

June 01, 2021

Capitalize on Machine Learning at Scale

1 min read

Jump to section

“MLOps is a must-have capability to operationalize AI at scale.” – Forrester

Machine learning (ML) and artificial intelligence (AI) have the potential to create new insights and new opportunities for your agency. To maximize on the potential of ML and AI, you need to develop processes that allow you to repeatably and reliably train, validate, deploy, and maintain your ML algorithms. With MLOps, your organization can democratize ML, empower a community of data practitioners, and maximize business impact. MLOps makes ML efforts more efficient and effective, allowing them to scale to meet the largest challenges.


  • Understand the importance of business needs before introducing AI
  • Introduce the 5 areas essential for MLOps
    • MLOps for data governance and ingestion
    • Model Development
    • Model Operationalization
    • Monitoring
    • Security
  • Learn how to get started with an example agency use-case


Claire Walsh, Vice President of Engineering and Services, Excella

Henry Jia, Data Science Lead, Excella

You Might Also Like

Artificial Intelligence (AI)

3 Components of Ethical Artificial Intelligence 

The concept of artificial intelligence (AI) has been around since the middle of the 20th century, but...


3 Tips for Shifting Security Left in the Development Process

In modern software development, cybersecurity cannot be an afterthought. Instead, security should be considered as...


The Top Three Technical Capabilities You Need To Build And Maintain More Secure Systems

More and more organizations are tackling the imperative to improve the security of their systems....