Deploying MLOps at Speed

ML Ops Pipeline Architecting and Building
The data and DevOps pipeline is the backbone of any ML solution, Pactera EDGE automates the pipeline from development to production, leveraging cloud environments and infrastructure as code.

ML Ops Framework Deployment
Like DevOps, ML Ops is about people and process, not just tech. Pactera EDGE deploys robust operational frameworks, training data scientists and ML engineers in the practices that power ML Ops.

Productionalizing ML Models
With a robust MLOps framework, ML models can be productionalized at a rapid pace, with new models brought into use faster than ever before.

Engineering Support
Rely on Pactera EDGE to provide ongoing support to enable growing capabilities and continuing success.

Capability Co-Creation
When the time comes to add to your strengths in machine learning, partner with our seasoned enterprise AI/ML teams to co-create new capabilities.
Why Pactera EDGE?
Hands-on Experience
What others talk about, we’ve implemented in Fortune 500 settings, driving change and profitability.
Speed to Market
Drawing on our experience and infrastructure as code, we complete a typical project in 8-12 weeks.
Practical Consultation
An expert team combines mastery of craft with the ability to ask the right questions at the outset.

ML Ops is DevOps for building and commercializing ML models. It embodies a shift from an “ARTISAN-LIKE” model building and deployment to an institutionalized way of infusing Intelligence into the enterprise.
Vasudevan Sundarababu, SVP, Head of Digital Engineering Practice