Machine Learning That Works in Production
We take ML from notebook to production: data, models, deployment and monitoring, built on the platforms you already use.
From Promising Model to Business Value
Machine learning engineering is the discipline of building, deploying and operating machine learning models reliably in production systems. Upen Group helps organizations turn AI and ML ideas into features and processes that deliver measurable results.
Many ML initiatives stall between a working prototype and a production system. We close that gap with solid data engineering, reproducible training, automated deployment and continuous monitoring.
Our clients use our AI and ML expertise to unlock new opportunities, from predictions and recommendations to intelligent automation and conversational AI.
Our Machine Learning Services
Use Case Discovery
Identify and prioritize ML opportunities with clear business value.
Data Preparation
Collect, clean and engineer features from governed data sources.
Model Development
Train and evaluate models for prediction, classification and recommendation.
MLOps
Pipelines for reproducible training, versioning and automated deployment.
Deployment & Monitoring
Serve models at scale and monitor accuracy, drift and performance.
Generative AI Integration
Add assistants, summarization and search to applications responsibly.
Our ML Delivery Approach
Frame
Define the problem and success metric.
Prepare
Build quality, governed datasets.
Model
Train, evaluate and iterate.
Deploy
Ship to production with MLOps.
Monitor
Track drift and retrain.
Frequently Asked Questions
Still have questions? Our team replies within one business day.
Contact Us →What is machine learning engineering?
What is MLOps?
Do we need a lot of data to start?
Can you add generative AI to our applications?
Related Services
Ready to Put Machine Learning to Work?
Tell us where you are today and what you want to achieve. We will come back within one business day with next steps.
Talk to an Expert →Mon–Fri, 9 am–5 pm CT
Irving, TX 75038
Last updated: October 2, 2026