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Deploying Machine Learning Models to Production

Machine learning allows businesses to operate efficiently at scale and glean transformative insights from data. The field is fast-evolving with new advances almost every day, yet translating state-of-the-art models into stable software can be unexpectedly challenging.

In this brief, we’ll walk through the critical decisions and common pitfalls in building and deploying production-grade machine learning software. We hope this will help your organization make the most of your machine learning tools – to serve more customers, help more people, and make more high-impact discoveries.

Lessons learned from cross-industry experience

At Strong Analytics, we have worked closely with companies of all sizes to design and implement powerful data science pipelines tailored to each client’s unique position and needs. Having deployed numerous business-critical models serving billions of requests in contexts requiring both high accuracy and near-instant response times, we’ve seen first-hand how machine learning can transform the way an organization operates and accelerate its growth.

We work with top brands in a range of industries.

“Strong Analytics partnered with us to design a new, machine learning-powered tool for restaurant operators to manage their business. They guided us through the process of framing the problem and determining what was possible with state-of-the-art ML/AI. The solution they developed transformed a key operational challenge into an automated solution that drives new value for restaurants.”
Mandy Tahvonen
Managing Director, Relish Works
“Strong was able to bring state-of-the-art computer vision and AI to bear on a challenge our organization has faced for over 100 years. Since our initial deployment, as new challenges and opportunities have arisen, Strong has remained a valued collaborative partner to Sunsweet.”
Harold Upton
Chief Information and Analytics Officer, Sunsweet Growers Inc.
“Partnering with Strong Analytics has taken ReUp further faster against our product vision than we could have anticipated. They are like rocket fuel for innovation, and our collaboration continues to deliver high-value data science initiatives thanks to their expertise and commitment to results.”
Zack Avshalomov
Head of Product, ReUp Education
“Our partnership with Strong has dramatically accelerated innovation at MBRDNA. They bring extreme technical capabilities, a creative and collaborative approach, and invaluable expertise to engineering challenges that push us forward in computer vision, AI, and machine learning.”
Naveen Sangeneni
Head of Engineering and CTO, Mercedes-Benz Research & Development North America
“As a growing startup, we found Strong Analytics' expertise to be invaluable in building a comprehensive and scalable data pipeline, warehousing, and analytics strategy.”
Ben Forgan
Founder, Hologram
“It was an absolute pleasure working with Strong Analytics; their technical expertise is as deep as it is broad… in the case of complex, unstructured problems, they blazed a trail for us where there was none.”
Charlotte Daniels
Head of Data Science,