Machine learning can automate business processes, but maybe more importantly,
it can improve customer experience—just look at Cimpress.
Cimpress, the parent company of VistaPrint, is one of the foremost aggregators of customized merchandise in the world with more than 10,000 employees spanning multiple continents. It has a mind for ethically and environmentally sustainable product production and has grown rapidly since its inception in 1994, while maintaining its ethos of staying small even as it gets big.
Cimpress integrates ML into its online experience
By 2016, Cimpress was running up against the challenge of deploying its models at
scale—a huge undertaking for any company to integrate into its existing tech infrastructure. The Cimpress team realized the effort required to manually deploy
ML models was slowing them down and started looking for solutions.
Cimpress tested many potential solutions but found Algorithmia’s Serverless AI Layer to be the perfect fit for deploying and managing its models at scale. The AI Layer reduced the number of full-time developers it required to maintain and optimize its systems.
Algorithmia is able to ensure seamless future deployments of machine learning projects for Cimpress without costly or time-intensive rollouts.
The Algorithmia collaboration is accelerating Cimpress’ ability to offer wider customer focus without reducing its commitment to quality and efficiency.
Cimpress was ahead of the curve in understanding core principles of machine learning
Of course, companies should spend time distilling and identifying their core business needs and gaps, like Cimpress did, before looking to incorporate machine learning says Chief Decision Intelligence Engineer at Google and widely published writer about all things AI and machine learning, Cassie Koryzov (Towards Data Science, 2018). An outside firm with expertise in building customized ML infrastructure is often better suited to meet the automation needs than internal developers.
Entrepreneur and former principal data scientist at LinkedIn Peter Skomoroch also calls for using outside experts to build machine learning into business models.
“Big companies should avoid building their own machine learning infrastructure. Almost every tech company I talk to is building their own custom machine learning stack and has a team that’s way too excited about doing this.” – @l2k dropping ML knowledge https://t.co/P0mOX8s9r0
— Peter Skomoroch (@peteskomoroch) November 12, 2018