APN Spotlight: Machine Learning Partners
Learn how APN Partners are using machine learning technology to drive business solutions for AWS customers.
About Machine Learning Partners
AWS Partner Network (APN) Machine Learning Partners have proven success and expertise in helping customers build and take advantage of machine learning solutions on AWS. Machine learning is a subset of artificial intelligence where predictions are not pre-programmed or determined by experts, but rather are derived by the algorithmic processing of data. APN Machine Learning Partners leverage customers' existing data to drive better decision-making and innovative solutions.
Machine Learning Partner Stories
Royal FloraHolland, the world’s largest flower auction company, needed to go digital, create IT infrastructure, and become more data-driven. The company engaged Xebia to help build a data science program internally and begin to develop machine learning tooling and applications.
Lenovo is dedicated to transforming its customers’ experiences with technology through relentless innovation and a broad range of connected devices. Brazil is a primary emerging market for Lenovo and the company sought to use machine learning tools to help predict sell-out volumes in the country.
Rue Gilt Groupe offers online shoppers a unique retail experience through its flash sale model. The company decided to build MyRue, a Collaborative Filtering (CF) recommendation engine, on AWS with the help of Databricks. Rue Gilt Groupe is now able to provide users with a more personalized browsing experience.
Citibot’s mission is to fundamentally change how citizens contact and interact with their local governments through digital channels. After launching the initial version of the Citibot chatbot, the organization engaged with TensorIoT to improve its natural language processing.
TINE is a Norwegian cooperative owned by farmers that’s creating new ways to combine technology, animal science, and age-old knowledge to create better dairy products. TINE engaged with Crayon to help improve its insights, predictions, and analyses using ML on AWS.
LinkSquares provides an automated, software-based solution to streamline post-signature contract analysis. The company needed to optimize its existing solution in order to conduct contract analysis efficiently and accurately at scale. The team engaged with SFL Scientific to build a custom machine learning solution.
Pandora is one of the world’s most powerful music discovery platforms. Pandora’s anomaly-detection system had limitations in its detection models. Using Anodot’s AI-powered time series analytics solution, Pandora now monitors system operations and health in near real-time.
Lyft didn’t have the resources to manually monitor every metric it gathered to detect anomalies in its data. To accurately detect anomalies at scale that could signal larger problems and require immediate attention, Lyft turned to the automation and machine learning capabilities of Anodot.
Consensus built a platform for retailers that simplifies the complex process of “activated selling,” or selling subscription-based products. The company uses data preparation and machine learning from Trifacta to identify retail fraud.
Machine Learning Partner Blog Posts
By Kris Skrinak, APN Machine Learning Segment Lead at AWS
By Jennifer Prendki, VP of Machine Learning at Figure Eight
By Lars Joakim Nilsson, Managing Director of Advanced Analytics and Big Data at Inmeta
By Josh Poduska, Chief Data Scientist at Domino Data Lab