Product Overview
AIRec: Artificial Intelligence Recommendation
Alibaba Cloud Artificial Intelligence Recommendation (AIRec) is built on Alibaba's big data and artificial intelligence technologies. It combines experience from multiple industries, such as e-commerce, content, news, ApsaraVideo Live, and social media, to provide personalized recommendation services for enterprises and developers worldwide. You can simply provide data according to the specified conventions and make simple API calls to obtain a dedicated recommendation service that delivers significant results.
For more information, see:
PAIRec: A platform for custom recommendation systems
PAIRec (Platform of AI Recommendation) is an end-to-end platform for the custom development of recommendation systems. It provides a comprehensive set of platform-level services that allow enterprise developers to independently build, develop, iterate, and maintain their systems.
What is the PAI-Rec development platform for recommendation systems?
BE: Intelligent Retrieval Engine
Alibaba Cloud Retrieval Engine BE is a retrieval engine developed in-house by Alibaba Group for the recommendation industry. It provides comprehensive retrieval capabilities, a highly stable and high-performance index and query mechanism, and low O&M costs. The engine accelerates iteration efficiency through flexible filtering and configuration policies and supports features such as real-time online data updates that take effect within seconds.
For a detailed product description, see:
For more information, see What is a retrieval engine?.
TPP: Personalized Algorithm Development Platform
The Personalization Platform (TPP) is a development platform for algorithm and software engineers that supports business orchestration for services, such as retrieval and online prediction, in the recommendation, search, and advertising industries. It provides a mature engineering framework that frees developers from resource management and O&M. This allows them to focus on business logic development and business outcome experiments.
For more information about the product, see the following: