Real-time intelligence: Flink + AI
In today's AI era, businesses demand immediate data and real-time decision-making. Traditional AI, reliant on batch processing, falls short for low-latency, high-accuracy use cases like risk control, recommendations, and anomaly detection. Realtime Compute for Apache Flink bridges this gap by deeply integrating stream processing and AI. It delivers an end-to-end real-time intelligence loop—from data ingestion and feature engineering to AI inference and result feedback—empowering AI to drive business evolution in real time.
Overview of Flink's core AI capabilities
The integration of Flink and AI covers the following key areas:
Real-time feature engineering: Extracts, aggregates, and transforms features from streaming data in real time to provide timely input for models.
Native LLM integration: Uses Model DDLs and built-in AI functions, such as ML_PREDICT. This feature lets you directly call LLM or embedding models for tasks such as text comprehension, vectorization, and semantic analysis. The integration is compatible with the OpenAI APIs, allowing you to seamlessly connect various models. It fully supports LLM services, including Alibaba Cloud Model Studio and Platform for AI (PAI).
Vector data processing and retrieval: Integrates seamlessly with vector databases, such as Milvus, to enable millisecond-level streaming similarity searches and integrated analysis of unstructured data.
Unified processing of heterogeneous data: Supports real-time ingestion and AI enhancement of data from multiple sources, including structured logs, database Change Data Capture (CDC), and unstructured data such as text and voice.
With these capabilities, Realtime Compute for Apache Flink transforms data processing into real-time intelligence. It enables businesses to understand data, predict trends, and make intelligent decisions. With evolving capabilities in areas like real-time video stream analysis and multimodal AI, Flink is ready to expand the frontiers of real-time intelligence and serve as the foundational infrastructure for future AI applications.