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.
Core AI capabilities overview
The integration of Flink and AI covers the following key areas:
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).
Semantic retrieval and knowledge enhancement: Flink seamlessly integrates with vector databases such as Milvus. It combines vector search and vector assembler search with text embedding to move beyond traditional keyword matching. This provides core support for building high-precision, enterprise-level retrieval-augmented generation (RAG) and knowledge base Q&A systems.
Unstructured data insights: Flink automatically identifies business intents, emotional tones, and key entities from text using text classification, sentiment analysis, and information extraction functions. This transforms disorganized log or document streams into structured, analyzable data.
Efficient content processing and interaction: You can use text summarization to quickly extract the core points from long documents and text translation to eliminate cross-language communication barriers. This significantly reduces manual processing costs and improves information flow efficiency for your global business.
Data security and compliance: Flink supports data masking to automatically identify and mask sensitive private information across the entire data processing and model invocation pipeline. This ensures that AI applications meet enterprise security and compliance requirements.
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.