Browsing Tag

GenAI

4 posts
Event-Driven Agentic AI with Data Streaming using Apache Kafka and Flink
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  • 12 minute read

How Apache Kafka and Flink Power Event-Driven Agentic AI in Real Time

Agentic AI marks a major evolution in artificial intelligence—shifting from passive analytics to autonomous, goal-driven systems capable of planning and executing complex tasks in real time. To function effectively, these intelligent agents require immediate access to consistent, trustworthy data. Traditional batch processing architectures fall short of this need, introducing delays, data staleness, and rigid workflows. This blog post explores why event-driven architecture (EDA)—powered by Apache Kafka and Apache Flink—is essential for building scalable, reliable, and adaptive AI systems. It introduces key concepts such as Model Context Protocol (MCP) and Google’s Agent-to-Agent (A2A) protocol, which are redefining interoperability and context management in multi-agent environments. Real-world use cases from finance, healthcare, manufacturing, and more illustrate how Kafka and Flink provide the real-time backbone needed for production-grade Agentic AI. The post also highlights why popular frameworks like LangChain and LlamaIndex must be complemented by robust streaming infrastructure to support stateful, event-driven AI at scale.
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Learnings from the CIO Summit: AI + Data Streaming = Key for Success
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  • 5 minute read

CIO Summit: The State of AI and Why Data Streaming is Key for Success

The CIO Summit in Amsterdam provided a valuable perspective on the state of AI adoption across industries. While enthusiasm for AI remains high, organizations are grappling with the challenge of turning potential into tangible business outcomes. Key discussions centered on distinguishing hype from real value, the importance of high-quality and real-time data, and the role of automation in preparing businesses for AI integration. A recurring theme was that AI is not a standalone solution—it must be supported by a strong data foundation, clear ROI objectives, and a strategic approach. As AI continues to evolve toward more autonomous, agentic systems, data streaming will play a critical role in ensuring AI models remain relevant, context-aware, and actionable in real time.
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Data Streaming with Apache Kafka and Flink vs Visual Coding with Low-Code No-Code
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  • 9 minute read

Why Generative AI and Data Streaming Are Replacing Visual Coding with Low-Code / No-Code Platforms

Low-code/no-code tools have revolutionized software development and data engineering by providing visual interfaces that empower non-technical users. However, their limitations in scalability, consistency, and integration pose significant challenges in modern, real-time architectures. Generative AI is emerging as a game-changer, offering unprecedented flexibility and customization, addressing many of the pitfalls of traditional low-code/no-code platforms. Simultaneously, the data ecosystem is evolving with Apache Kafka and Flink, enabling real-time, event-driven architectures that resolve inefficiencies of fragmented, batch-driven systems. This blog explores the evolution of low-code/no-code tools, their challenges, when (not) to use visual coding, and how generative AI and data streaming are reshaping the landscape.
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The Past Present and Future of Stream Processing
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  • 12 minute read

The Past, Present and Future of Stream Processing

Stream processing has existed for decades. The adoption grows with open source frameworks like Apache Kafka and Flink in combination with fully managed cloud services. This blog post explores the past, present and future of stream processing, including the relation of machine learning and GenAI, streaming databases, and the integration between data streaming and data lakes with Apache Iceberg.
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