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Agentic AI

23 posts
MCP vs REST HTTP vs Apache Kafka -The Enterprise Architect Guide and Decision Tree to Agentic AI Integration
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  • 1.3K views
  • 12 minute read

MCP vs. REST/HTTP API vs. Kafka: The Architect’s Guide to Agentic AI Integration

MCP, REST/HTTP APIs, and Apache Kafka are not alternatives. They solve different problems at different layers of the architecture. This article maps the decision: what each technology is built for, where the boundaries are, and where the real gray areas lie. Includes a comparison table and decision tree for architects.
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  • 11.3K views
  • 27 minute read

Enterprise Agentic AI Landscape 2026: Trust, Flexibility, and Vendor Lock-in

The Enterprise Agentic AI Landscape 2026 maps every major AI vendor across two dimensions that matter most: how much you trust their AI, and how much lock-in you accept. An independent, vendor-neutral analysis covering Anthropic, OpenAI, Google, Microsoft, AWS, Mistral, SAP, Salesforce, and more.
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The Enterprise Architecture Trinity around Process Orchestration Intelligence, Data Integration and Streaming, and Trusted Safe Agentic AI
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  • 1.8K views
  • 7 minute read

The Trinity of Modern Data Architecture: Process Intelligence, Event-Driven Integration, and Trusted Agentic AI

Agentic AI without governed processes is fast but ungoverned. Event-driven integration without process intelligence moves data but not decisions. Process intelligence without live data automates the wrong outcomes. The fix is a converged architecture. This post shows what that looks like.
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Shift Left Architecture 2.0 for the Era of Agentic AI with Kafka Flink Iceberg and MCP
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  • 1.9K views
  • 10 minute read

The Shift Left Architecture 2.0: Operational, Analytical and AI Interfaces for Real-Time Data Products

The Shift Left Architecture moves data integration logic into an event-driven architecture where governed data products are built once and served to multiple consumers. The original pattern covered two interfaces: operational via Apache Kafka and analytical via Apache Iceberg. This post introduces the third: AI applications via MCP, powered by a real-time context engine that gives AI agents access to current operational data. Governance spans the full data stack through enterprise catalog tools. Together, the three interfaces turn a single data streaming investment into the foundation for operational, analytical, and AI-powered enterprise software.
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Dashboards and Queries for Apache Kafka and the Role of Context Engine for Agentic AI and Humans
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  • 7 minute read

Dashboards and Queries for Apache Kafka: Operational, Explorative, and the Role of the Context Engine

Dashboards are a popular way to make streaming data visible and useful, but they are not always the right solution. This blog post explains when dashboards make sense for Apache Kafka data and when other approaches like automation, process intelligence, or agentic AI are better suited. It outlines the three main types of queries: operational, explorative, and dashboard serving. Each type requires a different architectural approach. The post highlights the importance of data quality, schemas, and governance as the foundation for reliable systems and introduces the role of a context engine in serving both human users and AI agents. Readers will learn how to choose the right solution based on business goals, not on tool preferences.
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Data Streaming and AI Telco Trends at MWC 2026 in Barcelona
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  • 8 minute read

Data Streaming at MWC 2026: How Apache Kafka, Flink and Agentic AI Power Telecom Trends

Mobile World Congress (MWC) 2026 highlights the shift from batch systems to real time data streaming in telecom. AI and agentic automation, network APIs, sovereign cloud, autonomous networks, and 5G monetization all depend on continuous, governed data flows at scale. A Data Streaming Platform built on Apache Kafka and Apache Flink enables operators to collect, process, and act on live data across network and business systems. It provides the foundation for applied AI, SLA enforcement, API monetization, and usage based billing. MWC shows that telecom innovation and measurable business value now rely on real time data streaming.
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Data Streaming Trends for 2026 with Apache Kafka Flink Diskless Cloud Agentic AI
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  • 9 minute read

Top Trends for Data Streaming with Apache Kafka and Flink in 2026

Each year brings new momentum to the data streaming space. In 2026, six key trends stand out. Platforms and vendors are consolidating. Diskless Kafka and Apache Iceberg are reshaping storage. Real-time analytics is moving into the stream. Enterprises demand zero data loss and regional compliance. Streaming is now powering operational AI with real-time context. Data streaming has evolved. It is now strategic infrastructure at the heart of modern enterprise systems.
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Social Commerce in Retail with Data Streaming using Apache Kafka Flink and Agentic AI
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  • 9 minute read

Data Streaming in Retail: Social Commerce from Influencers to Inventory

Social commerce is reshaping retail by merging entertainment, influencer marketing, and instant purchasing into one real-time experience. Platforms like TikTok and Instagram have become active digital storefronts where discovery and transactions happen at once. This article explains how data streaming with Apache Kafka and Flink enables retailers to power social commerce through continuous data flow, real-time inventory updates, and personalized engagement. It shows how streaming unifies marketing, operations, and AI-driven decision-making while helping retailers compete with new AI platforms such as OpenAI that are redefining digital shopping.
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The Future of AI-Ready Integration with Data Streaming powered by Apache Kafka and Flink
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  • 4 minute read

How Siemens, SAP, and Confluent Shape the Future of AI Ready Integration – Highlights from the Rojo Event in Amsterdam

Many enterprises want to become AI ready but are limited by slow, batch based integration platforms that prevent real time insight and automation. The Rojo “Future of Integration” event in Amsterdam addressed this challenge by bringing together Siemens, SAP, Rojo, and Confluent to show how event driven and intelligent data architectures solve it. The discussions revealed how data streaming with Apache Kafka and Flink complements traditional integration tools, enabling continuous data flow, scalability, and the foundation for AI and automation. This blog summarizes the key learnings from the event, including my presentation “AI Ready Integration with Data Streaming,” and insights from Siemens, SAP, and Rojo on how enterprises can build truly connected, AI ready ecosystems.
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Real Time Point of Sale POS in Retail and eCommerce with Data Streaming using Kafka and Flink at SumUp Square Shopify
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  • 6 minute read

Square, SumUp, Shopify: Real-Time Point-of-Sale (POS) in the Age of Data Streaming

Point-of-Sale systems are evolving into real-time, connected platforms that go far beyond payments. Mobile solutions from Square, SumUp, and Shopify give even the smallest merchants access to integrated sales channels, inventory management, and customer insights. Powered by Apache Kafka and Apache Flink, data streaming is transforming retail with instant decisions, automated actions, and the foundation for Agentic AI in the future of POS.
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