How Data Streaming with Apache Kafka and Flink Powers AI and Autonomous Networks in the Telecom Industry
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How Data Streaming Powers AI and Autonomous Networks in Telecom – Insights from TM Forum Innovate Americas

AI and autonomous networks took center stage at TM Forum Innovate Americas 2025 in Dallas. Leaders from AT&T, Verizon, and other telcos showed how large-scale AI is transforming customer experience, security, and network operations, while the vision of self-optimizing networks moves closer to reality. At the heart of these advances lies data streaming: real-time, governed data flows that connect OSS/BSS, feed AI with fresh context, and enable automation at scale. This article captures the key insights from the event and explains why data streaming is becoming the central nervous system of modern telecoms.
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Telecom OSS Modernization with Data Streaming using Apache Kafka and Flink for Cloud-Native BSS and OTT Integration
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Telecom OSS Modernization with Data Streaming: From Legacy Burden to Cloud-Native Agility

OSS is critical for service delivery in telecom, yet legacy platforms have become rigid and costly. They slow innovation just as 5G, cloud native networks and OTT partnerships demand agility. This article explores how a data streaming platform with Apache Kafka and Flink helps telcos modernize OSS step by step, cut costs, accelerate time to market and turn OSS into the real time backbone for AI and event driven operations.
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Connected Car Vehicle API and Data Streaming with Apache Kafka and Flink in the Automotive Industry
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Streaming the Automotive Future: Real-Time Infrastructure for Vehicle Data

Connected vehicles are transforming the automotive industry into a software-driven, data-centric ecosystem. While APIs provide access to critical vehicle data, they fall short when it comes to real-time intelligence and scalability. This post explores how data streaming with Apache Kafka and Apache Flink turns raw API responses into reusable, governed data products that support real-time operations, analytics, and innovation. Learn how industry leaders are combining APIs and event streaming to build modern automotive platforms -where real-time data becomes a strategic asset.
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Global Payment Processor Built with Data Streaming using Apache Kafka at Stripe Paypal Payoneer Worldline
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How Global Payment Processors like Stripe and PayPal Use Data Streaming to Scale

This blog post explores how leading payment processors like Stripe, PayPal, Payoneer, and Worldline are leveraging data streaming with Apache Kafka to power real-time, scalable, and secure financial systems. As the industry shifts from batch processing to event-driven architecture, data streaming has become essential for handling transactions, fraud detection, compliance, and embedded services. The post highlights why Kafka is at the core of modern payment infrastructure – and how it enables innovation, resilience, and operational agility in the evolving fintech landscape.
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Data Streaming and AI in the Automotive Industry at OEMs like Porsche Tesla BMW
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Driving the Future: How Real-Time Data Streaming Is Powering Automotive Innovation

The automotive industry is rapidly shifting toward a software-defined, data-driven future. Real-time technologies like Apache Kafka and Apache Flink are now critical to powering connected vehicles, smart factories, autonomous platforms, and personalized mobility services. This blog explores how leading OEMs and suppliers use data streaming to drive digital transformation – from edge processing and AI to predictive maintenance and customer experience. As the industry moves toward intelligent, adaptive systems, event-driven architecture becomes a strategic foundation.
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Agentic AI with AWS Amazon Bedrock AgentCore and Data Streaming using Apache Kafka Flink and Confluent Cloud
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Building Agentic AI with Amazon Bedrock AgentCore and Data Streaming Using Apache Kafka and Flink

Agentic AI goes beyond chatbots. These are autonomous systems that observe, reason, and act—continuously and in real time. At AWS Summit New York 2025, Amazon launched Bedrock AgentCore to build and operate secure, scalable AI agents. But to run in production, agents also need real-time data, continuous context, and flexible integration. That’s where data streaming with Apache Kafka and Apache Flink comes in. Combined with open standards like MCP and A2A, they provide the event-driven foundation for always-on, enterprise-grade AI agents.
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FourKites Supply Chain Logistics Control Tower Powered by AI and Data Streaming with Confluent and Kafka
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Inside FourKites Logistics Platform: Data Streaming for AI and End-to-End Visibility in the Supply Chain

Global supply chains face constant disruption. Trade conflicts, wars, inflation, and shifting regulations are making logistics more unpredictable than ever. Traditional systems can’t keep up with the speed and complexity of today’s challenges. This blog post shows how FourKites, a leader in supply chain visibility, uses data streaming with Apache Kafka in the cloud, and AI to power real-time logistics. With over 3 million shipments tracked daily, FourKites delivers more than visibility — it enables fast, autonomous decisions at global scale.
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Real-Time FinOps with Data Streaming using Apache Kafka and Flink
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FinOps in Real Time: How Data Streaming Transforms Cloud Cost Management

FinOps bridges the gap between finance and engineering to control cloud spend in real time. However, many organizations still rely on delayed, batch-driven data pipelines that limit visibility and slow down decisions. This blog explores how Apache Kafka and Apache Flink enable real-time, governed FinOps by streaming cloud usage data as it happens. It covers the challenges of data governance, compliance, and cross-functional accountability—and how streaming architecture addresses them. Real-world examples from Bitvavo and SumUp show how financial services companies scale securely, build cost-aware teams, and improve agility using event-driven platforms.
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FinTech Alpian using Data Streaming and Agentic AI with Apache Kafka in Switzerland Regulated Market
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Agentic AI and RAG in Regulated FinTech with Apache Kafka at Alpian Bank

Regulated FinTech is transforming financial services by combining compliance with innovation. This post explores how real-time data streaming with Apache Kafka and Flink enables modern architecture, personalization, and AI integration—while maintaining strict governance. Alpian, a fully licensed Swiss digital bank, showcases how Agentic AI, RAG, and domain-driven design work together in a compliant, cloud-only environment.
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Durable Execution Engine with Restate Temporal DBOS vs Stream Processing with Kafka Streams Apache Flink Spark Structured Streaming
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­­The Rise of the Durable Execution Engine (Temporal, Restate) in an Event-driven Architecture (Apache Kafka)

Durable execution engines like Temporal and Restate are redefining how developers orchestrate long-running, stateful workflows in distributed systems. Unlike traditional BPM tools focused on human-centric tasks, these engines automate machine-to-machine processes with built-in durability, retries, and fault-tolerant coordination. When integrated with event-driven platforms like Apache Kafka, they enable scalable, resilient architectures—handling complex business logic such as order processing, fraud detection, and multi-step transactions. This blog explores their capabilities, differences from stream processing tools like Apache Flink, Kafka Streams or Spark Structured Streaming, and the emerging role they play in modern enterprise infrastructure.
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