Confluent unlocks scalable real-time agentic AI with Streaming Agents
Enterprises can quickly move from prototype to production-ready AI agents with Streaming Agents.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
How to Protect PII in Apache Kafka With Schema Registry and Data Contracts
A data contract is a formal agreement between an upstream component and a downstream component on the structure and semantics of data that’s in motion. In a previous post, I showed how Confluent Schema Registry supports data contracts. By combining data contracts and encryption on streaming workloads, you can shift left the responsibility of data consistency, quality, and security to the producer, allowing the consumer to depend on a trustworthy stream of data.
Demo: Streaming Agents automate competitive pricing in real time
Streaming Agents enable you to build, deploy, and orchestrate event-driven agents natively on Apache Flink and Apache Kafka. By unifying stream processing and agentic AI workflows, they leverage fresh context to continuously monitor and act on what’s happening in the business. In this demo, Brenner Heintz, Staff Technical Marketing Manager at Confluent, shows how to build agents that automate real-time competitive price matching on sales orders.
Real-Time AI Agents Powered by Apache Kafka, Apache Flink, and Google Cloud
Discover how developers and data teams can build agentic AI applications with the combined power of Google Cloud AI services and Confluent Cloud’s real-time data streaming platform. This video showcases the joint value of integrating Apache Kafka, Confluent Schema Registry, Kafka Connect, and Apache Flink to enable seamless, real-time communication between AI agents. What you’ll learn: With Confluent and Google Cloud, you can go beyond AI experiments to build scalable, enterprise-ready multi-agent systems powered by real-time data.
How Confluent Helps Software Providers Build Real-Time Products and SaaS Faster
Bringing real-time capabilities to your product or software-as-a-service (SaaS) is no longer a nice-to-have; it’s a competitive necessity. Whether you're building a real-time payment platform, a patient monitoring system, or any product where instant data processing fuels great user experiences and artificial intelligence (AI)-driven innovation, Apache Kafka data streaming is likely at the core.
Shift Left or Stay Stuck (With Bad Data)
Moving data processing and governance closer to the source, aka shifting left in data integration, results in faster, easier access to reliable data when and where it’s needed—without wasteful and costly reprocessing of bad data.
Lenses K2K | See the universal Kafka to Kafka replicator in action
Lenses K2K is a new Kafka to Kafka replicator that gives any user the power to easily and reliably share real-time data across their business. Why is it different to the likes of MirrorMaker2, Confluent Cluster Linking and AWS Replicator? Vendor agnostic: Replicate data to and from any cluster or vendor, from Confluent Cloud and Redpanda to AWS and Azure Event Hubs. Self service: Full self-service capabilities to empower teams to replicate data, all while governed by multi-cluster Identity and Access Management and auditing.
Your AI Strategy Will Fail Without This
AI is only as good as the data behind it. That’s why 87% of IT leaders are relying on data streaming platforms to feed AI systems. Dig into how businesses like Reworked AI and @Notion are accelerating their AI initiatives with DSPs.
Confluent announces $200 million investment across its global partner ecosystem
As AI accelerates demand for data streaming platforms, the new investment will empower more partners to seize the $100 billion market opportunity.
Solving ETL Challenges with Apache Kafka, Confluent Tableflow, and Zero ETL
Operational and analytical estates have been separated since data warehouses were first introduced in the 1990s. The operational estate includes microservices, software-as-a-service (SaaS) apps, and enterprise resource planning systems (ERPs) that have become the beating heart of an organization. The analytical estate consists of the data warehouses, lakehouses, artificial intelligence (AI)/machine learning (ML) platforms, and other custom batch workloads that support business analysis and reporting.