New in Confluent Cloud: Making Data & Pipelines Accessible for AI-Ready Streaming | Learn More
Confluent announces the General Availability of Queues for Kafka on Confluent Cloud and Confluent Platform with Apache Kafka 4.2. This production-ready feature brings native queue semantics to Kafka through KIP-932, enabling organizations to consolidate streaming and queuing infrastructure while...
Confluent's AI developer tools are now GA: an open-source local MCP server, a managed MCP server, and Agent Skills. Together they give AI coding assistants direct access to your streaming platform — the tools to act on it and the domain knowledge to build correctly.
Explore new Confluent Intelligence features: enhanced querying with Real-Time Context Engine, PII detection, sentiment analysis, and support for TimesFM, Anthropic, and Fireworks AI models.
Confluent Cloud Freight clusters are now Generally Available on AWS. In this blog, learn how Freight clusters can save you up to 90% at GBps+ scale.
Learn how an e-commerce company integrates the data from its Stripe system with the Pinecone vector database using the new fully managed HTTP Source V2 and HTTP Sink V2 Connectors along with Flink AI model inference in Confluent Cloud to enhance its real-time fraud detection.
Confluent's advanced security and connectivity features allow you to protect your data and innovate confidently. Features like Mutual TLS (mTLS), Private Link for Schema Registry, and Private Link for Flink, not only bolster security but also streamline network architecture and improve performance.
Read this Data in Motion Tour recap to get highlights and key insights from Singaporean business leaders leveraging data streaming in their organizations.
Before deploying agentic AI, enterprises should be prepared to address several issues that could impact the trustworthiness and security of the system.
Confluent’s Create Embeddings Action for Flink helps you generate vector embeddings from real-time data to create a live semantic layer for your AI workflows.
We built an AI-powered tool to automate LinkedIn post creation for podcasts, using Kafka, Flink, and OpenAI models. With an event-driven design, it’s scalable, modular, and future-proof. Learn how this system works and explore the code on GitHub in our latest blog.
FLIP 304 lets you customize and enrich your Flink failure messaging: Assign types to failures, emit custom metrics per type, and expose your failure data to other tools.
In our latest Confluent Champion, staff solutions engineer Maria Berinde-Tampanariu shares how Confluent fosters a culture of motivation and growth.
Learn how Flink enables developers to connect real-time data to external models through remote inference, enabling seamless coordination between data processing and AI/ML workflows.
Allium provides real-time, accessible blockchain data for analytics and business teams with the help of data streaming. Learn how here.
Effective supply chain management relies on the ready availability of well-governed, real-time data. Learn how Confluent facilitates supply chain optimization.
The rise of agentic AI has fueled excitement around agents that autonomously perform tasks, make recommendations, and execute complex workflows. This blog post details the design and architecture of PodPrep AI, an AI-powered research assistant that helps the author prepare for podcast interviews.