Technology

Most AI projects fail not because of bad models, but because of bad data. Siloed, stale, and locked in batch pipelines, enterprise data isn’t AI-ready. This post breaks down the data liberation problem and how streaming solves it—freeing real-time data so AI can actually deliver value.

The concept of “shift left” in building data pipelines involves applying stream governance close to the source of events. Let’s discuss some tools (like Terraform and Gradle) and practices used by data streaming engineers to build and maintain those data contracts.

This article explores how event-driven design—a proven approach in microservices—can address the chaos, creating scalable, efficient multi-agent systems. If you’re leading teams toward the future of AI, understanding these patterns is critical. We’ll demonstrate how they can be implemented.

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.

Learn how to use the recently launched Provisioned Mode for Lambda’s Kafka ESM to build high throughput Kafka applications with Confluent Cloud’s Kafka platform. This blog also exhibits a sample scenario to activate and test the Provisioned Mode for ESM, and outline best practices.

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.

Before deploying agentic AI, enterprises should be prepared to address several issues that could impact the trustworthiness and security of the system.

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 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.

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.

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.

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.

Confluent Cloud 2024 Q4 adds private networking and mTLS authentication, follower fetching, Flink updates, WarpStream features to support migration and governance, and more!