Confluent announced new capabilities in Confluent Intelligence and Confluent Cloud to help organisations build and secure real-time artificial intelligence applications at scale.
“Most AI projects fail before they reach a single customer because the data layer breaks down,” said Sean Falconer, head of AI at Confluent. “Teams have the models and the mandate, but security risks and fragmented data stop them from shipping. We’re fixing that by making the streaming layer the foundation for secure, production-ready AI.”
Building and securing real-time AI applications at scale
The new features aim to address challenges that prevent AI projects from moving into production, especially around fragmented data systems, security risks, and operational complexity.
The new features include:
- A fully managed Model Context Protocol server and Agent Skills that allow AI systems to manage streaming operations using natural language.
- Integration of Apache Flink pipelines with dbt, enabling developers to use existing engineering workflows for real-time data applications
- Automated personally identifiable information detection and redaction directly within Flink SQL for industries with strict compliance requirements, including finance, healthcare, and insurance
- Additional support for Azure Private Link, allowing AI workloads to securely connect to services such as Azure OpenAI, Azure SQL, and Cosmos DB without traversing the public internet.
- Additional model support was introduced for TimesFM, Anthropic, and Fireworks AI to enable advanced anomaly detection and real-time AI processing.
