Confluent, an IBM company, has new capabilities in Confluent Intelligence and Confluent Cloud that streamline how real-time artificial intelligence (AI) applications are built and secured.
Sean Falconer, head of AI at Confluent, explains
“Most AI projects fail before they reach a single customer because the data layer breaks down. 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.”
The problem is widespread, according to a McKinsey report that says,
“… eight in ten companies cite data limitations as a roadblock to scaling agentic AI.”
Root causes are often tied to security teams blocking data from entering AI pipelines due to exposure risks and developers losing hours to tool-switching to inspect and manage the data streams their AI depends on. The resulting slow, manual process turns what should be a fast iteration cycle into a bottleneck.
Confluent Cloud and Confluent Intelligence new capabilities include:
• Natural language operations:
Developers can use Confluent MCP as a control plane, allowing AI to build, manage, and debug streaming operations using natural language. Agent Skills add a second layer, encoding best practices and workflows so those operations are executed consistently and in line with organisational standards.
Generally available for Confluent Cloud.
• Automated data privacy:
A new built-in ML function for PII detection and redaction protects sensitive information directly in Flink SQL, without custom code, external services, or moving data to a warehouse first. It can unlock more AI use cases across highly regulated industries such as financial services, healthcare, and insurance.
Available in early access for Confluent Intelligence.
• Secure connectivity:
Support for Azure Private Link ensures that AI workloads stay off the public internet with secure, private paths to calling external models and querying external tables. Now, Flink jobs can securely connect to Azure-hosted services such as Azure OpenAI, Azure SQL, and Cosmos DB over Microsoft’s private backbone.
Generally available on Confluent Cloud.
• Unified engineering workflows:
The free open source dbt adapter brings Flink SQL on Confluent Cloud into dbt, the industry-standard framework data that engineers use to build and manage data pipelines. Teams can define, test, and deploy streaming pipelines using the same dbt commands and project structure they currently rely on. This lowers the barrier to Flink adoption and makes it easier to extend existing data workflows into real-time use cases.
Generally available on Confluent Cloud.
• Flexibility with additional model support:
Confluent supports TimesFM models for robust anomaly detection as well as Anthropic and Fireworks AI models, which developers can directly use in Flink stream processing workflows to build sophisticated real-time AI applications.
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