New Confluent Cloud for Apache Flink® Capabilities Simplify Real-Time AI Development

Rhea-AI Summary

Confluent (NASDAQ:CFLT) has unveiled new capabilities in Confluent Cloud for Apache Flink® to simplify real-time AI application development. The announcement introduces three key features: Flink Native Inference, which enables running open-source AI models directly in Confluent Cloud; Flink search, providing a unified interface for querying multiple vector databases; and built-in machine learning functions that bring AI-driven analytics to Flink SQL.

These innovations address the complexity in building real-time AI applications, as highlighted by McKinsey's report showing 92% of companies plan to increase AI investments over the next three years. The new features aim to streamline workflows, enhance security, and make AI-powered streaming intelligence more accessible to development teams.

The company also announced additional Confluent Cloud advancements, including Tableflow, Freight Clusters, Confluent for Visual Studio Code, and the Oracle XStream CDC Source Connector, further expanding its data streaming capabilities.

Positive

• Introduction of Flink Native Inference reduces infrastructure costs and enhances security
• Unified interface for vector database access streamlines operations and reduces development complexity
• Built-in ML functions expand product accessibility to non-specialist teams, potentially increasing market reach
• Platform consolidation eliminates need for multiple tools, reducing operational overhead

Negative

• Features are currently only available in early access program, limiting immediate adoption
• Requires existing Confluent Cloud subscription to access new capabilities

Insights

Technology and AI Integration Expert

Confluent's new Flink capabilities represent a significant strategic advancement in the company's product portfolio, directly addressing the growing demand for streamlined AI development tools. By enabling native AI model inference within Confluent Cloud, the company eliminates a critical technical bottleneck that has historically required complex integrations and specialized expertise.

The unified search functionality across vector databases is particularly valuable as retrieval-augmented generation (RAG) becomes essential for LLM applications. This positions Confluent as an enabler of trustworthy AI by helping prevent hallucinations - a key concern for enterprise AI adoption. The built-in ML functions further democratize advanced analytics by making these capabilities accessible through familiar SQL interfaces.

What's most compelling about this announcement is how it aligns with broader market trends. With McKinsey reporting 92% of companies increasing AI investments, Confluent is targeting a high-growth opportunity by simplifying the connection between real-time data streams and AI - two technologies that naturally complement each other but have been technically challenging to integrate effectively.

For Confluent's business prospects, these capabilities create stronger differentiation in the data streaming market while potentially expanding their addressable market to include more AI-focused use cases and customers. The testimonial from Airy's CEO validates that these features solve genuine customer pain points around implementing AI agents with real-time organizational knowledge.

Flink Native Inference seamlessly runs AI models directly in Confluent Cloud for streamlined development

Flink search delivers a unified interface for querying vector databases, simplifying the data enrichment process

Built-in ML functions open the full potential of AI-driven analytics to non-data science specialists

BENGALURU, India--(BUSINESS WIRE)-- Confluent, Inc. (NASDAQ:CFLT), the data streaming pioneer, announced new capabilities in Confluent Cloud for Apache Flink^® that streamline and simplify the process of developing real-time artificial intelligence (AI) applications. Flink Native Inference cuts through complex workflows by enabling teams to run any open source AI model directly in Confluent Cloud. Flink search unifies data access across multiple vector databases, streamlining discovery and retrieval within a single interface. And new built-in machine learning (ML) functions bring AI-driven use cases, such as forecasting and anomaly detection, directly into Flink SQL, making advanced data science effortless. Together these innovations redefine how businesses can harness AI for real-time customer engagement and decision-making.

"Building real-time AI applications has been too complex for too long, requiring a maze of tools and deep expertise just to get started," said Shaun Clowes, Chief Product Officer at Confluent. "With the latest advancements in Confluent Cloud for Apache Flink, we’re breaking down those barriers—bringing AI-powered streaming intelligence within reach of any team. What once required a patchwork of technologies can now be done seamlessly within our platform, with enterprise-level security and cost efficiencies baked in."

The AI boom is here. According to McKinsey, 92% of companies plan to increase their AI investments over the next three years. Organizations want to seize this opportunity and capitalize on the promises of AI. However, the road to building real-time AI apps is complicated. Developers are juggling multiple tools, languages, and interfaces to incorporate ML models and pull valuable context from the many places that data lives. This fragmented workflow leads to costly inefficiencies, slowdowns in operations, and AI hallucinations that can damage reputations.

Simplify the Path to AI Success

“Confluent helps us accelerate copilot adoption for our customers, giving teams access to valuable real-time, organizational knowledge,” said Steffen Hoellinger, Co-founder and CEO at Airy. “Confluent’s data streaming platform with Flink AI Model Inference simplified our tech stack by enabling us to work directly with large language models (LLMs) and vector databases for retrieval-augmented generation (RAG) and schema intelligence, providing real-time context for smarter AI agents. As a result, our customers have achieved greater productivity and improved workflows across their enterprise operations.”

As the only serverless stream processing solution on the market that unifies real-time and batch processing, Confluent Cloud for Apache Flink empowers teams to effortlessly handle both continuous streams of data and batch workloads within a single platform. This eliminates the complexity and operational overhead of managing separate processing solutions. With these newly released AI, ML, and analytics features, it enables businesses to streamline more workflows and unlock greater efficiency. These features are available in an early access program, which is open for signup to Confluent Cloud customers.

• Flink Native Inference: Run open source AI models in Confluent Cloud without added infrastructure management.
  When working with ML models and data pipelines, developers often use separate tools and languages, leading to complex and fragmented workflows and outdated data. Flink Native Inference simplifies this by enabling teams to run open source or fine-tuned AI models directly in Confluent Cloud. This approach offers greater flexibility and cost savings. Plus, the data never leaves the platform for inference, adding a greater level of security.

• Flink search: Use just one interface to access data from multiple vector databases.
  Vector searches provide LLMs with the necessary context to prevent hallucinations and ensure trustworthy results. Flink search simplifies accessing real-time data from vector databases, such as MongoDB, Elasticsearch, and Pinecone. This eliminates the need for complex ETL processes or manual data consolidation, saving valuable time and resources, while ensuring that data is contextual and always up to date.

• Built-in ML functions: Make data science skills accessible to more teams.
  Many data science solutions require highly specialized expertise, creating bottlenecks in the development cycles. Built-in ML functions simplify complex tasks, such as forecasting, anomaly detection, and real-time visualization, directly in Flink SQL. These features make real-time AI accessible to more developers, enabling teams to gain actionable insights faster and empowering businesses to make smarter decisions with greater speed and agility.

“The ability to integrate real-time, contextualized, and trustworthy data into AI and ML models will give companies a competitive edge with AI,” said Stewart Bond, Vice President, Data Intelligence and Integration Software at IDC. “Organizations need to unify data processing and AI workflows for accurate predictions and LLM responses. Flink provides a single interface to orchestrate inference and vector search for RAG, and having it available in a cloud-native and fully managed implementation will make real-time analytics and AI more accessible and applicable to the future of generative AI and agentic AI.”

Additional Confluent Cloud Features

Confluent also announced further advancements in Confluent Cloud, making it easier for teams to connect and access their real-time data, including Tableflow, Freight Clusters, Confluent for Visual Studio (VS) Code, and the Oracle XStream CDC Source Connector. Learn more about these new features in this blog post.

About Confluent

Confluent is the data streaming platform that is pioneering a fundamentally new category of data infrastructure that sets data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion—designed to be the intelligent connective tissue enabling real-time data from multiple sources to constantly stream across an organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven back-end operations. To learn more, please visit www.confluent.io.

As our road map may change in the future, the features referred to here may change, may not be delivered on time, or may not be delivered at all. This information is not a commitment to deliver any functionality, and customers should make their purchasing decisions based on features that are currently available.

Confluent^® and associated marks are trademarks or registered trademarks of Confluent, Inc.

Apache^®, Apache Kafka^®, Kafka^®, Apache Flink^®, and Flink^® are registered trademarks of the Apache Software Foundation in the United States and/or other countries. No endorsement by the Apache Software Foundation is implied by the use of these marks. All other trademarks are the property of their respective owners.

View source version on businesswire.com: https://www.businesswire.com/news/home/20250318242614/en/

Media Contact:

Natalie Mangan

pr@confluent.io

Source: Confluent, Inc.

FAQ

What are the three new AI capabilities introduced in Confluent Cloud for Apache Flink?

Confluent Cloud introduced Flink Native Inference for running AI models directly in the cloud, Flink search for unified vector database querying, and built-in ML functions for AI-driven analytics in Flink SQL.

How does Flink Native Inference benefit CFLT users?

It allows teams to run open source or fine-tuned AI models directly in Confluent Cloud, reducing workflow complexity, improving security by keeping data within the platform, and offering cost savings.

What problem does Confluent's Flink search feature solve?

Flink search simplifies access to real-time data from multiple vector databases (MongoDB, Elasticsearch, Pinecone) through a single interface, eliminating complex ETL processes and ensuring up-to-date data context.

How do Confluent's new built-in ML functions make AI more accessible?

The built-in ML functions allow teams to perform complex tasks like forecasting and anomaly detection directly in Flink SQL, making real-time AI accessible to developers without specialized data science expertise.