Ververica sits at the forefront of data processing. As the original creators of Apache Flink®, the evolution of the streaming data landscape is nothing new to us. Our mission is to transform raw data into actionable insights, driving business value and growth.
We’ve helped our clients disrupt this space since as early as 2017, which saw the launch of Flink Machine Learning (Flink ML). Flink ML offers the market mature support for approximate nearest neighbor search and clustering out of the box, in addition to recommendation and graph queries commonly used in the AI space
The Evolution of the AI Landscape
The AI landscape has evolved significantly, with the advent of technologies like ChatGPT becoming mainstream. However, AI has been making waves much earlier than this. Our VERA engine, fully compatible with Apache Flink, unifies batch and real-time data processing, a crucial capability for AI use cases. Unlike ChatGPT (which relies on historical data), VERA gives you the choice to tap into real-time data on Data Lake-sized deployments.
During a recent panel discussion with NASDAQ, our CEO, Alex Walden, highlighted the transformative impact of real-time data on AI. He emphasized that AI applications, such as predictive maintenance, recommendation systems, and real-time decision-making, thrive on up-to-date information. While traditional models are trained on historical data, VERA allows for continuous updates with new data in real-time, ensuring AI systems remain relevant and accurate.
The Value of Flink Machine Learning
Flink MLis a cornerstone of Ververica's Streaming Data Platform which provides robust support for a wide range of AI applications. With Flink ML integrated with our VERA engine, Ververica's users can seamlessly scale their applications to address big data challenges with ease. Whether it's recall-augmented generation against pre-vectorized datasets, predictive maintenance on MQTT streams, or user profile-based recommendations, VERA offers the flexibility and real-time processing capabilities required for advanced AI solutions. Our AI solutions have significantly impacted various industries. For example, a large European bank utilizes our technology for real-time fraud detection, showcasing the power of Flink ML in critical applications.
"We are helping companies train their AI models at the right time with the right data."
Alex Walden, CEO, Ververica
Data Privacy, Risk Management, and Ethical Considerations
Our commitment to data privacy and compliance further distinguishes Ververica in the AI market. No matter which Streaming Data Platform deployment option you choose, you can be confident the data is secure. Review our Trust Center portal to learn more about our stringent privacy, security, and compliance standards, including ISO27k, SOC2, and PCI DSS certifications.
Our approach to risk management focuses on data integrity and consistency. By ensuring traceability and transparency, we help users understand the data origins and decision-making processes within AI systems. This is crucial for regulatory compliance and mitigating risks associated with AI, such as bias and erroneous outputs.
Ethical considerations are integral to our AI development and deployment too. We prioritize consent, transparency, and control, enabling users to understand and manage how AI uses their data. Our solutions are designed to comply with regulations like GDPR, offering opt-in/opt-out options and robust security measures.
Conclusion
Our future plans are simple: We will remain dedicated to advancing AI and data streaming technologies for further enterprise solutions. Our values for enhancing transparency, compliance, and risk management in AI applications will forever be at the forefront. By ensuring consistent, accurate, and timely data, we aim to unlock AI's full potential, helping businesses make informed decisions and achieve greater efficiency.
