Streaming data for real-time AI applications

Most enterprises are exploring how real-time AI can reshape its operations, helping them make faster, smarter decisions with greater accuracy. Some organizations are already using it in targeted ways — like fraud detection, predictive maintenance, or personalized customer experiences — while others are still experimenting with pilot projects and proofs of concept.

In between these approaches is the need to build end-to-end real-time AI systems capable of handling massive streams of data as it happens. This is where organizations can harness AI for business impact, but also where challenges such as latency, resource management, and real-time inference become critical to solve.

If you’re exploring real-time AI and wondering how to bring it to life in your organization, this report will guide you through:

• What real-time AI is and how it works
• The benefits of real-time AI across industries and use cases
• The challenges of designing, deploying, and scaling low-latency AI systems
• How to get started with real-time AI

Download the report to learn how to build scalable and low-latency AI systems that aren’t just effective for your business, but easy and efficient for the teams managing them.