Systems | Development | Analytics | API | Testing

As organizations adopt specialized streaming technologies, real-time data is increasingly distributed across multiple domains, clouds, and locations. With the rapid evolution of streaming-dependent technologies, companies need the ability to pivot between providers almost instantly to spread risk and maintain performance (just look at the January DeepSeek-R1 LLM news).

Buckle up, we’re past the AI hype. Now, it’s about making intelligent systems that act on our behalf. In 2025, AI isn’t just a tool– it’s becoming our core way of operating, powered by real-time data. How we stream, manage and monetize that data will define the next generation of business. Here, we zoom into four examples of what autonomous real-time intelligence could look like in the coming year.

The need to democratize and share data inside and outside your organization, as a real-time data stream, has never been more in demand. Treating real-time data as a product, and adopting Data Mesh practices, is the way forward. Here, we explain the concept through a real-life example of an airline building applications that process data across different domains.

Democratizing and sharing data inside and outside your organization, as a real-time data stream, has never been more in demand. Treating data as-a-product and adopting Data Mesh practices is leading the way. Here, we explain the concept through a real-life example of an airline building applications that process data across different domains.