Kishore Gopalakrishna, Cofounder and CEO, StarTree, shares what he expects from the coming year.
The Dawn of Real-Time RAG for Dynamic Insights in 2025
We’ll see the emergence of real-time Retrieval-Augmented Generation (RAG) as organizations push beyond batch processing limitations. Today’s RAG implementations primarily rely on static LLMs paired with batch vector databases, which augment responses with pre-processed, stale data. While effective for many applications, this approach falls short for dynamic use cases that require real-time information updates, such as logistics optimization, personalized video game assistants, or financial risk monitoring. Real-time RAG will bridge this gap by integrating LLMs with real-time data streams and event-driven architectures, enabling models to access and leverage the freshest data during generation. This shift will unlock powerful, timely insights in scenarios where up-to-the-second context is critical, making 2025 a pivotal year for real-time augmented intelligence.
From Streams to Insights: 2025 Marks the Real-Time Analytics Revolution
Real-time analytics will finally hit its stride as organizations complete the “last mile” of their data architecture. Over the past few years, businesses have focused heavily on building out event streaming systems like Apache Kafka, ensuring that data flows smoothly in real-time. However, many are now realizing that traditional analytic endpoints, such as data warehouses and batch-based solutions, are unable to fully harness the potential of these streams. These legacy systems simply can’t deliver the instant insights needed in today’s fast-paced environment. In 2025, organizations will prioritize real-time analytics platforms that can process, analyze, and act on data instantly, closing the loop and unlocking the true value of their streaming architectures. This shift will enable innovative use cases such as hyper-personalized customer experiences, real-time external-facing data products, and adaptive risk management systems – far beyond the capabilities of traditional solutions.
2025 Will be the Year Observability Stacks Break Apart
Observability stacks are likely to become more disaggregated as companies move away from monolithic, all-in-one solutions to specialized, best-of-breed tools. As data volumes and complexity grow, teams will demand more flexibility in how they monitor and manage their infrastructure. This shift will result in observability stacks breaking into distinct layers—such as metrics, logs, traces, and events—each optimized with dedicated solutions. Disaggregation will enable more tailored observability strategies, greater scalability and cost efficiency, as businesses can choose the most effective tools for specific parts of their systems rather than relying on a single, unified platform.
