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Traditional data infrastructures were never designed for real-time intelligence.
At best, they supported batch analytics—overnight ETL processes, siloed systems, and static reporting tools. Today, many large enterprises, particularly in industries like retail and consumer packaged goods, are still attempting to deploy AI on these outdated foundations. The result? Even the most advanced AI initiatives are stalling. Models are only as effective as the data they consume, and too often, that data arrives late, is fragmented, or lacks completeness, undermining the very insights organizations seek to unlock.
A joint technical reference architecture developed by Striim and Tata Consultancy Services (TCS) is tailored for technical leaders addressing the operational and architectural challenges of enterprise AI adoption. It provides a clear blueprint for building cloud-native, real-time, and AI-ready data pipelines—proven at scale in some of the world’s most complex enterprise environments.