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Rahul Agarwal

Founder | Agentic AI... • 21d

AI initiatives don’t fail because of models. They fail because enterprise data isn’t ready. Modernization isn’t just cloud migration. Data must be usable, trusted, and AI-ready. Data volumes are exploding. Streaming is replacing batch. AI needs clean, contextual, vector-ready data. Regulation is tightening. Costs are under scrutiny. Weak data architecture blocks AI at scale. Leading organizations follow a clear path: Build data mesh or fabric layers. Adopt lakehouse platforms. Enable real-time streaming. Embed governance and lineage. Operationalize AI. Then scale. The impact is real. Decisions are faster. Costs decline. Revenue grows. Modernization is now a board-level priority. The real question is speed.

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1 Reply

Techinsiteai

𝙴𝚗𝚝𝚛𝚎𝚙𝚛𝚎𝚗𝚎... • 1y

AI is capable of analyzing millions of data points in seconds, optimizing ad campaigns in real-time.

1 Reply

Anonymous
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JSW • 1y

I have an idea to build Indian alternative to Scale ai, mechanical turk for outsourcing data labeling work for AI training. Focusing on dataset creation on Indian context. IMO this is a necessity rn as most AI models are trained on western data sou

3 Replies

Vansh Khandelwal

Full Stack Web Devel... • 1m

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emiley Madison

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White-label video streaming is a ready-made platform that businesses can brand as their own to host, stream, and monetize video content. It offers full customization without revealing the original service provider’s identity. For More Info Visit http

Ayush Maurya

AI Pioneer • 1y

"Synthetic Data" is used in AI and LLM training !! • cheap • easy to produce • perfectly labelled data ~ derived from the real world data to replicate the properties and characteristics of the rela world data. It's used in training an LLM (LLMs