Snow Leopard AI
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AI’s true platform shift + 3 spicy takes
AI keeps promising to deliver autonomous reasoning systems...that's not the reality though
Jul 24
1
June 2025
Structured data for AI: Snow Leopard vs. MCP
Snow Leopard, with its semantic data intelligence, significantly outperforms LLM+MCP (95% accuracy vs. 74%, for real-world datasets)
Jun 30
•
Deepti Srivastava
4
AI agents need live business data, not more intelligence
Simply put, for AI agents to be part of critical / user-facing workflows, they need real-time access to the “crown jewels” of a business...structured…
Jun 17
1
RAG just doesn’t cut it for structured data for AI
RAG (Retrieval Augmented Generation) has become the de facto design pattern for AI applications. But it just doesn't cut it for most operational…
Jun 13
•
Deepti Srivastava
2
Structured data is broken for AI!
As soon as you try to convert that POC into a production app, things fall apart fairly quickly
Jun 2
•
Deepti Srivastava
6
May 2025
Why most enterprise GenAI prototypes fail
They ignore structured data problems! If your structured queries aren’t reliable, no LLM magic will fix bad retrieval or broken joins.
May 22
What it will take for AI agents to address real-time customer concerns
Most teams are stuck wiring agents into fragmented APIs, exporting data into lakes, or building syncs with vector stores that quickly go stale.
May 8
April 2025
Enterprise AI’s systems architecture problem
Instead of unlocking data, most AI initiatives recreate old problems: brittle pipelines, static snapshots, and expensive ETL jobs.
Apr 29
Beyond ETL: Why scalable AI systems need live operational data
Live data access is the only scalable way to support production-grade AI systems.
Apr 22
Why enterprise AI can't answer high value business questions—and how to change that
Disconnected tools, brittle pipelines, and rigid logic falls apart under real-world conditions.
Apr 14
How the things we build impact the world
Most AI workflows buckle under static assumptions, rigid pipelines, and layers of hidden complexity.
Apr 8
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