Deepti Srivastava on Agentic AI, Native Data Connectors, and Real-Time Data Aggregation
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Deepti Srivastava is the Founder and CEO of Snow Leopard. We dive into Snow Leopard’s innovative approach to data integration, exploring its live data access model that bypasses traditional ETL pipelines to offer real-time data retrieval directly from source systems. This kind of solution will be critical for AI and agentic applications moving forward, especially those relying on live data to perform high-stakes, real-time tasks. We discuss the architecture’s impact on AI application integration, scalability, and deployment in regulated industries. The conversation also covers market relevance, business use cases, and the build vs. buy decision, making this episode essential for anyone involved in AI-driven data management.
Interview highlights – key sections from the video version:
- Introduction to Snow Leopard and its Mission
- The Value of Connecting Operational Data with AI
- Challenges of Traditional ETL and the Need for Real-Time Access
- Enterprise Data Complexity and the Shift Towards Agentic AI
- Growing Recognition of Operational Data’s Importance for AI
- Brute Force Solutions and Their Limitations
- Introducing Snow Leopard’s Intelligent Data Retrieval System
- Two Modes of Snow Leopard: Direct Data Retrieval and BYO-LLM
- The Importance of Eliminating Pipelines for Real-Time Data
- Why Direct Access to Operational Data is Essential for Agentic Applications
- Advantages of Using Snow Leopard Over Building Custom Solutions
- Connector Management and Handling API Changes
- Snow Leopard’s Early Use Cases and Internal BI Applications
- Snow Leopard’s Roadmap and Future Plans for Open Source Components
Related content:
- A video version of this conversation is available on our YouTube channel.
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