Session Overview
Learn how StreamNative and RisingWave combine forces to deliver rich, real-time context for live streaming data and autonomous AI agents.
In this session, Rayees Pasha (CPO at RisingWave Labs) and Qiang Zhao (Software Engineer at StreamNative) break down the architecture behind streaming SQL, materialized views, and event-driven AI agent workflows. Discover how the StreamNative Cloud SQL Workspace simplifies the pipeline from event ingestion to instant analytical serving without traditional batch delays.
What You'll Learn
- Why real-time context is critical for agentic AI and live data systems
- RisingWave’s distributed SQL streaming engine architecture and PostgreSQL compatibility
- How to use StreamNative Cloud SQL Workspace to query streams directly
- Building continuous materialized views and streaming ETL pipelines
- Real-world IoT walkthrough: An automated monitoring and alert loop using AI agents and Kafka topics
- Closing the feedback loop with persistent event streams and human-in-the-loop validation
Chapters
- 00:00 — Introduction: Why live context matters for agentic AI
- 03:24 — What is RisingWave: Architecture, streaming SQL, and storage
- 11:32 — Streaming ETL vs. streaming analytics pipelines
- 14:28 — StreamNative Cloud SQL Workspace overview
- 16:50 — Live IoT demo: Real-time sensor monitoring, risk scoring, and AI agents
- 20:30 — Autonomous agent loops, event replay, and human feedback
- 22:04 — Audience Q&A and session wrap-up
