WEBINAR "Building Context-Aware AI Agents with Real-Time Data"

Just like we don't put crude oil in a car—we refine it into gasoline—AI can't run on raw data. It needs continuous, refined context. Serving fresh context is the missing architectural layer for reliable AI. In this session, learn how IBM, Confluent Intelligence, and Google Cloud turn operational data into fresh context for AI agents to take the right action at the right time. See how Confluent’s data streaming platform turns operational data into automated decisions, and how Google Cloud adds a layer of real-time investigation and explanation on top—all grounded in context that reflects the current state of the business. We'll demo a real-time architecture for anomaly detection and investigation—streaming racing telemetry through Confluent's Real-Time Context Engine, where a Confluent Streaming Agent detects anomalies and recommends pit timing in real time. You'll then see a Gemini agent in Google Antigravity, connected via MCP, investigate those decisions and explain the reasoning behind them, with governed data synced to BigQuery for historical record and analysis. You'll leave with practical, streaming-native patterns to move from brittle pipelines and demos to production-grade AI on Google Cloud while reducing TCO. Speakers: • Karan Sachdeva, IBM • Sean Falconer, Confluent • Sohrab Rahimi, Google Cloud ​Some useful links: • Get free access to more talks/trainings like this at the Ai+ Training platform: https://aiplus.training/ • ODSC blog: https://opendatascience.com/ • Slack Channel: https://hubs.li/Q038cQBy0 • Code of conduct: https://odsc.com/code-of-conduct/