Systems | Development | Analytics | API | Testing

AI agents are only as good as the data they can access. In this video, we explore the Model Context Protocol (MCP) and how it creates a bridge between AI models and Apache Kafka. Learn how MCP allows AI agents to securely produce, consume, and manage Kafka topics in real-time—transforming your event streams into actionable context for LLMs.

Learn more: speedscale.com.

In this interview, Stefan Williams, VP of Corporate Development, shares Snowflake Ventures’ top priorities and why the pace of innovation across the AI Data Cloud matters for startups. Learn how native platform capabilities, including Cortex Search, Cortex Analyst, and the Cortex REST API, help reduce complexity and unlock faster innovation. The Snowflake ecosystem is where startups gain secure, trusted access to data and the opportunity to work with some of the world’s largest customers.

Learn how business leaders use Snowflake Intelligence to eliminate operational lag and turn fragmented data into confident decisions at enterprise speed. Snowflake chief revenue officer Mike Gannon shows how a single intelligent agent delivers trusted, multi modal analysis across emails, documents, spreadsheets, images, video, and more. See how Snowflake Intelligence uncovers the why behind critical moments, accelerates revenue and pipeline insight, and keeps every query secure and governed within your existing framework.

BDD (Behavior-Driven Development) is an agile approach comprising three key practices: discovery, formulation, and automation. This methodology aims to improve software development by reducing ambiguities, enhancing collaboration, and creating living documentation. In BDD, acceptance tests stay stable because business rules change less than the UI. They can be written before the UI and describe business actions that guide development, serving as the application’s business vocabulary.

They started with basic test automation using record-and-playback, then expanded into BDD and full automation with Katalon. As their test suites grew, we helped them scale, parallelizing tests, executing them faster, and consolidating reporting, making it easier to manage large volumes of tests and meet delivery requirements.

Learn how geographic data science helps cities understand and address urban inequality, sustainability, and resilience.

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This demonstration shall suggest those baby steps that should encourage most of us (the testers) to inculcate the habit of exploring* GenAI and LLMs. The exploration shall help understand why, what, where, when and how we should use these rapidly moving technologies to bring efficiency and better thinking in our day-to-day testing work.

In 2026, the gap between companies "testing" AI and companies "running" on AI has become a chasm. In this segment of The Data Chief, Paul Baier, CEO and Co-Founder of @GAIInsights, explains why the honeymoon phase of Generative AI is over and the era of Agentic AI has officially arrived. Paul breaks down how leading enterprises are pulling ahead by moving beyond simple chatbots to autonomous agents that can plan, reason, and execute complex workflows. If you want to know how to reshape your enterprise operating model to stay competitive, this is the field guide you’ve been looking for.