Systems | Development | Analytics | API | Testing

Qlik and Snowflake Cortex AISQL - Show Me How to Build It

Ready to implement Snowflake Cortex AI-SQL in your Qlik environment? This technical walkthrough provides step-by-step guidance for building AI-powered analytics applications using two proven architectural approaches. Learn how to leverage Qlik's partial reload functionality for user-triggered AI queries, and discover the advanced analytics connector method for creating fully responsive, selection-aware AI interactions. Master the techniques for passing aggregated data alongside questions to ensure security compliance, honor role-based access controls, and maintain multiple versions of truth across different departments.

Qlik and Snowflake Cortex AISQL - Show Me How It Works

See Snowflake Cortex AI-SQL in action with comprehensive demonstrations across the entire analytics lifecycle. This deep-dive video showcases real-world implementations including sentiment analysis on healthcare survey data, emotional classification using the Plutchik Wheel of Emotions, and sophisticated prompt engineering for actionable business recommendations. Watch how Qlik operationalizes these AI capabilities within data pipelines, storing enriched insights as structured data that any user can access—no SQL or data science expertise required.

Qlik and Snowflake Cortex AISQL - Show Me What's Possible

Discover how Qlik and Snowflake Cortex AI-SQL are revolutionizing data enrichment and analytics accessibility. This introductory video explores how SQL-savvy data engineers can invoke powerful AI functionality at scale—without complex data science programming—using Snowflake's SQL wrapper for AI capabilities. Learn how Qlik operationalizes Cortex AI-SQL across your entire data pipeline, from enriching data in-flight through Qlik Talend Cloud to enabling business users to interact with AI-powered insights through Qlik Sense analytics.

Multi-agent AI systems need infrastructure that can keep up

When you're building agentic AI applications with multiple agents working together, the infrastructure challenges show up fast. Agents need to coordinate, users need visibility into what's happening, and the whole system needs to stay responsive even as tasks branch out across specialised workers. We built a multi-agent travel planning system to understand these problems better. What we learned applies well beyond holiday booking.

Building Bitrise's AI platform: Scaling AI features across teams

This is the fourth and final installment in our series about bringing AI to Bitrise. In Part 1, we explained why we built our own AI coding agent. Part 2 covered our browser-integrated AI Assistant. Part 3 detailed how we brought AI to the Bitrise Build Cloud. In this final post, we'll explore how we unified these efforts into a cohesive AI Platform.

Trust Through Transparency: AI Answers You Can Verify with Spotter

Trust, verified. Powered by Spotter. Why settle for AI hallucinations when you can have governed truth? Spotter maps natural language to business tokens, giving you 100% transparency down to the code. Experience AI you can actually explain. Discover what Spotter can do.

Preparing for Agentic AI: Top Trends in Data and AI 2026

In this season premiere of The Data Chief podcast, host Cindi Howson sits down with three industry leaders to unpack what’s next for AI, and the concrete moves data and AI leaders need to make in 2026—many of which are detailed in ThoughtSpot’s Top Data & AI Trends of 2026 ebook. Get ready for a deep dive into: Consider this your field guide to navigating AI in 2026.

What is a MCP Gateway? The Missing Piece for Enterprise AI Infrastructure

AI agents are spreading across organizations rapidly. Each agent needs secure access to different Model Context Protocol (MCP) servers. Authentication becomes complex. Scaling creates bottlenecks. The dreaded "too many endpoints" problem emerges. You face a classic AI infrastructure headache. The numbers tell the story. Organizations using AI in at least one business function jumped from 55% to 78% in just one year. Generative AI usage specifically rose from 33% in 2023 to 71% in 2024.

KAi Just Got a Major Upgrade, Powered by the New Kong Konnect MCP Server

KAi, the AI assistant inside Kong Konnect, just got significantly more capable. Today, we're announcing an enhanced beta version powered by the new Kong Konnect MCP Server — a shared infrastructure layer that also opens up your API platform to IDE copilots and custom agents. The result? KAi can now do things it couldn't before, and those same capabilities are available wherever you work. If you've used KAi before, you'll notice the difference immediately.

How to share test builds using Bitrise Release Management

Discover how to use Bitrise Release Management to quickly distribute iOS and Android builds to your testers from a single interface. See how to find your builds (sourced natively from Bitrise CI or via API), organize testers into specific groups, share the installation link, set up automatic email notifications for new builds, and more.