Systems | Development | Analytics | API | Testing

Unlocking Intelligence: How AI-Assisted Insights Transform Embedded Analytics

The data visualization landscape is experiencing a seismic shift. No longer is it enough to simply present dashboards filled with colorful charts and metrics. Today's decision-makers need something more powerful: the ability to understand what their data actually means, why trends are occurring, and what actions to take next.

Build an Interactive Dashboard in 5 Minutes with Kai

Data Apps are interactive web applications that run directly in your Keboola project. They let you visualize, explore, and interact with your data without needing external BI tools. Think of Data Apps as your custom dashboards, built exactly how you need them. Now, let's see how Kai makes building Data Apps effortless.

AI won't fix your SaaS company

Right now, many SaaS leaders are wondering how AI will change building and scaling software companies? AI is transforming how we build software, how teams operate, and how quickly companies launch new products. According to Adam Robinson, founder and CEO of Retention.com, there’s something that most leaders overlook. Your problems won’t get solved by AI but by product-market fit.

Evolve25: AI Readiness and the Future of Intelligent Enterprises with AWS and Cloudera

Discover why the transition from Generative AI to Agentic AI is the key to unlocking $40M+ in business value, even for non-technical users via Cloudera Agent Studio. Learn how the AWS and Cloudera partnership solves the "Data Readiness" challenge by bringing AI to the data, whether on-prem or in the cloud. This session covers critical strategies for AI governance, hybrid architecture, and the shift from task-based tools to autonomous digital workforces.

Why ELT Can't Keep Up in the Era of High-Scale Data Engineering

While winning in artificial intelligence (AI) is critical to the future of business, old-school analytics—visualizations, dashboards, and infrequent reports—are still core to an organization's data needs. Behind the scenes, this analytics ecosystem remains heavily hydrated by batch-based ELT data integration. For a long time, this made perfect sense, as data sources were fewer, data volumes were manageable, and analytics consumers were limited.

Why Databox MCP Wins for AI Analytics Over Individual Connector MCPs

The Model Context Protocol (MCP) has given AI assistants something they’ve never had before: a standardized way to pull live data from external systems. Instead of just generating text, an AI agent can now query your CRM, check ad performance, or pull revenue numbers in real time. The industry’s response has been predictable. Every major platform is racing to build their own MCP server.