Don’t settle for blind spots

AI Analytics & Agentic AI: Definition, Benefits, and Real-World Examples

This 2025 guide to AI analytics covers definition, architecture, and examples—plus how agentic AI with a semantic layer and orchestrated AI agents turns insights into approved action, reducing time-to-action and delivering measurable impact.

Agents vs. Workflows. Why not both?

AI agents and workflow automation are often treated as competing approaches, but the real power emerges when they work together. As agents evolve from simple chatbots to autonomous decision-makers and automation platforms become more intelligent and flexible, organizations can combine both to achieve higher reliability, faster execution, and deeper insights. This post breaks down the agent and automation spectrums, explains why Mode 1 (Execute) and Mode 2 (Explore) are both essential, and shows how their convergence enables smarter, safer, and more scalable AI-driven operations.

Introducing Tellius Agent Mode: Agentic Analytics That Actually Does the Work

In today’s data-rich world, asking questions is no longer enough—what matters most is taking action. This blog introduces Tellius Agent Mode, a transformative leap into agentic analytics where AI agents don’t just answer queries—they plan, analyze, explain, and act. You’ll learn how Tellius marries a semantic layer, multi-agent orchestration, and business context to create an analytics ecosystem that moves beyond dashboards. With Agent Mode, you can automate multi-step workflows like root-cause detection, forecasting, and scenario planning—all through conversational goals. The result? Analysts elevate their focus to strategy while operational teams get trusted insights when they need them. Whether you're scaling analytics across sales, finance, or supply chain, this blog shows why Agent Mode is the architecture ready for enterprise intelligence at the speed of decision.