Data topics

Process mining and spend intelligence solve different problems, but they're often evaluated as if they compete. This guide explains why they are complementary technologies and when organizations need one, the other, or both. Learn how process mining platforms reconstruct procurement workflows from event logs to identify bottlenecks, compliance issues, and operational inefficiencies, while AI-powered spend intelligence validates every invoice against contracts to uncover overbilling, duplicate payments, off-contract spend, pricing errors, and unclaimed rebates that process mining cannot detect.

Tellius 6.3 marks a major step toward making enterprise AI available wherever work happens. With Kaiya Everywhere, users can access trusted AI-powered analytics directly from Slack, Microsoft Teams, dashboards, browsers, enterprise applications, and AI tools through MCP integrations. The release also introduces powerful new capabilities for domain reasoning, enabling organizations to combine business context, semantic definitions, institutional knowledge, and analytical best practices into every AI interaction. New Kaiya Skills make it easier to customize how AI performs analysis, generates insights, creates visualizations, and executes workflows, while enhancements to memory, phrase learning, and query learning help AI become more accurate over time. Tellius 6.3 also streamlines onboarding, allowing teams to connect data, build business views, and start generating trusted answers in minutes. Together, these innovations help enterprises move beyond generic AI assistants to AI that understands their business, reasons with context, and delivers actionable insights wherever decisions are made.

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.

This guide lays out a complete picture of where augmented analytics is headed in 2025. It goes beyond buzzwords to explain how AI agents, conversational interfaces, generative insights, and governed semantic layers combine to deliver more than just “what happened”—they show why things change and what to do next. Expect deep dives into agentic workflows, scalability, governance challenges, and real use cases across industries. Whether you’re redesigning your data stack or evaluating new analytics tools, this is your roadmap to making augmented analytics work in practice.

This blog dives into the practical challenges (“battle scars”) encountered while moving agentic AI analytics from demo to production. Covering real-world engineering and product lessons, it highlights pitfalls like ambiguous language, mismatched definitions, performance tail‑latency, lack of observability, and unreliable multi‑step logic. For each scar, it provides strategies—governed semantics, demander/validator separation, deterministic planning, explicit feedback loops, and transparency—that help build robust, trustworthy analytics agents at enterprise scale. If you’re rolling out AI analytics agents, these lessons can help you avoid common traps and ship with confidence.

For years, analytics tools promised guided insights—but often delivered static dashboards, confusing filters, and a steep learning curve. This blog explores how modern AI agents are changing the game. Unlike their predecessors, these intelligent systems understand user intent, dynamically investigate data, and return clear, actionable results conversationally. They uncover deeper “why” analysis, adapt to context, integrate seamlessly into workflows, and make insights accessible to business users without technical expertise. Discover how Tellius is ushering in a new era of empowered decision-making: fast, trusted, and built for the way we think.

Dive into the essential ingredients for building a genuinely enterprise-ready agentic analytics platform. You’ll learn why AI agents alone aren’t enough—why convergence with a robust semantic layer, rigorous governance, scalable compute, and clear explainability matters. Explore how Tellius’s architecture weaves together conversational AI, domain-aware knowledge models, multi-agent orchestration, and trust-first design to enable autonomous analytics workflows that deliver accurate insights and measurable business outcomes at scale.

Tellius has been named a Visionary for the 4th year in a row in the 2025 Gartner® Magic Quadrant™ for Analytics & BI Platforms. Why? Because we’re not just stopping at dashboards. We’re moving the industry forward with: - GenAI-powered conversational analytics - Agentic flows that connect insight to action - An end-to-end platform built for enterprise-grade governance The future of business intelligence isn’t just pretty charts. It’s intelligent decisions—made faster.

AI agents are not a “nice-to-have”; they’re a must-have if you want to break free from analysis paralysis, truly democratize data-driven decision-making, and scale your analytics across hundreds (or thousands) of business users. The real promise of data democratization is not just in enabling more people to ask questions, but in enabling those questions to be answered comprehensively and autonomously.

Traditional self-service BI tools promised independence but often left users dependent on analysts and stuck with complex interfaces. AI agents are now transforming the analytics landscape by managing complexity, automating workflows, and reasoning behind the scenes. Paired with a semantic knowledge layer, these agents deliver accurate, business-aware insights. With Tellius, users don’t need to learn analytics—they just ask questions and get answers. True self-service has finally arrived.

The next era of analytics is goal-driven, adaptive, and intelligent. Tellius brings this to life by combining deep analytics with conversational intelligence, multi-agent reasoning, and business-aware feedback loops. It’s not about replacing analysts—it’s about scaling intelligence across your business with a system that gets smarter every day.

Tellius AI Agents and AgentComposer transform business analytics by automating complex multi-step analysis through specialized autonomous agents. Unlike generic chatbots or RPA tools, these agents leverage your enterprise data and business context to deliver deep insights across sales, marketing, finance, and manufacturing—turning questions into actions in minutes instead of days. With no-code agentic workflows, organizations can achieve 100X productivity gains and continuous, data-driven decision making.

AI agents aren’t just hype—they’re the engine behind the next generation of self-service analytics. This post breaks down how agentic AI enables multi-step, contextual analysis workflows that automate the grunt work of business intelligence. Learn what makes agentic systems different, what to look for in a true AI-native platform, and how Tellius is pioneering this transformation.

The newly improved Tellius Feed metrics tracker unlocks huge time-savings, bringing companies from reactive to proactive analytics.

Conversational FP&A AI analytics promises to transform raw data into powerful financial insights and narratives that move the business forward, powered by generative AI.

Here are the key forms of diagnostic analytics, the limitations of traditional manual approaches, and the benefits of AI-powered diagnostic analytics.

Let's dig into what makes Tellius’ automated insights industry-leading, and provide an understanding of how automated insights can help your organization make better decisions.

In this new Tellius release, we’re helping customers dig into the why behind the what in their data by demystifying AI, turbocharging data insights, and expanding data connectivity.

The explainable AI charts introduced in our fall 2023 release allow us to see the reasoning behind a machine learning model's predictions.

Learn how AI and augmented analytics are revolutionizing every part of supply chain management—from planning, to sourcing, to manufacturing, to logistics.

Learn how eBay is supercharging its decision-making process with powerful self-service analytics and data exploration from Tellius.

Tellius has always prioritized data protection and privacy, and achieving SOC 2 Type II certification demonstrates its continued commitment to meeting and exceeding industry-best practices.

We are excited to announce the launch of Tellius Copilot—your perfect companion for smart decision-making. Tellius Copilot takes the platform’s industry-leading augmented analytics capabilities to the next level by leveraging the power of GPT.

Tellius has appointed Josh Peltz SVP of sales, who will set strategic sales direction and accelerate the growing adoption of Tellius Decision Intelligence.

Why are more organizations turning toward self-service analytics? Businesses thrive when everyone—not just the data experts—has access to the tools and information they need to make quick, insightful decisions driven by data.

This is the story of how FCA is empowering 100s of users to go beyond traditional BI capabilities while saving 100+ hours a month of manual data reporting to reliably make better data-informed decisions.

Learn why more organizations are looking beyond traditional dashboards to Decision Intelligence to deliver critical answers from your business data.

Tellius CEO, Ajay Khanna had the opportunity to speak with Karen Walker, Contributor: Leadership and Leadership Strategy for Forbes. Karen and Ajay discussed how Tellius is combining AI and machine learning-driven automation with a natural language search interface for ad hoc exploration.

On-Demand offering dramatically lowers the barrier for organizations to utilize AI-driven analytics at any scale, saving customers up to 70% compared to legacy “cloudified” technology

Madhukara Phatak, Tellius Director of Engineering, breaks down the challenges of traditional multi-data source analytics and how we overcome these challenges with Apache Spark.