AI that reasons is everywhere.
Reasoning that knows your business isn't

Kaiya Everywhere: Intelligence That Knows Your Business, Now Wherever You Work

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.

Best CPG Category Management Software (2026): The 6 Platforms Category Teams Actually Shortlist

Category management is evolving from periodic reporting and spreadsheet-driven analysis to continuous, AI-powered decision-making. This guide compares six of the leading category management platforms that CPG teams are actively evaluating in 2026. The comparison examines capabilities across category analytics, assortment optimization, shelf and space planning, retailer collaboration, demand insights, promotional performance, and AI-driven recommendations.

Why AI Workflows Give Different Answers Every Time — and How to Make Them Deterministic

One of the biggest challenges organizations face when deploying AI agents and workflows is inconsistency. The same question can generate different answers, recommendations, or actions depending on context, prompts, model behavior, and execution paths. This blog explains why AI systems are inherently probabilistic, where variability originates in modern agent architectures, and why prompt engineering alone cannot solve the problem. It explores how leading enterprises are introducing deterministic controls through semantic layers, governed business logic, structured workflows, context management, validation frameworks, and agent orchestration.