AI Agent & Automation

Shadow AI is spreading fast as employees use unapproved AI tools at work, risking data leaks and compliance issues. This blog explores the dangers and how businesses can stay protected.

Customer support in 2025 demands speed, scale, and personalization — something early automation couldn’t deliver. Enter agentic AI: systems that can think, decide, and act. This blog explores how agentic AI is redefining support with real-world use cases and insights.

Enterprises run on countless apps, leading to “app fatigue” and scattered workflows. AI is now emerging as the connective layer that unifies systems and makes work more seamless.

Enterprises are moving past public AI in 2025, demanding private, secure, and customizable systems. As major players pivot to enterprise-grade models, the shift toward sovereign AI is clear. This blog explores the drivers behind that change.

As CX becomes increasingly autonomous, even the most advanced AI agents can fall short when faced with complex or emotional issues. This blog explores why escalation planning is essential to maintain service quality—and how businesses can design seamless human handoffs when automation reaches its limits.

Agentic AI makes decisions autonomously, and Chain-of-Thought (CoT) monitoring reveals its reasoning. As agentic AI is deployed, CoT monitoring ensures transparency and auditability. Can we truly see what AI “thinks”? This blog explores that.

AI agents now handle support instantly—no humans, no delays. Here are the 13 best AI agent platforms for customer support in 2025.

Conversational AI is powerful—but risky. One misstep can leak sensitive data. As adoption grows, so must security. Here’s how to protect CX in the age of AI.

Enterprise AI is now mission-critical—but fragmented systems are holding it back. Model Context Protocol (MCP) brings shared context across AI models, enabling smarter, scalable, and more resilient enterprise AI. Here’s why it could be the most important layer yet.

Prompt injection is a rising threat in AI systems, allowing attackers to manipulate how large language models respond. This blog explores how it works and the strategies to defend against it.