Pranav Ramkumar

Intent architecture is the backbone of CX automation. When intent taxonomies are unclear or overlapping, bots misread requests, routing breaks, and Agent Assist suggests the wrong help. A clean structure keeps AI accurate and consistent.

AI is reshaping customer experience—but real-world changes can cause AI drift, reducing accuracy over time. Without continuous monitoring and updates, CX quality can quickly slip.

Vertical AI delivers industry-specific, context-aware intelligence that fixes the accuracy gaps of generic AI. It powers precise, personalized customer interactions that improve satisfaction and loyalty.

As AI quietly becomes the middleman for nearly every customer interaction, the difference between a frustrating bot and a truly helpful, compliant, and empathetic CX often comes down to the prompt behind it — and this blog explains how.

Behind every chatbot and workflow sits an agent bridging gaps that shouldn’t exist, giving rise to agent experience debt.
How this impacts scalability and how organizations can reverse it is what this blog explains.

Micro-automations turn tiny CX moments into instant, reliable support that quietly builds trust. They slot into existing workflows as small rule-based triggers, boosting speed and consistency without heavy system changes.

AI is reshaping customer experience, but choosing the right model matters more than ever. This article breaks down when to use LLMs or SLMs—and how to balance scale, cost, and efficiency in CX.

This blog explains why observability is critical in AI-driven CX, showing how monitoring, alerts, and insights can prevent failures and build customer trust.

AI Assistants are transforming customer support by automating repetitive tasks and empowering agents to focus on meaningful interactions. This guide answers key questions CX leaders have about using AI Assistants to boost efficiency and customer satisfaction.