Why some companies are replacing call centers with AI
Many companies began adopting AI for customer service because they faced recurring problems in their human operations.
AI vs. human receptionist: who responds better to your customers
Human receptionists bring empathy and natural communication. However, they also have structural limitations.
How to reduce latency in AI-powered voice agents
In this article we will explore how to reduce latency in AI-powered voice agents, and what factors affect real-time performance.
5 use cases for AI Chat with databases in modern businesses
One of the most common cases is allowing business teams (marketing, sales, operations) to query data without writing SQL.
What is Text-to-SQL and how does it allow you to query databases in natural language?
Text-to-SQL is the technical basis of many database chat solutions, conversational analytics assistants, and BI tools.
How to securely integrate an AI chatbot with databases
In this article, we discuss how to build a secure architecture for chatbots connected to databases.
From dashboards to conversations: the evolution of BI with generative AI
Companies that adopt this conversational layer report significant improvements in data adoption and analytical speed.
Chat with databases: How to talk to your data?
Communicating with a database involves using natural language to query, analyze, and explore information stored in business systems.
Key terminology for understanding Rootlenses Voice
21. Essential Rootlenses Voice terminology
Rootlenses Voice combines artificial intelligence, automation, and telephony to execute voice conversations at scale.
This glossary brings together key concepts, both operational and technical, to help users understand how the platform works, how agents are configured, and how call-generated results are interpreted.
Basic concepts of CoT and RAG for voice agents
This guide summarizes the essential concepts of COT (Chain of Thought) and RAG (Retrieval-Augmented Generation) for building conversational agents that are more natural, accurate, and production-ready.