A conversational agent is an AI system designed to interact with humans through natural language. These agents, also called AI conversational agents or chatbots—understand, process, and respond to text or voice inputs. From simple Q&A to complex task automation, conversational agents power seamless digital experiences across customer service, sales, IT support, and more.
Conversational AI agents use natural language processing (NLP), machine learning, and often retrieval-augmented generation (RAG) to understand user input and deliver intelligent responses. Whether voice-based or text-driven, they rely on data, context, and real-time feedback to improve over time, turning static systems into responsive, human-like digital partners.
Go beyond basic bots. You can get AI-powered conversational agents tailored for your industry—hospitality, finance, ITSM, or commerce. These agents speak fluently, understand nuance, and deliver value. Whether for customer service, sales enablement, or digital transformation, our conversational AI agents turn conversations into results.
| Feature | Conversational AI | Traditional chatbots |
|---|---|---|
| Capability | Addresses more complex questions | Address basic inquiries |
| Responses | Generates responses based on user input and sentiment | Only respond to exact keywords (predefined Q&A format) |
| Flexibility | Adapts to unexpected queries using machine learning (ML) | Incapable of straying from predetermined chat paths |
| Knowledge base | Uses AI’s extensive knowledge | Rely on a database of preset questions and answers |
Conversational AI refers to systems, like chatbots and voice agents, that interact with users using natural language, powered by NLP, ML, and large language models.
Define a use case, gather quality data, select an AI model (LLM), design conversational flows, develop and integrate the agent, then test, deploy, and iterate.
Training involves feeding the AI structured data, documents, or transcripts and using supervised fine-tuning, reinforcement learning, or RAG to optimize its responses over time.
Look for flexibility (bring your own LLM), integration capabilities, security, performance, and support for your specific industry and use case—don’t settle for one-size-fits-all bots.
