Conversational AI applications such as virtual assistants, digital avatars, and chatbots are paving the way for breakthrough, personalized, natural human-machine conversations. However, they must meet stringent requirements in terms of accuracy and latency. NVIDIA's conversational AI platform enables developers to quickly build and deploy innovative applications that deliver high accuracy and respond in well under 300 milliseconds - the speed for real-time interactions.

The advantages of conversational AI

Agent efficiency

Support contact center agents by creating real-time transcripts of customer conversations, analyzing them, and making recommendations to quickly resolve customer inquiries.

Digital accessibility

Enable people with hearing difficulties to consume audio content and people with speech impairments to express themselves more easily.

High availability

Use chatbots and virtual assistants to resolve customer inquiries and provide valuable information outside of normal human employee business hours.

Appealing experiences

Deliver engaging experiences with features like live captioning, expressive synthetic voices, and understanding customer preferences.

Cross-industry conversation AI

Financial Services

Detecting fraud is critical for any financial services company. Chatbots can help by identifying patterns of transactions, including quantities and locations, and by personalizing interactions. Conversational AI can also be used to assist agents and transcribe calls to increase call coverage.


When we think of the telecommunications industry, the first thing that comes to mind is customer information centers. They are at the heart of every telecom business, and conversational AI can help speed up many applications, such as agent support, virtual agents, and extracting statistics for things like sentiment analysis.

Consumer Services

Conversational AI can improve a range of processes in consumer services. This ranges from generating meeting summaries and scheduling follow-up sessions to live captioning during virtual meetings. In addition, conversational AI can provide voice commands for smart glasses and generate synthetic voices that sound like humans for use in consumer applications.

Solutions for conversational AI applications

Speech AI technologies include Automatic Speech Recognition (ASR) and Text-to-Speech (TTS). NVIDIA® Riva is a GPU-accelerated speech AI SDK for developing real-time speech AI pipelines that you can integrate into your conversational AI application.

Use any NVIDIA T4, V100, or A100 Tensor Core GPU to get the most out of Riva Learn more about what speech AI is and its benefits, use cases, and challenges here.

Smarter training
with the NVIDIA TAO Toolkit

Accelerate development time by 10x with production-ready NVIDIA pre-trained models and the NVIDIA TAO toolkit.

Simplified deployment
with NVIDIA Riva

Implement optimized speech AI models for maximum performance in the cloud, data center, embedded devices, and peripherals.

Natural language processing

There are two types of natural language processing (NLP): language models with fewer parameters and large NLP models with up to a trillion parameters. NVIDIA NeMo and NeMo Megatron are respectively designed for training small and large language models.

NeMo Megatron models can be exported to NVIDIA Triton™ Inference Server for high-performance inference in production. You can maximize the performance of NeMo Megatron by running it on NVIDIA DGX SuperPODs™ with A100 GPUs.

Develop models
easily with NVIDIA NeMo

Create, train, and optimize state-of-the-art conversational and speech models using the open source NVIDIA NeMo framework.

Train large language models
With NeMo Megatron

Edit training data and easily train and scale large language models with up to a trillion parameters using NeMo Megatron