AI Chatbots and Virtual Assistants for Customer Service

NVIDIA offers tools that help organizations embrace generative AI to build chatbots, AI virtual assistants, and virtual agents. To further empower strategic growth, these tools also include reference examples that enable them to use RAG to access vast internal and external datasets for more efficient information retrieval.

Optimal Inference for Generative AI Workloads

NVIDIA NIM^™, part of NVIDIA AI Enterprise, is a set of easy-to-use inference microservices designed to accelerate the deployment of generative AI across your enterprise. This versatile runtime supports open community models and NVIDIA AI Foundation models from the NVIDIA API catalog, as well as custom AI models. NIM builds on NVIDIA Triton™ Inference Server, a powerful and scalable open-source platform for deploying AI models, and is optimized for LLM inference on NVIDIA GPUs with NVIDIA® TensorRT™-LLM. NIM is engineered to facilitate seamless AI inferencing with high throughput and low latency, while preserving the accuracy of predictions. You can deploy AI applications anywhere with confidence, whether on premises or in the cloud.

NVIDIA ACE Brings Digital Humans to Life With Generative AI

Built on NVIDIA AI, graphics, and simulation technologies, NVIDIA ACE encompasses technology for every part of the digital human—from speech and translation to vision and intelligence, to realistic animation and behavior, to lifelike appearance. And with RAG, you can convey specific and up-to-date information to customers. NVIDIA Tokkio is a reference workflow built with ACE, bringing AI-powered customer service capabilities to telecommunications, financial services, retail, and more.

Several ACE microservices are NVIDIA NIM microservices, optimized to run on NVIDIA GDN—a global network of GPUs that delivers low-latency digital human processing to 100 countries, on any cloud or PC.

NVIDIA ACE is now generally available from developer.nvidia.com/ACE. Developers can integrate ACE NIM microservices directly into their products, tools, services, or applications.

Real-Time Information Retrieval

NeMo Retriever is a collection of microservices that enable retrieval-augmented semantic search of enterprise data to deliver highly accurate responses. Developers can use these GPU-accelerated microservices for specific tasks, including extraction, embedding, and reranking of large volumes of data, interacting with existing relational databases, and searching for relevant pieces of information to answer business questions.

Integrating Speech AI Capabilities

NVIDIA Riva, part of NVIDIA AI Enterprise, is a set of GPU-accelerated multilingual speech and translation microservices for building fully customizable, real-time conversational AI pipelines. Riva includes automatic speech recognition (ASR), text-to-speech (TTS), and neural machine translation (NMT) and is deployable in all clouds, in data centers, at the edge, or on embedded devices. With Riva, organizations can add speech and translation interfaces with LLMs and RAG to transform chatbots into engaging and expressive multilingual assistants and avatars.

Enterprises looking to deploy generative AI models for virtual call center agents can use the NVIDIA API catalog to quickly get started building chatbots with RAG. NVIDIA offers an AI chatbot AI workflow and AI virtual assistant NIM Agent Blueprint reference example to ease the path from pilot to production deployment.

1. Start With State-of-the-Art Generative AI Models: Leading foundation models include Meta Llama 3, Google Gemma 7B, Mixtral 8x7B, retrieval models, and NVIDIA’s Nemotron-3 8B family, optimized for the highest performance per cost.
2. Customize foundation models: Tune and test the models with proprietary data using NVIDIA NeMo™, an end-to-end platform for developing custom generative AI, anywhere.
3. The Cloud-First Way to Get the Best of NVIDIA AI: NVIDIA DGX™ Cloud is an AI platform for enterprise developers, optimized for the demands of generative AI.
4. Deploy and Scale: Run your applications anywhere—cloud, data center, or edge—by deploying with NVIDIA NIM, part of NVIDIA AI Enterprise, the production-grade, secure, end-to-end software platform that includes generative AI reference applications and enterprise support.

The NVIDIA RAG chatbot AI workflow example streamlines the creation of enterprise solutions that generate precise responses for diverse applications. This example allows you to develop a RAG application using the latest GPU-optimized LLM, NeMo Retriever, and NIM microservices.

This workflow highlights how NVIDIA's integration with LangChain and LlamaIndex streamlines the development of scalable, high-performance RAG pipelines for LLM applications. It showcases a seamless setup using Docker, enhanced by NVIDIA NIM for better inference and flexibility, along with examples for easy deployment and API integration.

The NVIDIA NIM Agent Blueprint is a customizable toolkit designed to help developers build advanced AI virtual assistants. It includes essential tools like NIM microservices, reference code, and documentation to create AI systems that can handle tasks such as personalization, summarization, and sentiment analysis.

The NIM Agent Blueprint enhances customer service using RAG and generative AI technologies like NVIDIA NIM and NeMo. It addresses challenges such as fragmented data sources and data security, connecting these sources to improve operational efficiency in contact centers.

The blueprint provides advanced AI tools for secure data management, personalized multi-turn conversations, sentiment analysis, summary generation, and flexible session handling.