Build an AI Agent for Enterprise Research

Experience Your Personal Research Assistant

This experience shows how an AI research agent, informed by many data sources, can synthesize hours of research in minutes. The AI-Q NVIDIA Blueprint enables developers to connect AI agents to their own data and use reasoning and tools to distill in-depth source materials with efficiency and precision. Using AI-Q, agents summarize large data sets, generating tokens 5x faster and ingesting large scale data 15x faster with better semantic accuracy. The blueprint uses the open-source NVIDIA NeMo Agent toolkit for evaluation and profiling of the agent workflow, enabling easier optimization and interoperability of agents, tools, and data sources.

Architecture Diagram

Key Features

• Ease development and optimization with NVIDIA NeMo Agentic AI toolkit
  • Evaluate, audit and debug agentic workflow to identify opportunities for optimization
  • Flexibly choose, and connect agents and tools best suited for each task
• Advanced semantic query with NVIDIA NeMo Retriever
  • Multimodal PDF data extraction and retrieval
  • 15x faster ingestion of enterprise data
  • 3x lower retrieval latency
  • Multilingual and cross-lingual
  • Reranking to further improve accuracy
  • GPU-accelerated index creation and search
• Fast reasoning with Llama Nemotron
  • Reasoning capabilities delivering the highest accuracy and lowest latency for analyzing datasets, identifying patterns, and proposing solutions

Minimum System Requirements

Hardware Requirements

• By default, this blueprint deploys the referenced NIM microservices locally. For this, you will require a minimum of 4xH100 or 7xA100 GPUs.
• The blueprint can be modified to use additional NIM microservices hosted by NVIDIA.

OS Requirements

• Ubuntu 22.04 OS

Deployment Options

• Docker-Compose

Software used in this blueprint

NVIDIA Technology

• llama-3.3-nemotron-super-49b-instruct
• llama-3.2-nv-embedqa-1b-v2
• llama-3.2-nv-rerankqa-1b-v2
• nemoretriever-graphic-elements-v1
• nemoretriever-table-structure-v1
• nemoretriever-page-elements-v2
• paddleocr
• llama-3.3-70b-instruct
• Agentic AI open-source toolkit
• NVIDIA RAG Blueprint
• NeMo Retriever Extraction

3rd Party Software

• Tavily
• LangChain
• Milvus database (accelerated with NVIDIA cuVS)

Ethical Considerations

NVIDIA believes Trustworthy AI is a shared responsibility, and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure the models meet requirements for the relevant industry and use case and address unforeseen product misuse. For more detailed information on ethical considerations for the models, please see the Model Card++ Explainability, Bias, Safety & Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI concerns here.

Terms of Use

GOVERNING TERMS: This service is governed by the NVIDIA API Trial Terms of Service