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Overview

The NVIDIA AI-Q Blueprint (pronounced IQ) is a deployable, customizable research system built on LangChain Deep Agents and accelerated by the NVIDIA NeMo Agent Toolkit. Teams can self-host the application boundary and connect deployment-owned models, enterprise data, authentication, policy controls, storage, and observability. AI-Q combines fast, cited answers with in-depth, report-style research and includes evaluation harnesses for measuring quality.

Architecture

$\"AI-Q$

Every query enters through an intent classifier, which responds directly to conversational requests or routes research to a shallow or deep path. Deep research can clarify the request, consult an optional source router, build a structured plan, dispatch concurrent researcher workers, and delegate final synthesis to a writer. Research roles share job-scoped state; configured skills can execute code in an isolated NVIDIA OpenShell or Modal sandbox without moving inference, source credentials, or enterprise data out of the AI-Q process.

Key Features

AI-Q is powered by a LangGraph-based state machine. The agents can run as one orchestrated research workflow or as standalone components:

Orchestration node: Classifies intent, produces conversational responses when appropriate, and routes research to the shallow or deep path.
Shallow research agent: Performs bounded, tool-augmented research optimized for fast, cited answers.
Deep research agent: Coordinates optional source routing, structured planning, concurrent researcher workers, and writer-led synthesis for report-style research.
Report follow-up: Answers questions about a completed report, creates rewrites, or performs additional research with the report as context.
Workflow configuration: YAML profiles define agents, tools, models, source selection, policies, and execution behavior without code changes.
Modular workflows: The orchestration node, shallow researcher, deep researcher, clarifier, and deep-research roles are composable within the full pipeline.
Pluggable data sources: Connect web and paper search, MCP tools, collaboration services, LlamaIndex, the NVIDIA RAG Blueprint, Azure AI Search, and OpenSearch.
MCP integration: Connect to MCP servers through NeMo Agent Toolkit or expose AI-Q research operations through the standalone MCP server.
Skills and sandbox execution: Assign reusable skills to research and writing roles and run generated code in a job-scoped OpenShell or Modal sandbox.
Durable generated files: Capture generated charts, CSVs, notebooks, and documents in SQL or S3-compatible storage for live and replayed access in the UI.
Evaluation harnesses: Use built-in FreshQA and DeepResearch evaluation workflows to measure quality and iterate on prompts and agent architecture.
Frontend options: Run through the CLI, web UI, or asynchronous jobs API.
Deployment options: Self-host with Docker Compose or Helm and connect deployment-owned models, databases, object storage, authentication, policy controls, and observability.

Prerequisites

Required:

Python 3.11-3.13
uv package manager
Node.js 22+ and npm (optional, for web UI mode)
API key for your chosen provider(s):\n
- NVIDIA API key from build.nvidia.com (for NVIDIA NIM inference microservices)
- OpenAI API key (for OpenAI models)
- Anthropic API key (for Claude models)
- Google API key (for Gemini models)
\n

Optional:

API credentials for the research sources and enterprise services enabled by your selected workflow

System Requirements

Local / Hybrid Development

Developer machine to run the AI-Q instance (no local GPU required)
LlamaIndex (optional local RAG)
Provider, service, or RAG APIs

Fully Self-Hosted / On-Prem

Server for AI-Q instances
NVIDIA Nemotron 3.5 Lightning 30B A3B (intent classification and shallow research)
NVIDIA Nemotron 3 Ultra 550B A55B (clarification and deep-research roles)
Google Gemma 4 31B IT (optional document summary)
NVIDIA RAG Blueprint (optional RAG)\n
- Models packaged as NVIDIA NIM microservices:\n
  \n
\n
LlamaIndex (optional RAG)\n
- NVIDIA Nemotron 3 Embed 1B
- NVIDIA Nemotron 3 Nano Omni 30B A3B Reasoning
\n

Hosted Service

Server for AI-Q instances
Provider APIs
NVIDIA RAG Blueprint (optional)
LlamaIndex (optional)

The models above correspond to the default AI-Q profiles. Other checked-in profiles can use different hosted model providers; no single profile enables every capability.

Hardware Requirements

Hardware requirements vary by model profile, concurrency, context length, and retrieval deployment. Refer to the following resources before sizing a self-hosted deployment:

Software Components

NVIDIA Technology

3rd Party Software

LangChain and LangGraph for agent workflows
Tavily, Exa, You.com, and Nimble for configurable web research
LlamaIndex, Azure AI Search, and OpenSearch for enterprise retrieval

License

This project is licensed under the Apache License 2.0. See the AI-Q license for details.

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

This service is governed by the NVIDIA API Trial Terms of Service.

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Teams can self-host the application boundary and connect deployment-owned models, enterprise data, authentication, policy controls, storage, and observability. AI-Q combines fast, cited answers with in-depth, report-style research and includes evaluation harnesses for measuring quality.\n\n## Architecture\n\n![AI-Q Architecture](https://assets.ngc.nvidia.com/products/api-catalog/aiq/diagram1.jpg)\n\nEvery query enters through an intent classifier, which responds directly to conversational requests or routes research to a shallow or deep path. Deep research can clarify the request, consult an optional source router, build a structured plan, dispatch concurrent researcher workers, and delegate final synthesis to a writer. Research roles share job-scoped state; configured skills can execute code in an isolated [NVIDIA OpenShell](https://docs.nvidia.com/openshell/latest/about/installation) or Modal sandbox without moving inference, source credentials, or enterprise data out of the AI-Q process.\n\n## Key Features\n\nAI-Q is powered by a LangGraph-based state machine. The agents can run as one orchestrated research workflow or as standalone components:\n\n- **Orchestration node**: Classifies intent, produces conversational responses when appropriate, and routes research to the shallow or deep path.\n- **Shallow research agent**: Performs bounded, tool-augmented research optimized for fast, cited answers.\n- **Deep research agent**: Coordinates optional source routing, structured planning, concurrent researcher workers, and writer-led synthesis for report-style research.\n- **Report follow-up**: Answers questions about a completed report, creates rewrites, or performs additional research with the report as context.\n- **Workflow configuration**: YAML profiles define agents, tools, models, source selection, policies, and execution behavior without code changes.\n- **Modular workflows**: The orchestration node, shallow researcher, deep researcher, clarifier, and deep-research roles are composable within the full pipeline.\n- **Pluggable data sources**: Connect web and paper search, MCP tools, collaboration services, LlamaIndex, the NVIDIA RAG Blueprint, Azure AI Search, and OpenSearch.\n- **MCP integration**: Connect to MCP servers through NeMo Agent Toolkit or expose AI-Q research operations through the standalone MCP server.\n- **Skills and sandbox execution**: Assign reusable skills to research and writing roles and run generated code in a job-scoped OpenShell or Modal sandbox.\n- **Durable generated files**: Capture generated charts, CSVs, notebooks, and documents in SQL or S3-compatible storage for live and replayed access in the UI.\n- **Evaluation harnesses**: Use built-in FreshQA and DeepResearch evaluation workflows to measure quality and iterate on prompts and agent architecture.\n- **Frontend options**: Run through the CLI, web UI, or asynchronous jobs API.\n- **Deployment options**: Self-host with Docker Compose or Helm and connect deployment-owned models, databases, object storage, authentication, policy controls, and observability.\n\n## Prerequisites\n\n**Required:**\n\n- Python 3.11-3.13\n- [uv](https://github.com/astral-sh/uv) package manager\n- Node.js 22+ and npm (optional, for web UI mode)\n- API key for your chosen provider(s):\n - NVIDIA API key from [build.nvidia.com](https://build.nvidia.com/) (for NVIDIA NIM inference microservices)\n - OpenAI API key (for OpenAI models)\n - Anthropic API key (for Claude models)\n - Google API key (for Gemini models)\n\n**Optional:**\n\n- API credentials for the research sources and enterprise services enabled by your selected workflow\n\n## System Requirements\n\n**Local / Hybrid Development**\n\n- Developer machine to run the AI-Q instance (no local GPU required)\n- LlamaIndex (optional local RAG)\n- Provider, service, or RAG APIs\n\n**Fully Self-Hosted / On-Prem**\n\n- Server for AI-Q instances\n- [NVIDIA Nemotron 3.5 Lightning 30B A3B](https://build.nvidia.com/nvidia/nemotron-3.5-lightning-30b-a3b) (intent classification and shallow research)\n- [NVIDIA Nemotron 3 Ultra 550B A55B](https://build.nvidia.com/nvidia/nemotron-3-ultra-550b-a55b) (clarification and deep-research roles)\n- [Google Gemma 4 31B IT](https://build.nvidia.com/google/gemma-4-31b-it) (optional document summary)\n- [NVIDIA RAG Blueprint](https://github.com/NVIDIA-AI-Blueprints/rag/blob/main/docs/support-matrix.md) (optional RAG)\n - Models packaged as NVIDIA NIM microservices:\n - [Llama 3.3 Nemotron Super 49B v1.5](https://build.nvidia.com/nvidia/llama-3_3-nemotron-super-49b-v1_5)\n - [Llama 3.2 NV EmbedQA 1B v2](https://build.nvidia.com/nvidia/llama-3_2-nv-embedqa-1b-v2)\n - [Llama 3.2 NV RerankQA 1B v2](https://build.nvidia.com/nvidia/llama-3_2-nv-rerankqa-1b-v2)\n - [NeMo Retriever Page Elements v3](https://build.nvidia.com/nvidia/nemoretriever-page-elements-v3)\n - [NeMo Retriever Table Structure v1](https://build.nvidia.com/nvidia/nemoretriever-table-structure-v1)\n - [NeMo Retriever Graphic Elements v1](https://build.nvidia.com/nvidia/nemoretriever-graphic-elements-v1)\n - [NeMo Retriever OCR](https://build.nvidia.com/nvidia/nemoretriever-ocr)\n- LlamaIndex (optional RAG)\n - [NVIDIA Nemotron 3 Embed 1B](https://build.nvidia.com/nvidia/nemotron-3-embed-1b)\n - [NVIDIA Nemotron 3 Nano Omni 30B A3B Reasoning](https://build.nvidia.com/nvidia/nemotron-3-nano-omni-30b-a3b-reasoning)\n\n**Hosted Service**\n\n- Server for AI-Q instances\n- Provider APIs\n- [NVIDIA RAG Blueprint](https://github.com/NVIDIA-AI-Blueprints/rag/blob/main/docs/support-matrix.md) (optional)\n- LlamaIndex (optional)\n\nThe models above correspond to the default AI-Q profiles. Other checked-in profiles can use different hosted model providers; no single profile enables every capability.\n\n## Hardware Requirements\n\nHardware requirements vary by model profile, concurrency, context length, and retrieval deployment. Refer to the following resources before sizing a self-hosted deployment:\n\n- [NVIDIA Nemotron 3.5 Lightning model card](https://build.nvidia.com/nvidia/nemotron-3.5-lightning-30b-a3b/modelcard)\n- [NVIDIA Nemotron 3 Ultra model card](https://build.nvidia.com/nvidia/nemotron-3-ultra-550b-a55b/modelcard)\n- [Google Gemma 4 31B IT model card](https://build.nvidia.com/google/gemma-4-31b-it/modelcard)\n- [NVIDIA Nemotron embedding support matrix](https://docs.nvidia.com/nim/nemo-retriever/text-embedding/latest/support-matrix.html)\n- [NVIDIA vision-language model support matrix](https://docs.nvidia.com/nim/vision-language-models/latest/support-matrix.html)\n- [NVIDIA RAG Blueprint support matrix](https://github.com/NVIDIA-AI-Blueprints/rag/blob/main/docs/support-matrix.md)\n\n## Software Components\n\n**NVIDIA Technology**\n\n- [NVIDIA NeMo Agent Toolkit](https://github.com/NVIDIA/NeMo-Agent-Toolkit)\n- [NVIDIA NeMo Guardrails](https://docs.nvidia.com/nemo/guardrails/latest/)\n- [NVIDIA NIM](https://build.nvidia.com/models)\n- [NVIDIA RAG Blueprint](https://github.com/NVIDIA-AI-Blueprints/rag)\n\n**3rd Party Software**\n\n- [LangChain](https://www.langchain.com/) and [LangGraph](https://www.langchain.com/langgraph) for agent workflows\n- [Tavily](https://tavily.com/), [Exa](https://exa.ai/), [You.com](https://you.com/), and [Nimble](https://docs.nimbleway.com/) for configurable web research\n- [LlamaIndex](https://www.llamaindex.ai/), Azure AI Search, and OpenSearch for enterprise retrieval\n\n## License\n\nThis project is licensed under the Apache License 2.0. See the [AI-Q license](https://github.com/NVIDIA-AI-Blueprints/aiq/blob/release/2.2/LICENSE) for details.\n\n## Ethical Considerations\n\nNVIDIA 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](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n## Terms of Use\n\nThis service is governed by the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf).","displayName","AI-Q Blueprint",["D",1787369871815],"publisher","NVIDIA Corporation","latestVersion","versions","collectionCounts","imageUrl","/api/image/nvidia/blueprint/helm-charts/aiq2-web","rawImageUrl","https://assets.ngc.nvidia.com/products/api-catalog/images/aiq.jpg","canGuestDownload","latestVersionSizeInBytes","licenseTerms","isMultinodeEnabled","isMultiArchitecture","bias","explainability","privacy","safetyAndSecurity","featureLabels",[],"displayLabels",[247,248,249,250,251],"policyLabels",[],"systemLabels",[],"products",[],"hasNimMetadata",{"_215":269,"_253":270,"_255":271,"_257":258},{"_215":266,"_253":267,"_255":268,"_257":258},{"_215":263,"_253":264,"_255":265,"_257":258},{"_215":261,"_253":261,"_255":262,"_257":258},{"_215":252,"_253":254,"_255":256,"_257":258},"Question Answering","value","uscs_question_answering","filter",{"_259":260,"_253":254},"category","label","field","application","NSPECT-HYTG-KJF1",{"_259":258,"_253":261},"Natural Language Understanding","uscs_natural_language_understanding",{"_259":260,"_253":264},"Natural Language Processing","uscs_natural_language_processing",{"_259":260,"_253":267},"AI","soln_ai",{"_259":272,"_253":270},"technology",{"_106":1252,"_108":1253},"ngcApps",[1205],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1186":1187,"_1188":1189,"_1190":1191,"_1192":1193,"_1194":284,"_138":310,"_1195":1196,"_1197":55,"_1198":85,"_1199":85,"_1200":1201,"_1202":85,"_1203":1204},"amplitude",{"_1183":1184,"_823":-7,"_1185":30},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMiUyMiUzQWZhbHNlJTdE","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1177":1178,"_1179":1180,"_1181":1182},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"manageableExternalUserGroups",[],"ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"now",1787694217978,"1.12.0","defaultSearchSuggestions",{"_1063":391,"_1064":1065,"_1066":1067,"_1068":1069},"announcements",[],"consentState",{"_348":1053,"_1054":85,"_1055":30,"_1056":30,"_1057":1058},"consentConfig",{"_330":331,"_332":333,"_334":335,"_336":337,"_338":339,"_340":341,"_342":343,"_344":345,"_346":347,"_348":349},"showContactAdmin",1787694217979,[],[],[324,325,326,327,328,329],{"_44":59,"_46":70,"_48":101,"_50":-5,"_52":-5,"_54":55},{"_44":59,"_46":68,"_48":101,"_50":-5,"_52":-5,"_54":55},{"_44":59,"_46":66,"_48":101,"_50":-5,"_52":-5,"_54":55},{"_44":59,"_46":60,"_48":101,"_50":-5,"_52":-5,"_54":55},{"_44":56,"_46":57,"_48":101,"_50":-5,"_52":-5,"_54":55},{"_44":45,"_46":47,"_48":49,"_50":51,"_52":130,"_54":55},"mainInfoText","We and our third-party partners (including social media, advertising, and analytics partners) use cookies and other tracking technologies to collect, store, monitor, and process certain information about you when you visit our website. 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They are capable of tracking your browser across other sites and building up a profile of your interests. This may impact the content and messages you see on other websites you visit. If you do not allow these cookies you may not be able to use or see these sharing tools.","alwaysActive","order",11,"cookies",[],"hosts",[],"C0004","Advertising Cookies","These cookies record your visit to our websites, the pages you have visited and the links you have followed to influence the advertisements that you see on other websites. These cookies and the information they collect may be managed by other companies, including our advertising partners, and may be used to build a profile of your interests and show you relevant advertising on other sites. We and our advertising partners will use this information to make our websites and the advertising displayed on it, more relevant to your interests.",5,[488,489,490,491,492,493,494,495,496,497,498,499,500,501,502,503,504,505,506,507,508,509],[372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388],{"_389":483,"_215":483,"_166":391,"_362":484},{"_389":479,"_215":479,"_166":391,"_362":480},{"_389":474,"_215":474,"_166":391,"_362":475},{"_389":470,"_215":470,"_166":391,"_362":471},{"_389":465,"_215":465,"_166":391,"_362":466},{"_389":460,"_215":460,"_166":391,"_362":461},{"_389":452,"_215":452,"_166":391,"_362":453},{"_389":444,"_215":444,"_166":391,"_362":445},{"_389":439,"_215":439,"_166":391,"_362":440},{"_389":434,"_215":434,"_166":391,"_362":435},{"_389":429,"_215":429,"_166":391,"_362":430},{"_389":424,"_215":424,"_166":391,"_362":425},{"_389":419,"_215":419,"_166":391,"_362":420},{"_389":412,"_215":412,"_166":391,"_362":413},{"_389":407,"_215":407,"_166":391,"_362":408},{"_389":400,"_215":400,"_166":391,"_362":401},{"_389":390,"_215":390,"_166":391,"_362":392},"hostName","amazon-adsystem.com","",[393,394],{"_77":399,"_396":390,"_397":30,"_166":398},{"_77":395,"_396":390,"_397":30,"_166":398},"ad-privacy","host","isSession","This domain is owned by online retailer Amazon and is used as part of its affiliate marketing programme.","ad-id","doubleclick.net",[402,403],{"_77":406,"_396":400,"_397":30,"_166":405},{"_77":404,"_396":400,"_397":30,"_166":405},"IDE","This domain is owned by Doubleclick (Google). 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It uses the data gathered from most of these services to profile the interests of web users and sell advertising space to organisations based on such interest profiles as well as aligning adverts to the content on the pages where its customer's adverts appear.","linkedin.com",[441],{"_77":442,"_396":439,"_397":30,"_166":443},"bcookie","This domain is owned by LinkedIn, the business networking platform. It typically acts as a third party host where website owners have placed one of its content sharing buttons in their pages, although its content and services can be embedded in other ways. Although such buttons add functionality to the website they are on, cookies are set regardless of whether or not the visitor has an active Linkedin profile, or agreed to their terms and conditions. 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This tracking cookie allows a website to link visitor behaviour to the recipient of an email marketing campaign, to measure campaign effectiveness.","investor.nvidia.com","This cookie is associated with Eventbrite and is used to deliver content tailored to the end user's interests and improve content creation. This cookie is also used for event-booking purposes.","_gat_gtag_UA_140825383_2","Google Analytics","_rdt_uuid","This cookie is set by Reddit and is used for tracking the views of embedded videos and performance of the advertisements.","catalog.ngc.nvidia.com","_uetsid","This cookie is used by Bing to determine what ads should be shown that may be relevant to the end user perusing the site. ","kndctr_F207D74D549850760A4C98C6_AdobeOrg_bc_session_id","ttcsid_XXXXXXXXXXXXXXXXXXXXCategory","This cookie name is associated with TikTok which is used to track your activity on the platform, including how you interact with their embedded services on other websites.This cookie is associated with TikTok. It helps track your activity on the platform, including how you interact with their embedded services on other websites.","_fbp","Used by Facebook to deliver a series of advertisement products such as real time bidding from third party advertisers","_zitok","_twpid","This cookie is typically associated with the use of Taptap Digital, a company specializing in digital advertising. It is used for tracking and ad personalization purposes.","_tt_enable_cookie","This cookie name is associated with TikTok which is used to collect data about behavior and purchases on the website and to measure the effect of advertising. It is also used to track website activity to help optimize advertising efforts.","AMCV_xxxxxAdobeOrg","This cookie is used to identify a unique visitor for tracking purposes by Adobe Experience Cloud.This is a pattern type cookie name associated with Adobe Marketing Cloud. It stores a unique visitor identifier, and uses an organisation identifier to allow a company to track users across their domains and services.","ttcsid","This cookie name is associated with TikTok which is used to enable TikTok Ads session tracking by assigning a unique session ID to users who click on TikTok ads, allowing for the attribution of user behavior and conversions within the same session.This cookie is associated with TikTok. It helps track your activity on the platform, including how you interact with their embedded services on other websites.","C0003","Personalization Cookies","These cookies collect data about how you have interacted with our website to help us improve your web experience, such as which pages you have visited. These cookies may store a unique ID so that our system will remember you when you return. They may be set by us or by third party providers whose services we have added to our pages. These cookies enable us to provide enhanced website functionality and personalization as well as make the marketing messages we send to you more relevant to your interests. If you do not allow these cookies, then some or all of these services may not function properly.",[580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604],[551,552,553,554,555],{"_389":465,"_215":465,"_166":391,"_362":575},{"_389":439,"_215":439,"_166":391,"_362":570},{"_389":565,"_215":565,"_166":391,"_362":566},{"_389":560,"_215":560,"_166":391,"_362":561},{"_389":556,"_215":556,"_166":391,"_362":557},"nvidia.partners",[558],{"_77":559,"_396":556,"_397":30,"_166":433},"edge","app.hushly.com",[562],{"_77":563,"_396":560,"_397":30,"_166":564},"*CORS","This domain is associated with Hushly, a platform that provides lead conversion solutions for content marketing by using personalization and content engagement strategies.","github.com",[567],{"_77":568,"_396":565,"_397":30,"_166":569},"_octo","This domain is owned by Github. 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We have categorized it under Functionality because it is necessary for the operation of our affiliate program.","nv_country_code","developer.nvidia.com","This cookie is likely used to store the country code of the visitor to provide localized content and possibly for legal compliance with regional data privacy laws.","_gdxxxxxxxxxxxxx","nvidianews.nvidia.com","docs.api.nvidia.com","research.nvidia.com","readme_library","wcmmode","ai-podcast.nvidia.com","resources.nvidia.com","geo_locator","openedx-language-preference","learn.nvidia.com","doxygen_width","raytracing-docs.nvidia.com","This cookie is likely used to remember the width preferences of a sidebar or interface element within a documentation platform like Doxygen.","_sfid_eb78","This cookie is categorized as Functionality Cookie.","crowdsource.nvidia.com","mbox","Cookie set by Adobe SiteCatalyst analytics software - used for measuring the performance of page content using A/B split testing","readme_language","vid","This cookie name 'vid' is used for tracking the search request made by the user on the 'Find a practitioner' page.","at_check","Used by Adobe Target to check if cookies are enabled/supported on the browser","blogs.nvidia.com","nvHeadless","This cookie is likely used to track if a user is using the site in a 'headless' non-GUI mode, which could be for accessibility reasons or for automated processes.","C0002","Performance Cookies","These cookies are used to provide quantitative measures of our website visitors, such as the number of times you visit, time on page, your mouse movements, scrolling, clicks and keystroke activity on the websites; other browsing, search, or product research behavior; and what brought you to our site. These cookies may store a unique ID so that our system will remember you when you return. Information collected with these cookies is used to measure and find ways to improve website performance.",[663,664,665,666,667,668,669,670,671,672,673,674,675,676,677,678,679,680,681,682,683,684,685,686,687,688,689,690,691],[643,644,645,646],{"_389":658,"_215":658,"_166":391,"_362":659},{"_389":653,"_215":653,"_166":391,"_362":654},{"_389":452,"_215":452,"_166":391,"_362":650},{"_389":565,"_215":565,"_166":391,"_362":647},[648],{"_77":649,"_396":565,"_397":85,"_166":569},"_gh_sess",[651],{"_77":652,"_396":452,"_397":85,"_166":459},"YSC","bizible.com",[655],{"_77":656,"_396":653,"_397":30,"_166":657},"_BUID","Bizible is a marketing attribution software that tracks the performance of marketing efforts and connects them to revenue, primarily used for B2B environments.","a.usbrowserspeed.com",[660],{"_77":661,"_396":658,"_397":30,"_166":662},"tuid","This domain is owned by Ookla which provides internet speed testing services through its Speedtest application.",{"_77":733,"_396":511,"_397":30,"_166":734},{"_77":718,"_396":732,"_397":85,"_166":719},{"_77":701,"_396":514,"_397":30,"_166":626},{"_77":701,"_396":614,"_397":30,"_166":626},{"_77":730,"_396":511,"_397":30,"_166":731},{"_77":718,"_396":517,"_397":85,"_166":719},{"_77":728,"_396":511,"_397":30,"_166":729},{"_77":718,"_396":514,"_397":85,"_166":719},{"_77":726,"_396":613,"_397":30,"_166":727},{"_77":718,"_396":635,"_397":85,"_166":719},{"_77":698,"_396":514,"_397":30,"_166":700},{"_77":724,"_396":511,"_397":85,"_166":725},{"_77":722,"_396":511,"_397":30,"_166":723},{"_77":720,"_396":511,"_397":85,"_166":721},{"_77":718,"_396":609,"_397":85,"_166":719},{"_77":716,"_396":511,"_397":30,"_166":717},{"_77":714,"_396":511,"_397":30,"_166":715},{"_77":712,"_396":511,"_397":85,"_166":713},{"_77":710,"_396":618,"_397":30,"_166":711},{"_77":698,"_396":609,"_397":30,"_166":700},{"_77":708,"_396":511,"_397":30,"_166":709},{"_77":706,"_396":511,"_397":85,"_166":707},{"_77":704,"_396":511,"_397":30,"_166":705},{"_77":702,"_396":511,"_397":30,"_166":703},{"_77":701,"_396":511,"_397":30,"_166":626},{"_77":698,"_396":699,"_397":30,"_166":700},{"_77":696,"_396":511,"_397":30,"_166":697},{"_77":694,"_396":511,"_397":85,"_166":695},{"_77":692,"_396":511,"_397":30,"_166":693},"_ga_xxxxxxxxxx","Used by Google Analytics to identify and track an individual session with your device.","s_ppvl","This cookie is set by Adobe Analytics to store information on the percentage of the page displayed to the end user.","coveo_visitorId","This cookie name is associated with Coveo which is used to store a unique user ID for marketing purposes and to track the number of distinct users who submitted a query or clicked an item, counting them only once even if they did the same query or clicked the same item over the course of many visits.","_dd_s","marketplace.nvidia.com","Datadog Cookie used to group all events generated from a unique user session across multiple pages. It contains the current session ID, whether the session is excluded due to sampling, and the expiration date of the session. The cookie is extended for an extra 15 minutes every time the user interacts with the website, up to the maximum user session duration (4 hours).","nvweb_A","_ga","This cookie name is associated with Google Universal Analytics - which is a significant update to Google's more commonly used analytics service. This cookie is used to distinguish unique users by assigning a randomly generated number as a client identifier. It is included in each page request in a site and used to calculate visitor, session and campaign data for the sites analytics reports. By default it is set to expire after 2 years, although this is customisable by website owners.","_uetvid","This is a cookie utilised by Microsoft Bing Ads and is a tracking cookie. It allows us to engage with a user that has previously visited our website.","tp","This cookie is associated with Adobe Analytics site tracking. It registers if the website's scroll-depth detection is active. This function remembers how far the user has scrolled on the current session across the website's sub-pages.","_hly_vid","This cookie _hly_vid is used to record website and server performance with each visit to the site. The data is aggregated and analyzed; therefore, it remains anonymous upon use.","_session_id","This cookie creates an interim session ID used as an in-session user ID.\n","s_cc","This cookie is associated with the Adobe Site Catalyst. It determines whether cookies are enabled in the web browser.","s_ecid","Adobe Analytics cookie containing the the Adobe Experience Cloud 1st party visitor id if the Analytics AMCV visitor id is not found.","_hjSessionUser_xxxxxx","Hotjar cookie that is set when a user first lands on a page with the Hotjar script. It is used to persist the Hotjar User ID, unique to that site on the browser. This ensures that behavior in subsequent visits to the same site will be attributed to the same user ID.","_hjHasCachedUserAttributes","This cookie name is associated with Hotjar which is used to know whether the data set in _hjUserAttributes Local Storage item is up to date or not.","s_ppv","This cookie is associated with Adobe Analytics site tracking and is used to measure a user's scroll activity to see how much of a page they view before moving to another page.","_gid","This cookie name is associated with Google Universal Analytics. This appears to be a new cookie and as of Spring 2017 no information is available from Google. It appears to store and update a unique value for each page visited.","_hjTLDTest","When the Hotjar script executes we try to determine the most generic cookie path we should use, instead of the page hostname. 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