Agentic AI, grounded in research methodology—coming soon

NVivo AI Cloud is Lumivero's AI-native, cloud-based research environment for qualitative and mixed-methods research. It pairs agentic AI workflows with the qualitative research methodology researchers already trust from NVivo, guiding project setup, importing literature and documents, identifying topics with per-topic evidence, auto-coding against confirmed topics, and answering grounded questions through AURA Chat.

AURA Chat is NVivo AI Cloud's agentic AI chat feature. It answers questions grounded in your project data, provides click-through citations back to source material, and can save answers as memos. Its Devil's Advocate mode is designed to surface disconfirming evidence or negative cases, helping researchers pressure-test their own conclusions rather than only confirm them.

NVivo (Desktop) is Lumivero's established, license-based desktop QDA software with an AI Assistant built into the application. NVivo AI Cloud is a separate, cloud-native product built around agentic AI workflows from the ground up. Both are grounded in the same qualitative research methodology, but NVivo AI Cloud is designed as an AI-native research environment rather than desktop software with AI features added to it.

NVivo AI Cloud is built for academic social science researchers conducting qualitative or mixed-methods studies, including individual researchers, students, and academic teams working on projects that need to be defensible and grounded in rigorous methodology.

NVivo AI Cloud applies AI across the research lifecycle. It offers AI-suggested research questions during project setup, imports literature and documents, identifies topics across a corpus with per-topic evidence, and auto-codes against confirmed topics while preserving your existing codebook. Researchers can also ask questions grounded in their own project through AURA Chat, which includes a Devil's Advocate mode for disconfirming or negative case analysis.

Every AI-generated theme, code, or insight links back to source data through a citation-linked coding trail. Every AI write action requires human approval before it becomes part of your project, and a full, exportable audit trail, including AI prompt inspection, is available so AI-assisted coding can be reviewed the same way manual coding is.

Yes. NVivo AI Cloud is built around established qualitative methodologies, including grounded theory, thematic analysis, and framework analysis, and draws on Lumivero's 20+ years in qualitative research software. It is not a general-purpose AI tool with research applied afterward.

General-purpose AI tools are not built with a research methodology and do not retain persistent memory of a researcher's codebook or project structure between sessions. NVivo AI Cloud works within your existing project, codes, memos, and analytical structure, and is designed specifically for qualitative and mixed-methods research. 

Some AI-native tools are built primarily for speed, auto-coding transcripts and generating themes quickly. NVivo AI Cloud is built to pair that kind of AI-assisted speed with methodological rigor and a full audit trail, so findings can stand up to scrutiny from a reviewer, committee, or journal, not just move quickly to a first draft.

You'll be first to know when it goes live on Oct. 6 for individual researchers or will receive first notification when access is ready for Team and Organization plans.

No. Joining the waitlist is free with no obligation—it just puts you first in line for early access and launch details.

NVivo AI Cloud launches Oct. 6, 2026, at Lumivero’s live reveal event, Illuminate. Pricing—including student and researcher options—will be announced at launch. Join the waitlist to get it the moment it's live.

No. NVivo AI Cloud is the new AI-native way to work; NVivo Desktop continues as the licensed app you already know. If you're a current user, join the waitlist and we'll share what the launch means for you.

Yes. It's built for research that must stand up to scrutiny—every AI-assisted step stays transparent and traceable, so your analysis remains reproducible and defensible.