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QualIntel OS

AI-assisted qualitative analysis for PhD and postgraduate researchers. The AI surfaces candidate evidence; you confirm every coding decision โ€” producing an audit trail and examiner-ready AI-disclosure statement. Seven methodologies supported.

QualIntel OS is an AI-assisted qualitative research platform for PhD and postgraduate researchers โ€” built for the question every examiner now asks: how did you use AI in your analysis?

Other AI tools code your data and ask you to check it. QualIntel works the other way: the AI surfaces candidate evidence semantically matched to your codebook, and you confirm or reject every coding decision. Every suggestion and every decision is logged into a complete, timestamped audit trail โ€” and on export you get a non-editable AI-disclosure statement built from that trail, ready for your methods chapter.

Methodology-aware, not generic: seven qualitative methodologies supported โ€” Reflexive Thematic Analysis, IPA, Grounded Theory, Gioia, Codebook TA, Content Analysis, and Template Analysis โ€” with method-specific guidance and reporting standards (RTARG, COREQ, SRQR).

From data to draft: upload your research design, build the codebook, review evidence, write your synthesis, and scaffold a methodology-aware, rubric-aligned report โ€” then export an examiner-ready evidence pack.

  • Free plan: one project, full workflow
  • Student $19/mo ยท Researcher $49/mo (annual = 2 months free)

The analysis โ€” and the credit โ€” stay yours.*

A startup from Hamilton, New Zealand that is founded by Stephen McCurdy.

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QualIntel OS

QualIntel OS Reviews and Details

This page is designed to help you find out whether QualIntel OS is good and if it is the right choice for you.

#Qualitative Data Analysis #Research Tools #AI Tools #Data Analysis #Qualitative Research #AI

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  • QualIntel OS
    Image date //
    2026-06-10
  • QualIntel OS
    Image date //
    2026-06-10
  • QualIntel OS
    Image date //
    2026-06-10

Features & Specs

  1. Researcher-led AI coding

    AI surfaces candidate evidence segments; the researcher accepts or rejects every suggestion. Nothing is coded without human confirmation.

  2. Methodology audit trail

    Every accept, reject, merge, and revision is timestamped and attributed to the researcher โ€” exportable for supervisors and examiners.

  3. AI disclosure statement

    Auto-generated from the audit log, ready for a methods chapter, ethics board, or journal submission.

  4. Methodology modes

    Supports 7 qualitative methodologies including reflexive thematic analysis, grounded theory, IPA, and the Gioia method.

  5. Anchoring system

    Analysis is grounded in your own proposal, interview guide, theoretical framework, and marking rubric before any AI assistance runs.

  6. Real-time quality checker

    Flags single-voice over-reliance, unused a priori codes, and research-question alignment gaps while you draft.

  7. Methodology-aware report writer

    Drafts the structural skeleton (COREQ/RTA-aware) built only from researcher-confirmed evidence; the analytical prose stays yours.

  8. One-click submission package

    ZIP export with evidence pack, codebook, audit trail, disclosure statement, and reflexivity template โ€” APA 7, Harvard, Chicago, or Vancouver.

  9. Zoom & Fathom import

    OAuth import of cloud recordings and transcripts, plus DOCX, TXT, and VTT upload.

  10. Privacy & compliance

    GDPR with signed DPA, EU AI Act self-assessment (limited-risk), SOC 2 Type II certified infrastructure. Your data is never used to train models.

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Questions & Answers

As answered by people managing QualIntel OS.

  1. What makes QualIntel OS unique?

    QualIntel OS is built around one non-negotiable rule: nothing gets coded without human confirmation. The AI retrieves candidate evidence from your transcripts, but the researcher accepts or rejects every suggestion โ€” and each decision is timestamped into a methodology audit trail as you work. At submission time, that becomes a one-click package: evidence pack, codebook, audit trail, and an auto-generated AI disclosure statement an examiner can actually inspect. Most AI analysis tools do the thinking for you. QualIntel OS deliberately refuses to โ€” it does the busywork and keeps the interpretation provably yours.

  2. Why should a person choose QualIntel OS over its competitors?

    It depends what you need. If you want maximum speed โ€” automated theme generation across large document sets โ€” AI-native tools do that well. If your analysis has to survive a supervisor, an examiner, an ethics board, or a funder, QualIntel OS is built for exactly that moment: researcher-confirmed evidence, an accept/reject decision log, methodology-aware workflows (reflexive TA, grounded theory, IPA, Gioia, and more), and a disclosure statement generated from what actually happened rather than what you remember. Legacy tools like NVivo organise your data but leave all the work and none of the defence; generic chatbots do the work but destroy the defence.

  3. How would you describe the primary audience of QualIntel OS?

    Postgraduate researchers โ€” master's and PhD candidates whose thesis has to survive examination โ€” plus their supervisors, independent research consultants, and programme evaluators who need to defend findings to funding boards. Anyone doing qualitative analysis where "the AI found the themes" is a disqualifying answer.

  4. What's the story behind QualIntel OS?

    The founder built it for his own problem: doing postgraduate research at a university whose AI policy demands declared, accountable AI use, while facing hundreds of pages of transcripts. Generic AI tools would do the analysis but hollow out the rigour; legacy software preserved rigour but did none of the lifting. QualIntel OS is the missing middle โ€” AI that carries the structure and retrieval while the researcher keeps every interpretive decision, with the proof generated automatically as a by-product of working.

  5. Which are the primary technologies used for building QualIntel OS?

    Next.js on Vercel for the web app, a Python/FastAPI API with PostgreSQL, Qdrant for semantic search, Anthropic's Claude for evidence retrieval and Voyage AI for embeddings (both under no-training terms), Clerk for authentication, and Stripe for billing. Hosting is on SOC 2 Type II certified infrastructure (Railway, US West).

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Why choose QualIntel OS?

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  • Company/product may be too new, niche, or obscure to have established reputation data
  • Risk of the domain being unverified, defunct, or potentially not a legitimate established service

Recommended for

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  • Users should independently research via the actual website, check for reviews on trusted platforms (G2, Capterra, Trustpilot), verify company legitimacy, and consider requesting a demo or trial before committing

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Is QualIntel OS good? This is an informative page that will help you find out. Moreover, you can review and discuss QualIntel OS here. The primary details have been verified within the last quarter. So they could be considered up to date. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.

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