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Frequently asked questions
Updated June 2026
Common questions about how QualIntel OS works, the methodologies it supports, academic integrity, data privacy, and pricing. Can't find an answer? Email us.
What QualIntel OS is
What is QualIntel OS?
QualIntel OS is an AI-assisted qualitative research platform for postgraduate and PhD researchers. It surfaces candidate evidence and organises your codebook while you confirm every coding decision, producing a defensible audit trail and a submission-ready evidence pack. The positioning is “cognitive scaffolding for qualitative rigour” — the system organises, surfaces, and audits; the researcher interprets.
Does QualIntel OS do the qualitative analysis for me?
No. QualIntel OS surfaces candidate evidence and organises your codebook, but you confirm or reject every coding decision. The platform does not interpret data or generate conclusions — interpretation and analytical judgement remain entirely the researcher’s. It is cognitive scaffolding, not an analysis replacement.
Who is QualIntel OS for?
QualIntel OS is built for postgraduate and PhD candidates, MBA students, research consultants, and programme evaluators who need to demonstrate methodological rigour. It suits anyone producing qualitative findings that must withstand examiner, supervisor, client, or funder scrutiny.
How does the QualIntel OS workflow work?
QualIntel OS follows six structured steps: (1) upload your research design so the AI extracts candidate codes from it, (2) review and finalise your codebook, (3) upload qualitative data such as transcripts, (4) review and accept or reject each candidate piece of evidence, (5) write your thematic synthesis, and (6) export a complete submission package. Every step requires active researcher input — there is no automated progression.
Methodology
Which qualitative methodologies does QualIntel OS support?
QualIntel OS supports seven methodologies: Reflexive Thematic Analysis (RTA), Interpretative Phenomenological Analysis (IPA), Grounded Theory, Codebook Thematic Analysis, Content Analysis, Template Analysis, and the Gioia methodology. Selecting a methodology at project setup adjusts the synthesis prompts, theme-naming guidance, saturation criteria, and quality-check thresholds — not just the labelling.
Is QualIntel OS just a text-analysis tool?
No. QualIntel OS is methodology-aware. Unlike generic text-analysis tools, it adapts its prompts, theme-naming conventions, and quality checks to the specific qualitative methodology you select, so the analytical support matches the standards your method requires.
Can QualIntel OS help with reflexive thematic analysis?
Yes. Reflexive Thematic Analysis (Braun & Clarke) is one of QualIntel OS’s seven supported methodologies and the first one built. In RTA mode the platform frames evidence as researcher-surfaced rather than AI-generated, supports a priori and emergent code distinctions, and prompts for reflexivity — consistent with the method’s emphasis on the researcher’s active role.
Academic integrity & examiners
Is QualIntel OS suitable for a PhD thesis or dissertation?
Yes. QualIntel OS is built for postgraduate and PhD researchers who must demonstrate methodological rigour. It maintains a complete audit trail of every coding decision and generates an AI disclosure statement and submission package designed for examiner scrutiny.
How does QualIntel OS handle AI disclosure for academic work?
Every QualIntel OS submission package includes a non-editable AI Disclosure Statement generated from the audit log. It states exactly what the AI did — how many candidate codes it extracted, how many the researcher accepted or rejected, and how many evidence segments were reviewed — reflecting actual platform activity rather than researcher self-report. This supports transparent reporting in line with institutional academic-integrity policies.
What does the audit trail record?
QualIntel OS logs every AI suggestion accepted or rejected, with a timestamp and researcher attribution: the AI’s initial code extraction versus your final codebook, every evidence suggestion you accepted or rejected, the inputs used for synthesis, and the AI model version and methodology mode. The full trail is included in the submission package so examiners can trace any finding back to the raw data.
What should a supervisor or examiner look for in a QualIntel OS submission?
Examiners should look for divergence between the researcher’s final codebook and the AI’s initial extraction (evidence of critical engagement), a meaningful evidence-rejection rate (selectivity rather than passive acceptance), a researcher-voiced synthesis that cites specific accepted evidence, and a completed reflexivity statement. QualIntel OS publishes a Supervisor & Examiner Trust Pack covering exactly these indicators.
Comparisons
How is QualIntel OS different from NVivo?
NVivo organises and stores qualitative data but does not reason over it or surface candidate evidence semantically, and it does not produce an AI-decision audit trail. QualIntel OS adds methodology-aware AI-assisted evidence retrieval, a researcher-confirmed audit trail, and a built-in pre-submission quality check, while keeping every interpretive decision with the researcher.
How is QualIntel OS different from using ChatGPT?
ChatGPT does not know your codebook, your chosen methodology, or what saturation means, and it produces no audit trail — so its output is hard to defend in an examination. QualIntel OS is methodology-aware, anchors AI assistance to your uploaded research design, requires you to confirm every coding decision, and generates a complete audit trail and AI disclosure statement built for academic scrutiny.
Is QualIntel OS a good NVivo alternative for PhD students?
Yes. For PhD students who need methodological rigour and a defensible audit trail, QualIntel OS is a strong NVivo alternative: it adds AI-assisted evidence retrieval and automatic AI-disclosure documentation that NVivo lacks, with student pricing from USD $19/month versus NVivo’s typical one-off licence cost of several hundred dollars.
Data privacy & security
Does QualIntel OS keep my research data private?
Yes. Research data is encrypted in transit (TLS 1.2+) and at rest, is never used to train AI models, and can be exported or permanently deleted at any time. QualIntel OS is GDPR-compliant, with right to erasure and data portability implemented in-product, and offers a Data Processing Agreement for institutional use.
Is my data used to train AI models?
No. QualIntel OS does not use your research data to train AI models. Documents are processed via Anthropic’s API, which does not train on API inputs under its standard commercial agreement.
Where is QualIntel OS data stored?
QualIntel OS infrastructure is hosted in the United States (Railway for the application and database, Qdrant for vector search). A full data residency statement and a Data Processing Agreement are available for institutions with specific requirements, including EU/UK transfer safeguards.
Pricing & plans
How much does QualIntel OS cost?
QualIntel OS has three plans: a Free plan (one project, AI-assisted codebook building, steps 1–2, free forever), a Student plan from USD $19/month with unlimited projects and full analysis features, and a Researcher plan from USD $49/month with priority AI processing and extended data retention. Pricing is available in USD, GBP, EUR, and AUD.
Is there a free version of QualIntel OS?
Yes. The Free plan is available forever at no cost and includes one project, uploading your research design, and AI-assisted codebook building through steps 1–2. Evidence review, thematic synthesis, and submission-package export require a paid plan.
Do I need a credit card to start?
No. You can start on the Free plan with no credit card required. You only add payment details if you upgrade to the Student or Researcher plan.