QualIntel OS structures your qualitative analysis from research question to submission package — surfacing candidate evidence for your review, never making decisions for you. Every coding choice, theme, and synthesis narrative stays yours.
No credit card required. Free for your first project.
The problem
You're doing serious work — interviews, focus groups, document analysis — but managing it across Google Docs, sticky notes, and spreadsheets. When an assessor asks how you arrived at a theme, you scramble. The methodology is sound. The paper trail isn't.
You know every decision you made. But can you prove it to an examiner? Probably not — it's scattered across five apps and your memory.
ChatGPT doesn't know your codebook, your research questions, or what saturation means. It generates plausible-sounding output you can't defend.
Writing theme narratives without checking quote diversity, RQ alignment, or single-voice dominance means surprises at examination. Late.
How it works
A structured workflow that takes you from raw data to an assessor-ready package — without letting AI make analytical decisions on your behalf.
Upload your proposal, interview guide, literature framework, or rubric. QualIntel reads your research design before touching your data — so AI assistance is anchored to your methodology, not generic patterns.
Create codes and themes grounded in your methodology — deductive from your literature, inductive from your data, or both. Every code is tied to your research questions. The AI can suggest initial codes from your design documents, which you accept or reject.
Interviews, focus groups, field notes, or observations. Every segment is embedded with Voyage AI and indexed against your codebook — ready for semantic retrieval.
QualIntel surfaces candidate evidence segments semantically matched to each code. You accept or reject every suggestion. Nothing is coded without your explicit confirmation — always human-in-the-loop, never autopilot.
Write narrative synthesis for each theme in a structured editor. Then run the built-in Quality Checker — which flags single-voice over-reliance, absent codes, RQ alignment gaps, and analytical modesty before you export.
Export a complete ZIP: Evidence Pack DOCX, Codebook export, AI Disclosure Statement, Reflexivity Template, and a How-To Guide for your methods appendix. Formatted in APA 7, Harvard, Chicago, or Vancouver.
Quality Checker
The built-in Quality Checker reviews each theme narrative against objective data and interpretive criteria. It flags issues while you can still fix them.
Objective checks
Interpretive checks
RQ Alignment
High confidenceNarrative directly addresses Primary RQ
Participant diversity
ObjectiveP3 accounts for 62% of cited evidence — consider broadening
Analytical modesty
High confidenceResearcher voice maintained throughout
A priori / emergent distinction
Medium confidenceEmergent codes not differentiated from codebook codes
Evidence grounding
High confidenceClaims tied to specific participant passages
QualIntel OS flags methodological considerations. Final analytical judgement stays with the researcher.
Submission_Package.zip
Evidence_Pack.docx
Themes, audit trail, excerpts — formatted in your citation style
Codebook.docx
All codes, descriptions, and RQ links
AI_Disclosure_Statement.txt
Researcher-led framing of how AI assisted your analysis
Reflexivity_Template.txt
Structured prompts for your positionality and decision log
How_To_Use_This_Package.txt
Guide for methods appendix and examiner review
Optional: Owen's (1984) recurrence, repetition, and forcefulness criteria applied to disclosure
Submission Package
One click generates a complete submission ZIP — not just a report. Your evidence pack, codebook, AI disclosure, reflexivity prompts, and a how-to guide for the examiner, all in one place.
Research Assistant
Stop rereading transcripts to find a single quote. The built-in Research Assistant retrieves across every document in your project — every answer cites the exact document and passage it came from.
Which participants described barriers to accessing mental health support?
Four participants described access barriers. Most common: cost and waitlists.
Interview_03.pdf · p.7 · P3
"I looked into it but the waitlist was six months. I just gave up after that."
Interview_07.pdf · p.4 · P7
"The cost was completely out of reach on a student income."
+ 2 more passages · Coded: barrier_access, barrier_cost
Built for rigour
Credibility, transferability, dependability, confirmability — the four pillars of qualitative trustworthiness, designed into every workflow.
Every coding decision, every theme revision, every AI suggestion you accepted or rejected — logged with timestamp, rationale, and researcher attribution. Your examiner traces every finding back to raw data.
QualIntel surfaces candidate evidence segments. You accept or reject every one. Thematic interpretation, narrative synthesis, and analytical conclusions are yours — the system organises, retrieves, and audits.
The platform understands thematic analysis, grounded theory, content analysis, and IPA — not just 'text analysis.' The synthesis editor, quality checker, and codebook tools all speak your discipline's language.
Formatted evidence packs, codebooks, AI disclosures, and reflexivity templates — structured methodological documentation that demonstrates rigour at every level, not just at the finding.
Who it's for
Masters and PhD candidates running thesis research who need to demonstrate methodological rigour to supervisors and examiners — not just produce findings. The audit trail is your evidence of process.
Thesis research · Dissertation projects
Independent consultants and boutique agencies delivering qualitative insights to clients who want evidence-based conclusions. The submission package gives clients documentation they can actually interrogate.
Client reports · Stakeholder research
Programme evaluators, nonprofit impact teams, and education researchers who need defensible evidence for funders, boards, and regulatory bodies. The quality checker surfaces issues before the report goes out.
Programme evaluation · Impact assessment
Why QualIntel
Based on standard workflows as of May 2026.
| Capability | Generic AI | NVivo / Atlas.ti | QualIntel OS |
|---|---|---|---|
| Methodology-anchored AI coding | — | — | ✓ |
| Automated audit trail | — | — | ✓ |
| Pre-submission quality checker | — | — | ✓ |
| Submission package with AI disclosure | — | — | ✓ |
| Structured codebook + RQ links | — | ✓ | ✓ |
| Human-in-the-loop confirmation | — | ✓ | ✓ |
| Evidence-linked Research Assistant | — | — | ✓ |
| Cloud-native, any device | ✓ | — | ✓ |
| Priced for individual researchers | ✓ | — | ✓ |
Pricing
Start free. Pay when you need more.
One complete project from data upload to submission package export.
For active researchers running multiple projects simultaneously.
For universities, research units, and consulting firms needing platform access for cohorts.
Qualitative research is under scrutiny. Funders want evidence. Journals want transparency. Examiners want to trace every finding back to raw data. QualIntel OS makes that possible — without adding hours to your workflow or letting AI make decisions for you.
Start your first project freeNo credit card required.