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Thematic analysis for your dissertation or thesis.

The easiest and cheapest thematic analysis tool for dissertation and thesis work. Paste the findings of published studies — or your own interviews, focus groups, and survey responses — choose your framework — Braun & Clarke, thematic synthesis, grounded theory, and more — and watch codes form and cluster into themes you can defend in a viva, with a verbatim quote behind every one.

Person-centredcareMedicationadherenceMotivationalinterviewingHealthliteracyShareddecisionsContinuityof careSelf-managementTherapeuticalliance

How it works

From a pile of findings to named themes in minutes

01

Paste or upload your studies' findings

One box per study: paste the findings or results section, or upload the PDF and let it pull the findings out. Label each with a short citation. Three studies minimum, fifteen maximum — the first three are always free.

  • Smith et al. (2021)
  • Bergström et al. (2023)
  • Chen & Okafor (2022)
02

The engine runs your framework

Choose Braun & Clarke, Thomas & Harden thematic synthesis, framework analysis, grounded theory, or content analysis. Each study is coded first, then codes are clustered across studies — and you watch it happen, bubble by bubble.

  • ① Familiarisation
  • ② Initial codes
  • ③ Searching for themes
  • ④ Reviewing → ⑤ Naming → ⑥ Report
03

Get a report you can defend

Named themes with definitions, analytic narratives that cite your studies, every code backed by a verbatim quote, plus a synthesis summary and limitations note. Download as a Word document and drop it into your write-up.

  • Themes + definitions
  • Verbatim quotes per code
  • Summary + limitations

Who it's for

Built for dissertation and thesis work

Most people here are writing up a dissertation or thesis chapter on a deadline. If your work involves making sense of findings across studies — or coding your own transcripts — this engine does the first pass, and you do the thinking.

undergrad + masters

Dissertation literature review

Synthesise the findings of your review into themes with an audit trail your supervisor can check — codes, verbatim quotes, and a named framework you can cite in your methods chapter.

masters + PhD

Thesis primary data

Code your own interview, focus group, or open-ended survey data participant by participant, then see the themes across your whole dataset — ready to defend in a viva.

evidence synthesis

Systematic reviews & meta-synthesis

Run a Thomas & Harden thematic synthesis across included studies and export descriptive-to-analytical themes for your review paper.

any discipline

Literature reviews

Stop summarising paper by paper. See what your fifteen sources say together — where they converge, and where they contradict.

lecturers

Teaching qualitative methods

Show a class the whole coding-to-themes journey live in one seminar, then have students critique and refine the machine's codes.

researchers

Grant & ethics applications

Build a quick evidence map of prior findings to justify your study — with quotes ready to cite in the background section.

public sector

Policy & practice briefs

Turn a stack of report findings into themed, quotable evidence summaries for decision-makers in an afternoon.

The honest question

“Couldn't I just ask a chatbot?”

You could — and you'd get a fluent summary you cannot cite, check, or defend. Markers and reviewers ask how you got your themes. This tool answers that question: a named framework, study-by-study coding, and a verbatim quote behind every code.

Comparison between asking a generic chatbot and using the thematic analysis tool
What you needGeneric chatbotthematicanalysis.ai
Named methodology“I asked ChatGPT to find themes” — hard to defend in a vivaBraun & Clarke, Thomas & Harden, and more — cited in the report
Evidence trailFluent summary, no quotes, no way to check a claimEvery code carries a verbatim quote from a named study
Study-level codingEverything blended into one answerEach study coded separately, then synthesised across studies
StructureDifferent format every time you askThemes → definitions → narratives → codes, identical every run
Seeing the analysisA wall of textWatch codes appear and cluster into themes, live
Write-up readyCopy-paste and reformat by handOne-click Markdown report with summary and limitations

Pricing

One flat price, not a subscription

No accounts, no monthly plans, no student-budget ambush. The first 3 sources of every analysis are free — published studies or your own participants, whichever you're analysing. Need more? The whole analysis is a flat $5.

First 3 sources

Free

  • Studies or participants — either mode
  • Every framework included
  • Full report with quotes & export
  • No signup, no card

Full analysis (up to 15)

$5 / analysis, flat

  • Everything above 3 sources, up to 15 — one price
  • No word limit: up to 20,000 words per source, so whole papers and full transcripts fit
  • Pay per analysis — no lock-in, no subscription

PDF upload is live — drop in published papers or your own transcripts instead of pasting text, up to 3MB per file. PDFs are read in your browser, so the file itself never reaches our servers.

Your first three studies are on us

Paste your findings, pick a framework, and watch your themes take shape — before your coffee goes cold.

Start your free analysis

FAQ

Frequently asked questions

Yes — it's what the tool is built for. Use literature review mode for your review chapter, pasting the findings of each study you're synthesising, or primary research mode for your own interview, focus group, and open-ended survey data. Either way you get named codes, a verbatim quote behind every code, themes with the sources that support and contradict them, and a Word report you can work from. Two things to do before you submit: review and rename the codes yourself — AI-assisted coding is a first pass, not a finished analysis — and check your institution's policy on AI assistance, disclosing it in your methods chapter where required. Cite the framework you chose (Braun & Clarke, Thomas & Harden, and so on), not this tool, as your method.

Substantially. A student NVivo licence runs about $125 a year and past $400 with the AI add-on, before the week you'd spend learning it. Here the first 3 sources of every analysis are free, and everything beyond that is one flat $5 for the whole analysis — up to 15 sources, with no word limit per source. A fifteen-study review chapter costs $5, nothing to install, and you're running your first analysis within a few minutes. Check your university library first, though: a site licence sometimes makes NVivo free for you.

In literature review mode: the findings or results section of each study — the part that reports what was found. You don't need the whole paper: skip the abstract, methods, and references. Paste one study per box and label it with a short citation like “Smith et al. (2021)”. In primary research mode: your own participant data — one interview transcript, focus group, or respondent's open-ended survey answers per box. You can also upload a PDF per box (up to 3MB): it's read in your browser, we pull out the findings section where there is one, and you can edit the text before running.

Yes — switch to primary research mode on the analyse page. Paste or upload each participant's responses (interview transcripts, focus group excerpts, or open-ended survey answers), pick a framework, and the engine codes every participant with verbatim quotes and clusters the codes into themes across your dataset. Your first 3 participants are free; a full analysis of up to 15 is a flat $5.

Five: Reflexive Thematic Analysis (Braun & Clarke) — the default and the most widely taught; Thematic Synthesis (Thomas & Harden) for systematic-review style syntheses; Framework Analysis (Ritchie & Spencer); Grounded Theory with constant comparison; and Qualitative Content Analysis. The engine follows the phases and terminology of whichever you pick, and the report names the method so you can cite it.

The first 3 sources of every analysis are free — studies or participants, no signup, no card, up to 15,000 characters (~2,500 words) in each box. Analysing more than 3 puts the whole analysis on one flat $5, up to the 15-source maximum: the same price whether you run 4 sources or 15, no subscription, and the per-source word limit is lifted to around 20,000 words so whole papers and full transcripts fit. Paying unlocks the full analysis for 24 hours, so you can run and re-run it as much as you need. No account, no card stored.

Yes — this is one. NVivo runs about $125 a year on a student licence and north of $400 once the AI add-on is included; here the first 3 studies of every analysis are free and anything beyond that is one flat $5 for the whole analysis, so a ten-study synthesis costs $5 with nothing to install and no week spent learning the software. Other affordable options for qualitative analysis are Taguette (free and open source, manual coding only), Quirkos (~$21 a quarter) and ATLAS.ti (~$50–99 a year on a student desktop licence). Check your university library first, though: a site licence often makes NVivo free for you. And if you're hand-coding hundreds of primary transcripts for a funded study with a formal audit trail, NVivo or ATLAS.ti is still the right tool — this is built to get you from a pile of findings to defensible themes fast.

Yes — as an AI-assisted first pass, not a replacement for your judgement. Review every code against its quote, rename themes to fit your research question, and follow your institution's or journal's policy on disclosing AI assistance. The report includes a limitations note that says exactly this.

Every code carries a verbatim quote copied from the text you pasted, and every theme lists the studies and codes behind it — so each claim is checkable in seconds. The engine is instructed never to paraphrase or invent quotes, and anything you can't verify against your own sources, you should cut. That audit trail is the difference between this and asking a chatbot.

Your text is processed to produce your results and is not stored on our servers — analyses live in your browser session and disappear when you leave (so export your report before closing the tab). To run the analysis your text is sent to a third-party AI provider whose API we use; we choose providers that do not use API data to train their models, and may change provider over time. Anonymise participant data before analysing it.

No. Open the tool, paste your studies, run the analysis, download the report. Nothing to sign up for, nothing to cancel.

At least 3 — below that, cross-study themes aren't meaningful — and at most 15 per analysis. If you have more than 15 sources, run them in batches by sub-topic and merge the themes in your write-up, or start with your 15 most central studies.