qualcode.ai

Coding you can cite

AI-powered qualitative coding with dual-rater reliability metrics. Code thousands of open-ended responses in hours, not months—with methodology reviewers will trust.

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See how it works

You have 5,000 open-ended responses. Your deadline is in two weeks.

Manual coding would take 150 hours. You'd need a second coder for reliability. Then you'd spend another week reconciling disagreements and calculating kappa.

Or you could paste everything into ChatGPT and hope your reviewers don't ask questions.

There's a better way.

How it works

Dual-rater AI coding with human-in-the-loop

1

Upload your data

CSV or Excel. Pick which column to code.

2

Define your coding guide—or let AI suggest one

Create categories manually, or let two AIs analyze your data and propose them. You approve what makes sense.

3

Two AIs code independently

OpenAI and Anthropic. No peeking. Like human dual-coding.

4

Get reliability metrics

Kappa. Alpha. Agreement rates. Methods section ready.

5

Reconcile and improve

Review disagreements. System learns. Re-run. Watch kappa climb.

Research-grade, not research-adjacent

Built for publication, not dashboards

Dual-rater architecture

Two independent LLMs code every response. Not for show—for the same reason you'd use two human coders.

Real inter-rater reliability

Cohen's kappa and Krippendorff's alpha calculated automatically. Per-category breakdowns. Publication-ready.

Active learning

Every disagreement you reconcile teaches the system. Run 3 studies, watch your kappa hit 0.85.

Multi-label out of the box

Responses can receive multiple codes. Because "Great product, terrible shipping" isn't a single category.

Training data versioning

Every change creates a new version. Roll back anytime. Know exactly which training data produced which results.

GDPR compliant

EU infrastructure. AI processing under Standard Contractual Clauses. Your data is never used to train AI models.

Built for people who need to defend their methodology

Whether you're publishing, presenting, or reporting to clients

PhD students

You're drowning in interview transcripts. Your supervisor keeps asking about inter-rater reliability. Your defense is in four months.

Academic researchers

Reviewer 2 will ask how you ensured coding consistency. You'll have the numbers ready.

Market research agencies

Your team spends 40% of project time on manual coding. Your margins are suffering. Your clients want faster turnarounds.

Public health researchers

Sensitive data. Strict compliance requirements. You need European hosting and a proper DPA.

What you're doing now isn't working

Compare your options honestly

Approach The problem
Manual coding 150+ hours per study. Second coder costs money. Reconciliation takes forever.
NVivo / MAXQDA Single-rater AI. Want kappa? You'll need a second coder.
Enterprise CX tools AI themes for dashboards, not publications. No kappa. No methodology section.
Raw ChatGPT / Claude No dual-rater. No reliability metrics. No audit trail. Good luck with Reviewer 2.
qualcode.ai Dual-rater AI. Automatic kappa and alpha. Codebooks that write themselves. Publication-ready.

Start free with 500 credits

Get 50 credits instantly. Verify your email to unlock 450 more. No credit card required.

Your responses are waiting

You've collected the data. You've procrastinated on coding long enough. Upload a CSV. Let AI suggest categories—or define your own. Two AIs handle the rest.

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