Qualitative analysis
with AI you can audit.
QualiLens runs five established qualitative methods — from grounded theory to literature synthesis — with LLM coding that pauses for your review, keeps verbatim provenance on every excerpt, and never touches a server we control.
Five steps to a complete analysis
The wizard walks you through method selection, configuration, model choice, data upload, and cost estimation — then the pipeline runs, pausing at each checkpoint for your review.
Choose a method
Grounded theory, thematic analysis, content analysis, framework coding, or literature synthesis.
Configure
Set your research question, method-specific options, and any codebook or framework.
Pick a model
Anthropic, OpenAI, Google, or Mistral — your key, your account, direct connection.
Upload data
Drag in documents, PDFs, or recordings. Transcription runs automatically.
Review & run
See a cost estimate, start the pipeline, and approve each checkpoint.
Five established methods
Each method follows its own epistemology. QualiLens implements distinct pipelines with method-appropriate stages, checkpoints, and figures.
Grounded Theory
- Stages
- Familiarization, open coding, axial coding, selective coding
- Checkpoints
- Code review, core category, theoretical model
- Report figure
- Paradigm flow model
Thematic Analysis
- Stages
- Familiarization, initial coding, theme construction, theme review
- Checkpoints
- Code review, theme refinement
- Report figure
- Thematic map
Content Analysis
- Stages
- Codebook derivation or import, systematic coding
- Checkpoints
- Codebook approval, frequency review
- Report figure
- Frequency bar chart
Framework Coding
- Stages
- Apply framework, chart by source, build matrix
- Checkpoints
- Low-confidence review, emergent codes, matrix
- Report figure
- Framework heatmap
Literature Synthesis
- Stages
- Structured extraction, cross-paper synthesis, concept matrix
- Checkpoints
- Extraction table, concept review
- Report figure
- Concept-by-paper heatmap
Built for researchers
Every method follows published methodological commitments. The wizard records your choices verbatim so your methods section writes itself.
Explore all featuresWhat makes QualiLens different
Researcher-led checkpoints
The pipeline pauses at every analytic decision point. Your edits are final and are never overwritten by later automated stages.
Provenance on every excerpt
Every coded passage stores the verbatim quote and its character position. The coded-source reader draws coding over each document in place.
Full audit trail
Every stage boundary, model call, and researcher decision is logged. The report appendix reproduces this trail for reviewers.
Runs locally
No QualiLens server. Your data goes only to the AI provider you chose, over a direct API connection. Nothing is collected.
Four providers, your key
Anthropic, OpenAI, Google, and Mistral. Cost estimation before every run, and resumable runs that never re-bill finished work.
Reports and Word export
Interactive report with narrative sections, method-appropriate figures, full evidence chains, and one-click Word export.
Your data stays on your computer.
No QualiLens server, no telemetry, no analytics, no background connections. Analysis calls go directly to the provider whose key you supplied — and nowhere else.
Read the full privacy statementReady to start?
QualiLens needs Python and an API key. A first analysis on one short document costs cents, not dollars.
If QualiLens contributes to your research, please cite it:
Aggarwal, A., & Commuri, S. (2026). QualiLens [Computer software].