Every answer
deserves context.
AI-assisted survey coding. Your codebook. Your judgment. Less manual work.
Turn a spreadsheet of open-ended responses into a thoughtful coding workflow—with clear rules, connected questions and room for your expertise.
LabelOwlLearning experiences
What helped your learning?
3 answersImported from course-feedback.xlsx · shared respondent IDs
Select an answer to try the review workspace.
Your codebook. Your judgment. A clear path to delivery.
Room for your research.
Create a verified account and start your free preview. Seven days of Pro and 200 AI coding runs are added automatically on your first workspace visit.
7 days of Pro. 200 AI coding runs.
A one-time welcome allowance, not a monthly refill. One answer, one successful coding run, one use. No card or automatic renewal.
Your Pro preview lasts 7 days. Your 200 welcome runs last 30 days from activation, with exact dates in Account & usage. One welcome offer per verified email; no monthly refill.| What you can do | Free | Pro trial · 7 days |
|---|---|---|
| Workspaces | 2 editable single-question works | Projects, surveys & multiple questions |
| Codebooks | Your own codes, including hierarchies | Reuse codebooks across projects |
| Review & export | Manual coding, review, Excel & CSV | The same tools, across your projects |
| After the trial | Keep coding manually in Free | Projects remain available to view & export |
More capacity, when you need it.
Beta plans · provisional pricing and monthly allowances, not available to purchase. Unused monthly runs will not roll over.
NanoBeta*
288 runs / month
Occasional projects
Planned · before taxProBeta*
1,188 runs / month
Light research use
Planned · before taxMaxBeta*
3,666 runs / month
Regular larger studies
Planned · before taxUltraBeta*
7,888 runs / month
High-volume workflows
Planned · before taxFrom scattered answers
to a shared structure.
Bring the survey as it is. Make the framework yours. Keep the important decisions visible.
- 01
One file. Multiple questions.
Import Excel or CSV, preview the worksheet and choose the open-ended columns. Respondent IDs connect answers across questions.
- 02
Rules that reflect your research.
Import or write your codebook. Add context, boundaries and hierarchy only where they help. Save changes as traceable versions.
- 03
Your judgment, throughout.
Test AI suggestions, save your review decisions, then compare results and export the data you need.
What shaped your experience?
“The examples were useful,
but I needed more time.”
Code explicit experiences. Do not infer an overall satisfaction score.
Better questions.
More grounded labels.
We test the details that matter: question wording, study scope and category boundaries. Here is what one small diagnostic taught us.
Constructed boundary cases, with question and study context.
A diagnostic result—not a general accuracy guarantee. Your codebook and data still need validation.
| Input condition | Exact sets |
|---|---|
| Codebook only | 25 / 30 |
| + question & study scope | 29 / 30 |
| + explicit boundaries & examples | 29 / 30 |
Method & real-survey comparison
30 constructed cases; eight category judgments per answer; jev-1.13.0; threshold 0.5. Expected labels were fixed before inference. These fixtures are not independent real survey respondents. The minimal arm deliberately omits question and study scope.
On a separate public survey sample of 30 responses and 35 categories, richer context yielded 21/30 exact label sets versus the published reference (precision 83.9%, recall 92.2%). The reference was not independently adjudicated as a human gold standard. These are different experiments, not interchangeable accuracy claims.
Read the experiment notes ↗Less busywork. More understanding.
Start with your survey or a specific question, and a framework you trust.