MonkeyLearn alternative
MonkeyLearn Alternative for Text Clustering and Theme Discovery
Looking for a MonkeyLearn alternative? Apercu groups survey responses, reviews and support tickets into AI-labeled themes without model training.
By Apercu team · Last updated
MonkeyLearn was a no-code text analysis platform for classification, extraction and topic discovery. Since its 2022 acquisition by Medallia, teams that used it for standalone text analysis often need a simpler replacement. Apercu covers the theme discovery part: upload a CSV or Excel file and get AI-labeled themes without training a custom model.
What happened to MonkeyLearn?
CB Insights lists MonkeyLearn as acquired by Medallia in February 2022, and MonkeyLearn's LinkedIn page is now archived. The standalone product, which many teams used to build custom text classifiers and explore topics, is no longer sold as an independent self-serve tool.
For teams that used MonkeyLearn to find themes in open-ended text, Apercu covers that workflow directly: upload your file, get AI-labeled themes and export the results.
How Apercu is different from MonkeyLearn
No training data needed. MonkeyLearn's custom classifiers needed labeled examples before they could categorize text. Apercu finds themes without examples or a codebook.
Results in minutes. With MonkeyLearn you defined a model, built training data, trained it and iterated. With Apercu you upload a CSV and read labeled themes in the same sitting.
Built for theme discovery. Instead of fitting text into categories you define in advance, Apercu shows you the themes that already exist in your data.
MonkeyLearn vs Apercu: comparison
MonkeyLearn details describe its standalone product before the Medallia acquisition.
| MonkeyLearn | Apercu | |
|---|---|---|
| Current status | Acquired by Medallia in February 2022 | Active, independent |
| Pricing | No standalone self-serve plan today | Free, paid plans from $14.99/mo |
| Access | Part of Medallia's platform | Instant self-serve signup |
| Model training | Labeled examples needed for custom models | None |
| Theme discovery | Required setup | Automatic on upload |
| Theme labels | Categories you define | AI proposes labels |
| Custom text classification | Yes | No (theme discovery only) |
| API | Yes | No |
| Exports | CSV, JSON, integrations | JSON on all plans; CSV, Excel and PDF report on paid plans |
| Rows per analysis | Varied by plan | Up to 100,000 (Pro) |
Is Apercu the right replacement for you?
Apercu is a good fit if you used MonkeyLearn to discover topics in survey responses, reviews or support tickets, and want AI theme labels without defining categories first.
Look elsewhere if you need to classify text into categories you define in advance, train and tune custom models, extract keywords or entities, or call an API from an automated pipeline.
Popular MonkeyLearn replacement workflows
- Analyze open-ended survey responses without building a training set
- Categorize customer feedback from NPS comments, support tickets and reviews
- Extract themes from product reviews on G2, Capterra and app stores
- Automate thematic analysis instead of coding every response by hand
- Compare Apercu with Thematic if you are also evaluating enterprise platforms
- Compare Apercu with Caplena for AI coding of survey responses
Frequently asked questions
What happened to MonkeyLearn?
MonkeyLearn was acquired by Medallia in February 2022 and its capabilities moved into Medallia's enterprise customer experience platform. Its company LinkedIn page is now archived, so teams that relied on MonkeyLearn as a standalone, self-serve text analysis tool have been looking for alternatives.
Is Apercu a good MonkeyLearn alternative for thematic analysis?
Yes, if you used MonkeyLearn to discover topics in text rather than to build custom classifiers. Apercu groups your responses into themes, labels them with AI and, on paid plans, writes a report, without any training data or labeled examples.
Do I need to train a model with Apercu like I did with MonkeyLearn?
No. MonkeyLearn's custom classifiers needed labeled training examples. Apercu groups responses that talk about the same thing and uses AI to name each group, so there is nothing to train.
What if I need text classification rather than thematic analysis?
Apercu focuses on discovering and labeling the natural groups in your text. If you need to sort text into categories you define in advance, or need an API for automated classification, Apercu is not the right tool. If you want to find out which themes exist without knowing them in advance, it is the faster option.
How long does it take to get results in Apercu compared to MonkeyLearn?
With MonkeyLearn you defined a model, created training examples, trained it and checked its accuracy before running it. With Apercu you upload a CSV and get labeled themes in minutes, with no setup or training.