ActiveTigger
ActiveTigger: A broad annotation and modeling workflow for teams working with text corpora. Ranked #1 of 16 in Active Learning Tools by our editors (9.0/10); pricing: Open source; best for collaborative corpus annotation and text modeling.
At a glance
- Editor score9.0 / 10
- PricingOpen source
- Best forCollaborative corpus annotation and text modeling
- Paid fromNone
- Human annotation workflowBuilt_in
- Facts checked24 Sep 2026
Where it wins
- Shared codebooks support annotation across collaborators.
- Active learning helps prioritize examples for annotation.
- Combines scikit-learn, BERT training, topic models, and export.
Where it doesn't
- Its primary audience is computational social scientists.
- The hosted CREST instance requires an account request.
- Self-hosting requires deployment on an organisation’s infrastructure.
Our verdict on ActiveTigger
ActiveTigger is an open-source web application for collaborative corpus annotation and classification, aimed primarily at computational social scientists. Teams upload tabular datasets, define shared codebooks, and annotate text together, with active-learning selection to prioritize examples. The workflow also supports multi-label and span annotation, making it suitable for projects that need more than single-label text classification. Its scope spans annotation, model-assisted work, and corpus exploration rather than focusing narrowly on labeling alone.
Modeling and exploration are central parts of the product. ActiveTigger supports quick classification models using scikit-learn, fine-tuned BERT training and evaluation, multilingual models, and BERTopic topic modeling. Corpus exploration includes projections, while query strategies include random, fixed, maximum-probability label, and active selection. Generative-AI tools are also included. Supported data types are text and images, though the product’s description emphasizes text corpora. This breadth may suit research teams that want annotation and model development within one workflow; teams seeking a focused general-purpose image annotation tool may prefer a more specialized option.
ActiveTigger is available as a cloud service or for self-hosting, and the vendor describes a hosted CREST instance that users can request access to by account request. The project is open source, with documentation, community, and email support channels. Its published positioning makes self-hosting relevant for organizations that want to run the software on their own infrastructure, while the account-request route is the path described for the hosted instance. Choose ActiveTigger if collaborative text annotation, active selection, and model-assisted corpus analysis belong together in your work. It is a less natural fit for teams that need a broadly packaged commercial service or whose main task is outside corpus-oriented text research.
ActiveTigger pricing
ActiveTigger fact sheet
| Free plan | Not verified |
|---|---|
| Paid from | None |
| Query strategies | Random; Fixed; Max prob LABEL; Active; Active LABEL |
| Human annotation workflow | Built_in |
| Supported data types | text; images |
| Model frameworks | scikit-learn; Hugging Face; BERT |
| Deployment options | Both |
| Deployment | Cloud, Self-hosted |
| Platforms | Web |
| Support | Email, Community, Docs |
| Built for | Solo, Small business, Mid-market (editorial estimate) |
| Pricing | Open source |
| Website | activetigger.com |
| Facts checked | 24 Sep 2026 |
Alternatives to ActiveTigger
- PotatoA self-hosted annotation toolkit for teams combining active learning with varied media.8.2
- ProdigyA paid, developer-oriented annotator spanning NLP, vision, audio, and video.7.7
- DataloopA collaborative labeling platform with model-assisted workflows, APIs, and cloud integrations.7.4
See all ActiveTigger alternatives →
ActiveTigger vs the competition
- ActiveTigger vs Potato
- ActiveTigger vs Prodigy
- ActiveTigger vs Dataloop
- ActiveTigger vs Encord
- ActiveTigger vs LightlyStudio
- ActiveTigger vs Label Sleuth
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Reviewed by iTechGuides Editors · Editorial team · Updated Sep 2026
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