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Colandr review

Free#23 of 38 in AI Literature Review SoftwareSystematic Review SoftwareLiterature Review Software

A free, collaborative workspace for screening and extracting evidence from research.

7.1/10Editor score
Colandr7.1 Visit Colandr

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Colandr is a free, open-source web platform for evidence reviews and systematic evidence syntheses. It is designed for collaborative review teams that need to structure searches, import citations, remove duplicates, screen titles and abstracts, review full-text PDFs, and export decisions and extracted data. Reviewers retain final control over inclusion, exclusion, and classification decisions while machine learning and natural language processing assist with relevance ranking, document classification, and full-text extraction.

Its workflow covers several core stages of a review. Teams can work together, cross-check decisions, get assistance with Boolean search strings, and import citations in BibTeX or RIS formats. Citation deduplication helps organize imported records, while machine-learning-assisted screening supports title and abstract review. PDF uploading and NLP-assisted full-text data extraction extend the process beyond initial screening, and CSV export provides a practical way to move screening decisions and extracted data into other workflows. These capabilities make Colandr a focused option for teams seeking a structured review process without a paid plan.

Colandr is strongest when the priority is collaborative screening and evidence extraction in an open-source environment. Its narrower ecosystem may be less suitable for teams that depend on verified database integrations, extensive reporting, or advanced synthesis features. Review teams looking for a free web-based workspace with AI-assisted screening, deduplication, PDF handling, and CSV export should consider it. Teams that need broader integration coverage or deeper reporting and synthesis capabilities should look for an alternative built around those requirements.

Colandr pros and cons

  • Where it wins
    • Free and open source for collaborative evidence reviews
    • Machine-learning-assisted title and abstract screening
    • Deduplication, PDF extraction, and CSV export in one workflow
  • Where it doesn't
    • Limited verified database integrations
    • Reporting and synthesis features are limited
    • Available as a web platform only

Colandr fact sheet, pricing and score →

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