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Bango

Free#24 of 30 in Systematic Review Software

Bango: A free, open-source desktop workspace for AI-assisted systematic reviews. Ranked #24 of 30 in Systematic Review Software by our editors (6.6/10); pricing: Free plan; best for local, free, AI-assisted reviews.

6.6/10Editor score

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Bango6.6 Visit Bango

At a glance

Editor score
6.6 / 10
Pricing
Free plan
Best for
Local, free, AI-assisted reviews
Free plan
Yes
Paid from
Free
Reference deduplication
Yes
Facts checked
20 Sep 2026

Where it wins
- Free, open-source use with no subscription, paywall, or account
- Runs on Windows, macOS, and Linux with local data storage
- Combines screening, deduplication, PDFs, PRISMA, and bibliometrics
Where it doesn't
- Its workflow centers on local desktop use rather than a hosted team workspace
- AI screening requires researcher-defined criteria and provider configuration
- Blinded screening is not established in the published feature set

Our verdict on Bango

Bango is free, open-source desktop software for researchers conducting systematic literature reviews. It imports RIS and BibTeX records, identifies duplicate references, supports user-defined inclusion and exclusion criteria, and stores research data locally on Windows, macOS, and Linux. Its scope extends from initial reference management through full-text review, structured article comparison, bibliometric analysis, citation networks, PRISMA 2020 flow diagrams, and a local wiki knowledge base with AI summaries.

The main strength is breadth within a local workflow. Bango combines automatic and manual deduplication with full-text PDF and text-file attachment and extraction, study-variable comparison, and PRISMA reporting. It also connects with Zotero, OpenAlex, PubMed, Scopus, and Web of Science for research discovery and reference workflows. For AI assistance, the published integrations include Google Gemini, Anthropic Claude, OpenAI, Ollama, and LM Studio, giving researchers options across hosted and local providers. The Free plan is open source under Apache 2.0 and has no subscription, paywall, or account requirement.

Bango is a strong fit for individual researchers or teams that prioritize local control, broad review functionality, and flexible AI-provider choices without a software subscription. Its desktop orientation is less suitable for buyers seeking a browser-based collaboration environment, and AI-assisted screening still depends on clearly defined criteria and configuration with a supported provider. Researchers who require a verified blinded-screening workflow or a hosted team workspace should choose a product explicitly built around those needs instead.

Your product? Our editors can test Bango in depth and publish a review, labelled as paid · from $149/mo →

Bango pricing

Plans Free planFree Free to use — no paid tier required for the core job.

See plans on bango.boncode.net

All 1 Bango plans and prices →

Bango fact sheet

Free plan	Yes
Paid from	Free
Reference deduplication	Yes
Blinded screening	Not verified
Data extraction	Yes
Full-text storage	Yes
Protocol support	Yes
Collaborator limit	Not verified
Review types	systematic review
Deployment	Desktop
Platforms	Windows, macOS, Linux
Support	Docs
Built for	Solo, Small business (editorial estimate)
Integrations	10 integrations: Zotero, OpenAlex, PubMed, Scopus, Web of Science, Google Gemini …
Pricing	Free plan (source)
Website	bango.boncode.net
Facts checked	20 Sep 2026

Bango integrations

Bango lists 10 integrations on its own site.

Zotero
OpenAlex
PubMed
Scopus
Web of Science
Google Gemini
Anthropic Claude
OpenAI
Ollama
LM Studio

Alternatives to Bango

See all Bango alternatives →

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The editor score above is our own research. What this page doesn't have yet is a reader's view — what you used Bango for, what worked and what didn't. No stars are seeded and no review is paid for; an editor reads every one before it appears.

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Featured on iTechGuides

Bango is listed in our Systematic Review Software directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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Last updated 7 Oct 2026 · How we research and update