Humata vs Paperlayer

Humata is a document question-and-answer service for finding information across uploaded files. Ask questions about document contents, search for answers, summarize findings, or compare documents; responses include citations that link to relevant sections in source files. Users can also embed Humata’s PDF AI in a webpage, while its API provides programmatic access to documents, conversations, and answers. The product is available on the web and through an API, with file uploads supported. The Free plan costs nothing and includes one user and up to 60 pages of monthly use. Expert costs $999 a month for three users and 500 pages, with $0.02 per additional page. Team costs $49 a month per user for 10 users and 5,000 pages, with $0.01 per additional page. Humata supports SAML 2.0 sign-on and states that it encrypts customer data at rest and in transit, is SOC 2 Type II compliant, and does not use user-provided data to train its models.

Paperlayer is a web-based AI reading layer for research papers, pairing summaries and contextual margin notes with evidence in the original PDF. You can find public arXiv papers by title or author, enter an arXiv ID or paste an arXiv link. Summaries cover the paper’s problem, method, results and caveats, while highlights mark claims, methods, results, problems and caveats with adjustable density. Margin notes explain terms, equations and figures beside the text. Summaries and notes support Korean, Japanese, Chinese, Spanish, French and German, and J and K keys navigate through a paper. Paper chat is marked “Soon.” The public demo covers public arXiv papers only and accepts no private or unpublished uploads. Paperlayer says live processing sends paper and request content to OpenAI over encryption without intentionally including account, cookie or anonymous identifiers.