Paperguide Affiliate Program for Research and Literature Review Audiences

Paperguide fits researchers, students, librarians, academic educators, and evidence-workflow audiences because the current platform spans more than a single PDF chat. First-party documentation covers AI Search across a large research corpus, Research Agent, Literature Review Agent, systematic review workflows, Chat with PDF with page-level citations, structured data extraction, reference management, AI writing, and shared workspaces.

A useful affiliate review can start with a narrow research question, collect a small paper set, inspect source citations, build an extraction table, and carry the evidence into a literature-review or writing workflow. That gives readers concrete criteria around traceability and research organization without implying that AI synthesis replaces source checking or research judgment.

Paperguide's current affiliate page and help center agree that affiliates earn 25% of all referred payments and link to the branded affiliate signup. The public FAQ headings ask about cookie duration, payout limits, payment methods, and payout timing, but the accessible answers do not publish those values.

Paperguide also runs a separate Refer & Earn program with fixed-dollar rewards, a 30-day referral cookie, and Net-30 timing; those referral rules are a different program and should not be imported into the 25% affiliate offer. With no current first-party conflict on the 25% rate, the commission can support the CTA while unspecified affiliate fields remain omitted.

Research-method educators, academic productivity publishers, student and postgraduate communities, librarians, evidence-synthesis reviewers, and teams comparing literature-review workflows.

The strongest content follows one narrow question from search and source checking through extraction, organization, and a cited synthesis while showing where human judgment remains necessary.