Rosey

Rosey is an independent AI review platform for financial, scientific, and technical documents. It verifies claims against source data, simulates domain expert readers, applies automated fixes, and returns prioritized findings as tracked changes inside Word and PowerPoint. It also runs as an MCP server inside ChatGPT, Claude, or custom agents.

Rosey is a review layer for documents that were drafted with generative AI, by hand, or through some mix of the two. Its premise is straightforward: the same model that produced a document cannot reliably audit it, because doing so rewards its own confident phrasing and leaves its blind spots intact. Rosey therefore runs a separate review pass over financial, scientific, and technical material, checking claims against source data and flagging what the draft gets wrong. The company positions this as the verification step that legal, financial, software, and pharmaceutical workflows have always had, now applied to AI assisted authoring. The product does two main jobs. Claim verification traces every number, statement, and calculation back to a source of truth and sorts findings into verified, contradicted, or unsubstantiated. Audience simulation adds domain specific reviewers who read the document the way a real reader would, surfacing objections before distribution. Rosey then applies the fixes it can handle on its own and returns a ranked list of issues it cannot, with markup that behaves like tracked changes and comments in the editor rather than in a separate dashboard. The workflow suits analysts, consultants, compliance staff, and executives who are already using AI to produce investment memos, client deliverables, board materials, or regulatory filings and need a defensible check before those documents leave the building. Setup is lightweight: authors bring a Word or PowerPoint file, pick reviewers or reuse a project, and iterate on feedback. Rosey also ships as an MCP server for teams that prefer to stay inside ChatGPT, Claude, or their own agent. Against general purpose chatbots prompted to "review this," Rosey claims an advantage from being independent of the creation step and from reviewers tuned to a specific domain and corporate data. Against human review, the pitch is consistency and volume. Its own published benchmark on a Cracker Barrel earnings report claims roughly four times more errors caught than the average frontier model at a fraction of the false positive rate, though that result comes from a single document and should be weighed accordingly.