MindPeer

MindPeer starts from a diagnosis of what goes wrong with AI-assisted research: without context, analysts default to generic static templates, and leaders receive summaries that cannot be defended when the decision matters. MindPeer inserts a structured workflow between the analyst and the senior leader, beginning with context elicitation where the analyst briefs the platform's Intellibot on the question, audience and priority before any research happens.

During research, MindPeer uses retrieval-augmented generation to extract answers from uploaded documents and attaches sentence-level references to each finding in the report. Source evaluation is treated as part of the work product, so conclusions arrive tied to assessed evidence instead of floating free. Findings carry confidence ratings, and an explicit gap register states what remains unknown, which is often the detail that high-stakes readers care about most.

The company positions the product for teams where being wrong is expensive: national security and intelligence analysts following established tradecraft, strategy and competitive intelligence groups, business development doing due diligence, governance, risk and compliance functions, and discretionary investment teams that need to capture the reasoning behind a position and monitor the assumptions it rests on. Reports are scoped to a specific leader, decision and context rather than being one-size-fits-all. MindPeer comes from Mind-Alliance, whose background in competitive and market intelligence the company cites in customer references.