AttendMe

AttendMe

Multi-Agent Medical AI For Physicians

90 followers

AttendMe is a multi-agent clinical decision support platform built for healthcare professionals Three specialised agents work across 1.5 million curated peer-reviewed articles to deliver evidence synthesis at the point of care: • Chat Agent: Clinical Q&A with real-time citations • Library Agent: Deep analysis of saved literature by study • Discovery Agent: Advanced search with evidence-level filter
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AttendMe gallery image
AttendMe gallery image
AttendMe gallery image
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AttendMe gallery image
Free
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Harry Power
Maker
📌
Hey Hunters! I'm a physician-developer. I built AttendMe to create a complete clinical workflow suite that saves time at the point of care and during research. The core problem: medical knowledge exists, but finding the right evidence when you need it takes too long. You're managing patients, preparing for rounds, or reviewing literature—and the overhead of search becomes the bottleneck. AttendMe uses three specialised agents for different clinical tasks: Chat Agent: Rapid clinical Q&A with real-time citations from 1.5M curated articles. Specialty-specific search across 34 medical fields means results are clinically relevant, not just keyword matches. Library Agent: Deep analysis of saved papers. Ask methodology questions, compare studies, identify limitations. Built for journal club prep and systematic review. Discovery Agent: Algorithmic search combined with systematic evidence appraisal. Uses established frameworks to evaluate study quality and evidence hierarchy—the same frameworks you'd apply manually, but automated. Articles are ranked by study design, journal tier, citation impact, and clinical relevance. Every claim links directly to source with full citation transparency. We built this to work the way clinicians actually work: rapid answers when you need them, deep analysis when you have time, and systematic discovery when you're doing research. Free to try at attendme.ai and downloadable on iOS and Android also. Lots of features in development—would value feedback from the community.