
Healthcare
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Revenue Cycle Management
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YC W26
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Valuation:
Undisclosed

Last Updated:
March 24, 2026

Builds an AI-powered prior-authorization automation platform that uses LLMs and NLP to auto-generate, submit, track, and appeal prior-auth requests for private medical practices.
Full-cycle prior-auth automation: EMR data extraction, payer-specific language optimization, real-time status tracking, automated appeals including phone calls. Deep EMR/PM integration. HIPAA compliance. CMS-0057-F readiness.
RPA bots for payer portal interactions and LLM pipelines for clinical document understanding. Predictive denial analytics and automated evidence gathering as next features. Expansion toward pharmacy prior-auths and broader payer connectivity.
AI auto-generates and submits payer-optimized prior-authorization requests by extracting clinical data from EMRs and tailoring language to each insurer's requirements.
The AI reads your patient's chart, writes the perfect insurance request in each payer's preferred language, and submits it automatically—so your staff doesn't have to.
It's like having a multilingual translator who knows exactly how each insurance company likes to hear "please approve this," and never gets tired of filling out forms.
AI predicts denial risk before submission and auto-generates clinically-grounded appeal letters with supporting evidence when denials occur, including handling payer phone calls.
The AI spots which requests are likely to get denied before you even submit them, then automatically writes and files a bulletproof appeal if one does get rejected.
It's like having a lawyer who reads the judge's mind before trial, rewrites your argument to match, and if you still lose, instantly files a perfect appeal with all the receipts.
AI continuously monitors prior-auth status across all payers, predicts bottlenecks and delays, and autonomously triggers follow-up actions to prevent authorization lapses.
The AI watches every pending authorization like a hawk, predicts which ones are about to stall, and automatically nudges the right people or systems before anything falls through the cracks.
It's like having an air traffic controller for your insurance paperwork—constantly scanning the radar, rerouting anything that's about to stall, and making sure every authorization lands safely before the patient's appointment.
Nami Lindquist (Penn M&T, BS Economics + BAS CS + Accelerated MSE CS from Wharton + Engineering dual degree) deliberately quit SpaceX SWE to embed herself in prior-auth workflows at Living Well Clinics for 3 months before building the product, giving ClaimGlide an authenticity and workflow-depth advantage that pure-tech competitors lack. She also has experience as a hospital researcher at Penn Medicine and led Penn Hyperloop's $135K fundraising (largest ever by a Penn student team).