Trellis AI
ActiveAI for streamlining healthcare paperwork
About
Trellis helps healthcare providers treat more patients, faster—while eliminating pre-service paperwork. We automate document intake, prior authorizations, and appeals at scale to streamline operations and accelerate care. Our AI agent is trained on millions of clinical data points and converts messy, unstructured documents into clean, structured data directly in your EHR. With Trellis, leading healthcare providers and pharmaceutical companies were able to: 1. Reduce time to treatment by over 90% 2. Improve prior authorization approval and reimbursement rates 3. Leverage structured data to enhance drug program performance and clinical decision-making Administrative costs account for over 20% of U.S. healthcare spending—delaying care, draining revenue, and driving staff burnout while having less visibility into patient care than ever before. We built Trellis to tackle this head on.
Founders · 2
AmazonMac is the co-founder and CEO of Trellis. Previously, he worked at the Stanford AI lab on large multimodal models for Stanford Health and built ML infrastructure at Cresta, Moveworks, and Amazon.
Jacky is a co-founder of Trellis and has taught hundreds of Stanford graduate students how to build, train, and deploy AI models in the Stanford School of Engineering & Graduate School of Business. Previously, he worked at Meta, the World Bank, and Wayfair.
Launch
Reduce time-to-treatment, improve reimbursement rates, and
Trellis automates document intake, prior authorizations, and appeals for healthcare providers, integrating with EHRs to reduce administrative bottlenecks and accelerate treatment. It targets providers handling pre-service documentation and approvals, aiming to cut time to treatment and improve reimbursement rates through AI-driven structured data and workflow automation.
From the original launch (Mar 2024) — may be outdated.
Formerly “Trellis”
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