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AI for streamlining healthcare paperwork
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.
Trellis AI provides AI agents to automate and streamline administrative and clinical workflows across the care journey, starting with specialty providers. The platform aims to reduce care gaps, speed time-to-treatment, and improve key business metrics by connecting healthcare nodes and automating processes.
Trellis AI embeds purpose-built AI agents that map and learn your existing workflows, convert proprietary data into executable processes, and execute end-to-end tasks. It handles tasks such as extracting clinical data from referrals, generating letters of medical necessity, submitting prior authorizations to payer portals, flagging denials, enrolling in PAP and clinical trials, triaging documents, running medical benefits and test claims, generating LMNs, and navigating payer portals. The system claims to compress days of manual work into minutes and provides self-improvement data to optimize processes and revenue capture.
Who it’s for: Specialty providers and healthcare organizations seeking to automate care-journey administrative and clinical workflows to reduce time-to-treatment, scale patient volume, and improve revenue.
Mention of demos/book-a-demo, pricing page presence, references to KPIs and outcomes; evidence of product-focused messaging and potential traction signals but no explicit funding/hiring data provided.
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.
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.
Medical chart intelligence
AI agents for healthcare admin
