Trellis AI

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.

High-Level Overview

Trellis AI is an AI-driven healthcare technology company focused on streamlining healthcare paperwork to help providers treat more patients faster by automating administrative tasks such as document intake, prior authorizations, and appeals. Their AI agent processes unstructured clinical documents into structured data integrated directly into Electronic Health Records (EHR), significantly reducing delays and administrative costs that currently consume over 20% of U.S. healthcare spending. Trellis serves healthcare providers and diagnostic labs, addressing bottlenecks that delay treatment and reduce revenue, while improving operational efficiency and patient care speed[1][2].

Founded as a spinout from the Stanford AI Lab, Trellis AI leverages deep expertise in language models and machine learning to build a scalable solution that reduces time-to-treatment, increases reimbursement rates, and lowers operational expenses for healthcare organizations. Their growth momentum is supported by backing from prominent investors including Y Combinator, General Catalyst, and executives from Google and Salesforce, with adoption by leading healthcare organizations[1][2].

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Origin Story

Trellis AI was founded by Mac and Jacky, friends from the Stanford AI Lab with backgrounds in building large language models and machine learning infrastructure. Mac previously worked on ML pipelines at Cresta and Moveworks, while Jacky taught AI at Stanford and worked at Meta on real-time ML systems. The idea emerged from their shared experience with AI and a desire to solve the pervasive problem of healthcare administrative inefficiencies, particularly in prior authorizations and paperwork that delay patient care. Early traction came from demonstrating the AI’s ability to process hundreds of pages per patient case, identifying missing information, and accelerating approvals, which resonated strongly with healthcare providers burdened by manual workflows[1].

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Core Differentiators

• Product Differentiators: Trellis AI’s system is trained on millions of clinical data points and medical ontologies, enabling it to extract, tag, and route complex healthcare documents with high accuracy and context awareness. It automates prior authorization submissions, eligibility checks, and appeals, reducing errors and speeding approvals[1][2].

• Developer Experience: Built on advanced language models and ML pipelines, Trellis integrates seamlessly with existing EHR systems, minimizing disruption and maximizing scalability.

• Speed and Pricing: By automating labor-intensive paperwork, Trellis reduces time-to-treatment from day one and lowers operational expenses within weeks, offering a rapid ROI for healthcare providers[2].

• Community Ecosystem: Backed by a strong network of investors and healthcare partners, Trellis benefits from continuous feedback and collaboration with leading healthcare organizations to refine and expand its AI capabilities[1].

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Role in the Broader Tech Landscape

Trellis AI rides the growing trend of AI-powered automation in healthcare administration, addressing a critical pain point where administrative costs and manual processes delay patient care and increase burnout. The timing is crucial as healthcare systems face increasing pressure to improve efficiency, reduce costs, and enhance patient outcomes. Market forces such as rising healthcare spending, regulatory complexity, and the digitization of medical records favor AI solutions that can scale and integrate with existing workflows. Trellis influences the broader ecosystem by demonstrating how AI can transform back-office healthcare operations, enabling providers to focus more on patient care rather than paperwork[1][2].

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Quick Take & Future Outlook

Trellis AI is well-positioned to expand its impact as healthcare providers increasingly adopt AI-driven automation to tackle administrative burdens. Future trends shaping their journey include broader adoption of AI in clinical workflows, increasing regulatory demands for data accuracy and transparency, and the growing need for interoperability in healthcare IT systems. Trellis’s influence may evolve from a document automation tool to a comprehensive AI assistant that supports multiple facets of healthcare administration and patient management, potentially integrating predictive analytics and personalized care pathways. Their foundation in Stanford AI Lab research and strong investor backing provide a robust platform for sustained innovation and growth[1][2].

Trellis AI exemplifies how cutting-edge AI can address entrenched inefficiencies in healthcare, promising faster, more efficient care delivery that benefits providers and patients alike.