---
title: TriFetch Raises $1.9M to Bring AI Automation to Independent Specialty Clinics
description: San Francisco AI startup TriFetch has raised $1.9M from Nexus Venture Partners to automate calls, referrals, and prior authorizations at specialty clinics.
author: Darie Nani (Editor-in-Chief)
date: 2026-04-27T11:59:08.182Z
updated: 2026-06-03T13:10:35.649Z
canonical: https://www.sovereignmagazine.com/article/trifetch-1-9m-ai-specialty-clinics
image: https://cdn.nanimediahouse.com/trifetch-founders.webp
categories: Artificial Intelligence, Startups
content_type: Spotlight, News
region: San Francisco
publication: Sovereign Magazine
about:
  - type: Organization
    name: TriFetch
    description: TriFetch is an AI automation platform for independent specialty clinics and multi-specialty groups, automating patient calls and scheduling, referral processing, and prior authorization. The platform is EMR-agnostic, integrating with systems like NextGen, eClinicalWorks, and athenahealth without requiring migration or staff retraining. Co-founded by Varuni Sarwal and Rosemary He, both UCLA Computer Science PhDs, TriFetch is based in San Francisco.
    url: https://www.trifetch.ai/
    industry: healthtech
---

Inside one independent specialty practice already using TriFetch, two staff members spend full shifts processing up to 100 patient referrals a day and [calling patients to schedule them](https://www.sovereignmagazine.com/article/your-doctor-s-phone-system-is-broken-can-confido-s-ai-voice-agents-actually-fix-it). A single prior authorization can take 45 minutes by phone or fax. The voicemail inbox runs into the hundreds. TriFetch, an AI automation startup based in San Francisco, has raised $1.9 million in pre-seed funding to take that work off staff entirely.

The round was led by Nexus Venture Partners, with participation from operators at Google, Hippocratic AI, Mercor, and MIT. The capital is going toward scaling the company's automation platform across the front, mid, and back office of independent specialty care.

## How TriFetch Automates Calls, Referrals, and Prior Authorization

TriFetch is a healthcare AI startup that automates three administrative workflows at the same time. Its multilingual voice agent runs inbound and outbound patient calls, books appointments, and handles follow-ups. Its referral engine routes incoming faxes and portal referrals to the right clinician, verifies eligibility, and schedules patients with a human kept in the loop on clinical judgment. Its AI prior authorization layer submits and tracks requests across payer portals so paperwork delays do not push costs onto patients.

The platform is EMR-agnostic. It plugs into NextGen, eClinicalWorks, athenahealth, and other systems already in use, with no migration or staff retraining required.

In a gastroenterology practice already running TriFetch, the system handles roughly 100 referrals a day end-to-end, freeing about 16 hours of staff time and returning more than $200,000 a year to the clinic. The company says a mid-size specialty practice can recover between $500,000 and $1.4 million annually once calls, referrals, and prior authorizations are all automated.

## Why Independent Specialty Clinics Have Been Left Behind on AI

According to the 2025 CAQH Index, US healthcare avoided $258 billion in costs through automation in 2024. Most of that capture has been concentrated in enterprise health systems with the budgets and IT teams to deploy it. Independent specialty clinics, where 22 percent of US physicians still practice, have not seen those gains.

The math gets harder every year. Specialists spend roughly 25 minutes on each [prior authorization](https://www.sovereignmagazine.com/article/the-billion-dollar-phone-problem-the-hard-numbers-behind-ai-agents), and a recent American Medical Association survey found that 61 percent of physicians believe AI is increasing prior authorization denial rates rather than reducing them. Labor costs are rising. Burnout is up. The default response, hiring more administrative staff, only adds to overhead.

Several companies have built large businesses around the edges of this problem. Abridge, Ambience Healthcare, Suki, and Nabla all sell ambient AI scribing into enterprise health systems. [Cohere Health](https://www.sovereignmagazine.com/article/coral-healthcare-automation-seed-lightspeed-z47) processes prior authorizations from the payer side. None of them have gone deep into the buyer TriFetch is targeting: the independent specialty clinic with no procurement department.

## Inside the Investor Round

[Nexus Venture Partners](https://www.sovereignmagazine.com/article/triomics-raises-22m-oncology-ai) runs about $3.2 billion across the US and India and is best known for developer tools and consumer software. Postman, Apollo.io, Hasura, MinIO, Druva, and Zepto are all in the portfolio. Lead partner Jishnu Bhattacharjee has historically focused on infrastructure and SaaS bets including Postman, Druva, and Observe.ai, which makes TriFetch one of the firm's first significant moves into US provider-side healthcare AI.

The angel list is the more revealing signal. Operators from Hippocratic AI, the patient-voice startup most recently valued at around $3.5 billion, are backing TriFetch alongside investors from Google, Mercor, and MIT. Hippocratic AI builds voice agents that talk to patients on behalf of health systems. TriFetch builds for the staff side of the same call.

"Varuni and Rose are deep domain experts in healthcare AI," said Bhattacharjee. "Healthcare administrative workflows represent one of the largest untapped opportunities for AI, and the TriFetch team is uniquely positioned to unlock it."

## The Founders Behind TriFetch

TriFetch was co-founded by Varuni Sarwal, the company's CEO, and Rosemary He, its COO. Both are Computer Science PhD candidates at UCLA, where they were advised in the same lab.

Sarwal's research applied machine learning to electronic health records to predict perinatal depression and urosepsis, with work published in peer-reviewed medical venues. He's research used computer vision and generative models to map Alzheimer's progression in longitudinal medical imaging, including work presented at ICML, one of the leading machine learning conferences.

The pair have taken what they call a forward-deployed approach, embedding alongside clinic teams in California while the product is being built. The pilots already running cover ophthalmology, cardiology, and gastroenterology, and the company has signed up a founding cohort of more than ten advisors drawn from operators at NextGen, Sutter Health, Johns Hopkins, Mayo, UW Health, Revere Health, Springfield Clinic, and UChicago Medicine.

"Clinics are doing everything they can to keep up, but the administrative workload keeps expanding," Sarwal said. "We built TriFetch to plug into how clinics already run and take the tasks staff dread the most off their plate, calls, referrals, and prior auth, so teams can focus on the parts of care that require the human touch."

## What Comes Next for TriFetch

The near-term plan is to expand from California into more states, deepen the company's EMR integrations, and connect more of the third-party tools clinics already rely on. Longer term, TriFetch is positioning itself as the operating layer for independent specialty practices, multi-specialty groups, and eventually hospital-owned networks.

Dhruv Miyani, Founding Engineer at TriFetch, added: “The development of browser-use agents has changed what’s possible in healthcare automation. We can now build deeply customised workflows across many specialties that navigate EMR systems just like a human staff member.”

Larger ambient AI companies are also moving into administrative work, and TriFetch's pace inside specialty clinics will determine whether it stays ahead of them as the category opens up.

**About TriFetch**

TriFetch is an AI automation platform for independent specialty clinics and multi-specialty groups, automating patient calls and scheduling, referral processing, and prior authorization. The platform is EMR-agnostic, integrating with systems like NextGen, eClinicalWorks, and athenahealth without requiring migration or staff retraining. Co-founded by Varuni Sarwal and Rosemary He, both UCLA Computer Science PhDs, TriFetch is based in San Francisco.

[Website](https://www.trifetch.ai/)

## FAQ

**Q: What is prior authorization in healthcare?**
Prior authorization is a process where a physician must get approval from a patient's health insurer before a specific treatment, medication, or procedure can be provided. It is intended to control costs and prevent unnecessary care, but in practice it has become one of the largest administrative burdens in American medicine. Specialty clinics in particular spend long hours per patient submitting paperwork, calling payers, and waiting for decisions, which delays care and adds cost.

**Q: How is AI used in clinics?**
AI is being used in clinics in two broad ways. Ambient AI scribes listen to clinical conversations and generate notes, summaries, and orders. Administrative AI handles back-office work like patient phone calls, appointment scheduling, referral routing, and prior authorization submissions. The administrative side is where most independent specialty clinics see the largest near-term savings, because it directly replaces work that has historically required additional staff.

**Q: What is referral management software?**
Referral management software helps clinics process incoming patient referrals, verify insurance eligibility, schedule appointments, and track where each patient sits in the clinical workflow. Modern systems use AI to read inbound faxes and portal messages, route them to the correct clinician, and book patients automatically, with humans reviewing clinical judgment calls. The goal is to reduce the time staff spend manually triaging referrals, which in busy specialty practices can run into hours per day.

**Q: How is EHR different from EMR?**
An EMR, or electronic medical record, is the digital version of a single practice's chart for a patient. An EHR, or electronic health record, is designed to be shared across multiple providers and care settings. In day-to-day clinic operations the two terms are often used interchangeably, but EHRs typically include broader patient histories pulled from different organizations. AI tools in healthcare are usually described as EMR-agnostic when they can integrate with any of the major systems regardless of which standard the clinic is on.