The New York startup has built AI that reads handwritten fax forms, processes prior authorisations, and completes patient intakes in under five minutes, all without asking providers to change how they work. It has reached multiple millions in revenue in under a year and is targeting 4x growth by end of 2026.
Coral, the New York-based AI startup automating administrative workflows for specialty healthcare providers, has raised $12.5 million in a Series A led by Lightspeed and Z47.
The company was founded in 2024 by Ajay Shrihari, a robotics and AI researcher, and Aniket Mohanty, who has a background in medical image processing.
In under a year of commercial operation, Coral has reached multiple millions in annual revenue and is targeting 4x growth before the end of 2026.
The 💜 of EU tech
The latest rumblings from the EU tech scene, a story from our wise ol’ founder Boris, and some questionable AI art. It’s free, every week, in your inbox. Sign up now!
The problem Coral is solving is not technological complexity, it is administrative volume. In American healthcare, every appointment generates a trail of prior authorisation requests, referral packets, insurance eligibility checks, and discharge paperwork.
Much of this flows through fax machines, which remain deeply embedded in clinical workflows despite being a technology from a previous era.
Rather than attempting to replace fax infrastructure, an approach that would require providers to rebuild systems they cannot afford to rebuild, Coral connects to existing EHR systems, fax lines, and payer portals and automates around them.
Providers do not change how they work. Coral changes what happens inside that workflow.
The company began in the durable medical equipment sector, one of the most fax-intensive corners of outpatient care, where a single order can require multiple rounds of documentation before approval.
DASCO, a home medical equipment provider, has been an early customer, describing turnaround times dropping from hours or days to minutes.
Coral then extended the same model into infusion centres, where a delayed authorisation means a missed dose, not a delayed appointment, and into specialty pharmacy.
In each new vertical, the same administrative bottleneck appeared in the same shape.
The product’s core capability is document understanding at healthcare’s specific level of messiness: handwritten fax forms, scanned insurance cards, prior authorisation templates, and payer portal screens.
Coral’s models have reached 99.7% accuracy across these document types, a threshold the company describes as the minimum viable standard for healthcare, where errors have clinical and financial consequences.
Complete patient intakes, including complex cases, now run in under five minutes. When information is missing, which is frequent in this environment, the platform coordinates with payers, patients, and referral sources to resolve the gap without requiring staff intervention.
The strongest signal in the commercial story is not the revenue figure but the payment behaviour. A portion of Coral’s customers are paying the full contract value upfront, an unusual dynamic in enterprise software, and a striking one in a sector where vendor evaluation cycles are typically slow and risk-averse.
The explanation is mechanical: when a workflow that previously took hours completes in under five minutes at high accuracy, the return on investment is immediate and visible. Commit now, stop the queue now.
Coral recently shipped AI-powered voice and text workflows that automate follow-ups with payers, patients, and referral sources, replacing calls that previously required a staff member to pick up the phone.
The next phase of product development includes an AI workflow builder that will let providers design and deploy their own administrative processes without involving IT, and a co-pilot layer that surfaces operational intelligence from the data already flowing through the platform: which payers have the highest denial rates and why, where cases are stalling in the authorisation process, which referral sources convert reliably and which do not, and what changes would improve outcomes on insurance claim resubmissions.
Rohil Bagga, investor at Lightspeed, described the company as “delivering real outcomes at scale” in an environment where legacy automation has historically failed.
Ashwin KP, investor at Z47, framed the investment thesis around the specific characteristics of healthcare administration: over a trillion dollars in annual overhead, chronically underserved by technology, and requiring deep vertical expertise to crack.
The Series A funds team growth and product development, with Coral adding engineering talent alongside people who have spent careers inside healthcare operations.
