New York-based healthcare automation startup Coral has closed a $12.5 million Series A funding round led by Lightspeed and Z47, signaling continued investor confidence in AI-driven workflow automation for regulated health environments. The round will fund engineering expansion and product development as Coral targets the estimated $450 billion that U.S. healthcare providers spend annually on manual administrative work, according to the company.
Background
Healthcare administration remains one of the most fragmented and compliance-sensitive operational domains in any industry. Providers across specialty care-including durable medical equipment (DME) suppliers, infusion centers, and radiology practices-continue to rely on fax-based intake processes, manual prior authorization workflows, and disconnected payer portals that resist conventional automation. Generic robotic process automation (RPA) tools have historically struggled in this environment, where document formats are inconsistent and errors carry clinical and financial consequences.
Coral's approach focuses on integrating with existing electronic health record (EHR) systems, fax infrastructure, and payer portals rather than replacing them. 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. This publication has previously examined how governance frameworks using HL7 FHIR APIs and HIPAA-aligned audit controls are shaping AI deployment in healthcare financial workflows; Coral's Series A extends that narrative into clinical back-office operations.
Details
Coral's platform automates prior authorizations, patient intake, and fax processing, connecting to existing EHR systems and payer portals without requiring providers to rebuild their infrastructure, according to the company. The platform has reached a document accuracy rate of 99.7% across handwritten fax forms, scanned insurance cards, prior authorization templates, and payer portal screens. The company states that complete patient intakes, including complex cases, now run in under five minutes, and when data is missing, the system coordinates with payers, patients, and referral sources autonomously.
Coral has also shipped AI-powered voice and text workflows that automate follow-up communications with payers and referral sources-functions that previously required direct staff intervention. The company is developing a no-code AI workflow builder that will allow providers to configure and deploy administrative workflows without IT involvement.
On traction, Coral's revenue grew more than eightfold over a seven-month period and the platform now processes over 500,000 patient workflows per month, according to a prior company announcement. Organizations using Coral reported an 81% reduction in intake time, from 21 minutes to approximately 4 minutes per patient.
Rohil Bagga, an investor at Lightspeed, noted that "healthcare is one of the hardest environments to automate, given legacy systems and fragmented workflows," adding that Coral's product is already deployed by some of the largest U.S. providers to reduce patient intake times and first-pass insurance denials. Ashwin KP of Z47 stated that "US healthcare admin carries over a trillion dollars in overhead each year, yet the back-office teams doing this work have been chronically underserved by technology."
Co-founder Ajay Shrihari said the company's differentiation lies in its willingness to operate within existing complexity: "We accept the complexity of healthcare as it exists today and automate within current processes, delivering value on day one without our customers having to upend their entire infrastructure."
Outlook
Coral is targeting 4x revenue growth by the end of 2026, with Series A proceeds directed toward engineering hires and product expansion into additional specialty verticals. The company is also building an intelligence layer designed to surface operational insights from the administrative data it already processes-a capability with potential relevance for compliance and governance reporting in regulated environments. As AI governance requirements in healthcare tighten under frameworks such as HIPAA and emerging state-level AI rules, vendors that demonstrate high-accuracy, auditable automation within existing infrastructure are likely to face heightened procurement scrutiny and demand in equal measure.
