Healthcare professionals are often overwhelmed by administrative tasks, spending more time on paperwork than on patient care. This inefficiency stems from manual workflows and unstructured data, leading to errors and increased costs.
That’s what led Dr. Ahmed Kerwan to found Taxo, a data extraction and reasoning engine for healthcare administration.
“As a practicing physician, I experienced this burden firsthand, sometimes dedicating six to seven hours to paperwork after only three hours of patient care. Motivated to alleviate this issue, I founded Taxo to automate healthcare administration using AI,” Kerwan told VatorNews.
Now the company will be building out its AI thanks to a $5 million seed round of funding announced on Thursday. The round was led by Y Combinator, General Catalyst, and Character, with participation from prominent angels including Kulveer Taggar, founder of Zeus Living, and Yahya Mokhtarzad, founder of Rocket Money.
Taxo addresses the challenges of data extraction in the healthcare space by integrating AI with electronic health records (EHRs) to automate tasks such as prior authorizations, medical coding, and claim submissions.
Under the hood, Taxo doesn’t use a specialized foundation AI model; instead, it uses a model-agnostic approach through a unique “meta-layer” that sits atop a foundation model.
“That means Taxo can incorporate multiple foundation models and isn’t locked into any single AI technology and can adapt for specialized healthcare administration tasks. This also avoids having to train and fine-tune a foundational model, which would be extremely expensive and take a long time to bring to market each time. It would also allow the company to adapt rapidly alongside emerging AI technology,” Kerwan explained.
It’s also fully compliant with HIPAA and SOC2 standards, and every decision it makes is explainable, with direct references to source documents, giving increased transparency to the healthcare organizations that deploy it.
Taxo primarily serves enterprises dealing with messy healthcare data: healthcare providers and payers, including hospitals, physician offices, governments, and insurance companies.
For payers, Taxo automates claim intake, using Apex to automatically extracte and organize claim data. Incomplete or missing information is flagged, which initiates an automated retrieval process to ensure comprehensive submissions. It also assists with eligibility verification, adjudication, and denial management. It also provides aata analytics and reporting by identifying trends and uncovering inefficiencies.
Taxo currently working with dozens of clients, including Mass General Brigham, Stanford Medicine, and Boston Children’s Hospital, and has demonstrated ROI by reducing the time and cost of claims processing by over 90%.
The company will use the new funding to continue to expand its current team of 10 by hiring for key roles, as well as to develop its AI platform.
“Taxo aims to build out its AI meta-layer technology, focusing on hiring AI talent to enhance its capabilities. The goal is to further automate complex administrative tasks, ensuring decisions are not only accurate but also explainable and auditable, thereby building trust with healthcare providers,” said Kerwan.
“The ultimate goal is to alleviate the administrative burden on healthcare professionals, allowing them to focus more on patient care. Success would mean widespread adoption of Taxo’s AI solutions, leading to significant reductions in administrative costs and improved patient outcomes.”
