SiftMed Named “Startup of the Year” by TechNL

Bryant White
Nov 3, 2023

SiftMed, an innovative AI-powered medical investigative technology startup, has been honored with the prestigious "Startup of the Year'' award by TechNL. This recognition comes as a testament to SiftMed's outstanding contributions to the industry and its current trajectory to transform the way medical information is accessed, processed, and utilized.

SiftMed, co-founded by Jeremie Larouche and Holly Hill, has rapidly emerged as a promising disruptor in the medical information space. The company's revolutionary platform securely analyzes medical case files, empowering Independent Medical Experts (IMEs), Legal teams, and Insurance Claim professionals to make data-driven decisions faster to ensure fair outcomes in the bodily injury claims process. 

In February 2023, the startup secured $2.7 Million in seed funding, led by Sandpiper Ventures, to fuel its mission to help find medical facts that change lives. Other key investors in the seed round included Pelorus Venture Capital, a handful of strategic angel investors and industry experts who have enabled to expand its team, enhance its technology infrastructure, and gain customer traction.

Commenting on this recognition, Holly Hill, Co-Founder of SiftMed, stated,  “Fueling growth and creating world-class opportunities for employment in Atlantic Canada has been at the core of our mission at SiftMed. The strength of the startup ecosystem is stronger and more competitive than ever. We are deeply honored to receive the ‘Startup of the Year’ award alongside an incredibly talented group of nominees and visionaries."  

This recognition further validates SiftMed’s vision of becoming the centralized Canadian hub for processing medical data across industries to reduce the time, complexity and stress of the injury claims process. With the support of a dedicated team and partnerships in the industry, they are reshaping a key component of the claims processing landscape to ensure a fair, equitable outcome for insurers and insureds. 

SiftMed has been supported by the Government of Newfoundland and Labrador, through the Department of Industry, Energy, and Technology (IET), the Government of Canada through the Atlantic Canada Opportunities Agency (ACOA), National Research Council (NRC), and the 

Genesis Centre in supporting our efforts over these past three years. This support has been invaluable in their efforts to scale and grow their team.

Rob Hooper, Senior Partner of Grosso Hooper Law, has been a staunch advocate and customer of SiftMed since early 2023.  

Hooper comments, "Having dedicated over 31 years of my career to fighting for the rights of injured individuals, my primary goal has been to secure just and equitable outcomes for them. Integrating SiftMed into our practice has substantially streamlined and enhanced the accuracy of our investigation process, reducing the time required by half. This efficiency allows us to prioritize what truly matters – providing unwavering support to our clients during their most critical time of need."

SiftMed has assembled a top-tier team of experts. Notably, the startup has successfully attracted industry veterans from renowned Atlantic Canadian startups including Celtx and Verafin, who bring invaluable experience to scale the business efficiently. 

About SiftMed

SiftMed is an Artificial Intelligence (AI) processing software that organizes, categorizes, and analyzes medical files. With 1 in 5 medical insurance claims unfairly processed, SiftMed is on a mission to help find facts in medical data that can change lives - the company is currently focused on improving access to critical information that helps legal teams and medical experts to quickly and accurately find key hidden facts in medical data.

By turning medical data into smart documents, SiftMed can review patient files and histories and help its users find the facts that matter with accuracy and speed. By improving accessibility to critical information, SiftMed helps improve patient outcomes and reduce costs driven by time and access complexities.

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Bryant White

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Bryant White