Tricog raises $10.5 mn in Series B funding

Source : IANS
Author : IANS
Last Updated: Wed, Mar 4th, 2020, 13:19:28hrs
Tricog raises $10.5 mn in Series B funding

Bengaluru: Bengaluru-headquartered healthcare analytics firm Tricog on Tuesday said it raised $10.5 million (approximately Rs 76.8 crore) in a Series B funding round from Japanese investors The University of Tokyo Edge Capital, Aflac Ventures and Dream Incubator, alongside US-based impact investor TeamFund.

Existing investors Inventus Capital and Blume Ventures also participated in this round, Tricog said.

The investment comes two years after Tricog's Series A funding round, bringing the company's total funding to $17.5 million. Since the previous round, Tricog has grown its presence in over 12 countries in South-East Asia and Africa.

Tricog said its Artificial Intelligence-powered platform has been used by over three million patients globally for wellness, screening and diagnosis of acute as well as chronic heart diseases.

Founded in 2015 by Charit Bhograj, Zainul Charbiwala, Udayan Dasgupta and Abhinav Gujjar, Tricog provides virtual cardiology services to remote clinics, powered by AI and medical experts.

Tricog said its Insta ECG platform has been deployed in over 2,500 cathlabs, hospitals, clinics and diagnostic centres to help diagnose and manage patients with critical cardiac diseases including heart attacks.

The platform has been deployed across both government and private health care networks and has demonstrated a significant reduction in mortality and morbidity.

"We have witnessed phenomenal growth from our initial investments, both in terms of footprints in new geographies as well as revenue growth," said Bhograj.

"Through this round of investment, we reinforce our commitment to strengthen our AI-powered platform for faster diagnosis, expand our product line and establish strong presence in Africa and Asia including India, China and Japan," Bhograj said.

Tricog recently launched the InstaEcho platform for remote echocardiography with a focus on using AI to enable point of care cardiac ultrasound for the diagnosis of heart failure, valvular heart disease and screening for congenital heart disease.