In a notable advancement for integrating artificial intelligence in healthcare, Ambience Healthcare has announced a significant $70 million Series B funding round.
The investment, co-led by OpenAI’s Startup Fund and Kleiner Perkins, with participation from Andreessen Horowitz and Optum Ventures, highlights the growing confidence in AI’s potential to transform healthcare operations and patient care.
Ambience Healthcare, headquartered in San Francisco and founded in 2020 by Mike Ng and Nikhil Buduma, is at the forefront of developing AI solutions to enhance the efficiency of healthcare providers.
The company’s flagship product, AutoScribe, is an AI-driven medical scribe that automatically generates detailed medical notes across various clinical specialties, seamlessly integrating with leading Electronic Medical Records (EMRs) systems such as Epic, Cerner, and Athenahealth.
This Series B funding elevates Ambience Healthcare’s total capital raised to $100 million, underscoring the tech community’s strong belief in the company’s mission to streamline healthcare administration and enhance patient care through AI.
Long before this announcement hit the internet, there was widespread anticipation globally for AI’s entry into the healthcare sector. The majority harbored optimism regarding AI’s potential to revolutionize healthcare.
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While the company has opted not to disclose its current valuation, PitchBook provided a glimpse into its financial standing with an estimated post-money valuation of $126 million following its Series A round in 2022.
This latest funding round underscores Ambience Healthcare’s commitment to expanding its suite of AI tools, which also includes AutoCDI for clinical documentation improvement, AutoRefer for streamlining referrals, AutoAVS for generating after-visit summaries, and the upcoming AutoPrep, designed to provide clinicians with predictive insights for patient visits.
Ambience Healthcare’s technology is already in use at several prestigious healthcare organizations, demonstrating its ability to reduce the time clinicians spend on documentation, improve coding accuracy, and enhance the overall quality of patient care.