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More money comes to AI healthcare: Qventus nabs $105M at $400M+ valuation | TechCrunch

Jan 13, 2025 - techcrunch.com
Qventus, a healthcare AI startup, has raised $105 million in a Series D funding round led by KKR, with participation from Bessemer Venture Partners and strategic investors like Northwestern Medicine, HonorHealth, and Allina Health. The funding, comprising $85 million in equity and $20 million in optional debt, will be used to expand Qventus's AI solutions beyond its core in-patient applications. The company, which has grown its customer base four-fold and its core business three-fold since its last valuation of $200 million in 2022, is nearing profitability. CEO Mudit Garg emphasizes that Qventus focuses on alleviating administrative burdens in healthcare rather than being an AI scribe company.

The fundraise highlights the growing investor interest in AI healthcare solutions, with other companies like Cera, Hippocratic, and Innovaccer also securing significant financing recently. Qventus, founded over 12 years ago, initially applied machine learning to improve clinician efficiency and has since expanded into areas like pharmacy operations. The company is now leveraging generative AI to enhance real-time responsiveness and reduce administrative tasks for healthcare professionals. This development aligns with the increasing adoption of technology in healthcare systems to improve efficiency and care delivery.

Key takeaways:

  • Qventus, a healthcare AI startup, raised $105 million in Series D funding to expand its AI solutions beyond in-patient applications.
  • The funding round was led by KKR, with participation from Bessemer Venture Partners and strategic investors like Northwestern Medicine, HonorHealth, and Allina Health.
  • Qventus has grown its customer base four-fold and its core business three-fold since its last valuation in 2022, which was around $200 million.
  • The company focuses on automating administrative tasks in healthcare, differentiating itself from AI scribe companies by addressing significant operational pain points.
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