Ambience Healthcare just closed $70M in Series B funding to cut away at burnout-inducing manual workflows using the latest advances in generative AI.
Ambience’s carving knife isn’t an AI scribe, a coding solution, or a referral tool, but an “AI operating system” that promises to be all those things at once.
That operating system consists of a holistic suite of genAI applications catering to an impressively broad set of use cases. Each app is customized for dozens of specific specialties, care models, and reimbursement frameworks:
- AutoScribe: AI medical scribe that works across all specialties
- AutoRefer: AI referral letter support for both PCPs and specialists
- AutoAVS: After-visit summary tool that generates custom educational content
- AutoCDI: Point-of-care clinical documentation integrity assistant that analyzes notes and EHR context to ensure ICD-10 codes, CPT codes, and documentation are aligned
Ambience has kept tight-lipped about both its customer count and LLM provider, but we do know that it as:
- $100M in total funding since launching in 2020
- Marquee customers like UCSF, Memorial Hermann, and John Muir Health
- Investments from Silicon Valley heavyweights like Kleiner Perkins, a16z, and OpenAI (probably a decent hint toward the unrevealed LLM partner)
The newly-raised capital will accelerate Ambience’s product roadmap and allow it to build dedicated support teams for its health system partners.
- The first product up on that roadmap is AutoPrep, an intelligent pre-charting solution that equips clinicians with suggestions for the visit agenda and potential conditions to screen for.
Ambience’s operating system strategy not only gives it a huge total addressable market, but also positions it apart from well-established competition like Nuance and Augmedix, as well as a hungry pack of genAI up-and-comers such as Nabla and Abridge.
- A continuously learning OS with “a single shared brain” sounds like a versatile way to break down silos, but the flip side of that coin is that providers looking for an answer to a specific problem might be tempted to go with a more specialized solution.
The Takeaway
Driving adoption of any software is hard. Crafting a beautiful user experience is hard. Tailoring a continuously learning AI operating system to every medical specialty sounds extremely hard. At the end of the day, Ambience’s approach is about as ambitious as it gets, but it carries massive advantages if it can execute.
