The Spark That Started It All
In 2012 Mike Ng suffered a back injury that was misdiagnosed. This wrenching personal experience revealed to him just how opaque and burdensome the US medical system could be: doctors bogged in paperwork, inefficient clinical workflows, and administrative friction.
Meanwhile, Nikil Buduma had been observing healthcare struggles from a different angle. Having immigrated as a child and faced family health challenges, he understood deeply how hard it is to navigate care systems. At MIT, he immersed himself in AI research, earning recognition for his early work in deep learning.
At MIT, their paths crossed. Their discussion— about healthcare inefficiencies, AI capabilities, and the future of clinical workflows became the seed of a shared vision. They asked: What if doctors could focus on patients, not paperworks? That question evolved into Ambience Healthcare, founded in 2020 to build AI copilots that work invisibly in clinical workflows.
From Concept to Founders
Ng and Buduma were not starting from scratch—they each brought essential experience and revealed complementary strengths.
- Mike’s encounter with the broken system gave him empathy, domain insight, and urgency. He saw that so much of a clinician’s time was swallowed by documentation, billing, coding, and navigating electronic health records (EHRs).
- Nikhil’s technical grounding and prior exposure to AI gave the duo the ability to imagine how next-generation models could actually influence healthcare operations. He had already written a well-known textbook on deep learning.
Before Ambience, they co-founded Remedy Health, which exposed them to the challenges of working with clinicians, compliance, and deploying AI in health settings. They learned that building a “bright idea” was not enough — it must integrate with hospital infrastructure, regulation, and daily workflows.
Consequently, in 2020, they officially established Ambience, with a mission to integrate AI at the core of clinical systems to enable clinicians to have less administrative burden and more time for care.
Building Tools That Clinicians Can Trust
The founders knew that for Ambience to succeed, the AI couldn’t be a bolt-on afterthought. It had to be workflow-native, clinically aware, and audit-ready.
Ambient Scribing & Pre-Charting
Ambience introduced an ambient scribe: the AI listens in real time during patient visits, captures key utterances, and drafts clinical notes. All of this happens while the doctor focuses on dialogue—not typing.
Before visits, Ambience’s pre-charting module synthesizes historical patient data, lab results, and past notes into a compact summary so the clinician walks in prepared.
Coding-Aware Documentation & CDI
Notably, Ambience’s AI doesn’t merely transcribe—it is coding-aware. That means the system understands ICD-10, CPT, compliance rules, and ensures the generated draft supports valid billing. The AI continuously learns the coding rules (which change yearly) across specialties.
In October 2025, Ambience became the first ambient AI platform to launch inpatient Clinical Documentation Integrity (CDI) at the point of care, built using OpenAI models. This tool helps hospitalists document precise diagnoses, complications, and coding details in real time.
Patient-Facing Summaries & Chart Chat
Ambience also launched features that extend beyond clinician aid. Their system can generate after-visit summaries in multiple languages, helping patients and families understand care plans.
In 2025, they rolled out Chart Chat, a conversational AI copilot embedded in Epic EHR that allows clinicians to ask questions about a patient’s history or treatment and receive real-time answers. This union of patient data + medical knowledge helps clinicians navigate complexity faster.
The Early Validation & Momentum
Ambience didn’t rely on promises—they tested in real systems early.
- They deployed across 40 U.S. health systems covering 100+ specialties, including outpatient, inpatient, emergency, and subspecialties.
- Internal benchmark studies showed Ambience’s AI outperformed board-certified physicians by ~27% in medical coding accuracy.
- In KLAS research, Ambience earned a 97.7% Spotlight Report score, among the highest in the ambient AI category, across metrics such as product quality, implementation, and customer satisfaction.
These validations gave credibility in a cautious industry and opened doors with large hospital systems.
Scaling, Leadership Shifts & Big Rounds
Growing from prototypes to a platform required capital and leadership transitions.
- In February 2024, Ambience raised a $70M Series B, co-led by Kleiner Perkins and the OpenAI Startup Fund. The funds fueled the expansion of engineering, compliance, and integrations.
- In July 2025, they closed a $343M Series C, co-led by Oak HC/FT and a16z, with participation from OpenAI Fund, Kleiner Perkins, Optum Ventures, and others. This round enabled aggressive scaling across health systems.
- Also in September 2025, Ambience announced a leadership change: Nikhil Buduma became CEO, and Mike Ng transitioned to President & Chairman. The move was positioned to let Buduma lead daily operations while Mike focuses on strategy and vision.
The founders have steered the company from its origin through phases of product-market fit, system validation, and now large-scale deployment.
Read Also: Web AI: Three Founders on a Mission to Teach the Internet to Think
Integrations & Partnerships: Embedding in Health Systems
Ambience’s growth depends on deep technical partnerships and embedded deployment.
- They joined Epic’s Toolbox program, unlocking deeper integration within Epic’s Ambient Module and Haiku (its mobile interface). This ensures Ambience’s capabilities are available in more clinical settings.
- Through this integration, clinicians in ambulatory, inpatient, and emergency settings can use Ambience’s AI functions directly from Epic workflows—reducing friction and adaptation barriers.
- Hospitals like Cleveland Clinic, UCSF Health, Memorial Hermann, John Muir Health, and Houston Methodist are among their high-profile customers.
Ambience’s ability to operate across specialties and interface with major EHR systems is a key driver of adoption.
Founders’ Philosophy & Vision
Ng and Buduma lead with a guiding principle: free clinicians from administrative burden so they can care for patients.
They see Ambience not as a tool, but as a “copilot”—a quiet helper embedded in the background, surfacing valuable insights when needed.
From the start, the founders prioritized auditability, compliance, and clinical nuance. They understood that in healthcare, mistakes have high stakes; AI must be transparent, correctable, and context-aware.
They’ve said they are 10% into their roadmap—AI for care coordination, prior authorization, utilization management, and deeper specialty reasoning are on the horizon.
Challenges & Lessons Learned
The journey hasn’t been smooth; being a founder in healthcare AI demands resilience.
- Scaling across diverse specialties means models must be finely tuned to each domain—oncology, cardiology, emergency—each with different documentation norms and clinical complexity.
- Regulatory, compliance, and audit risk loom large; the founders must always anticipate shifting coding rules, payer policies, and documentation standards.
- Integration with EHRs is notoriously difficult: for Ambience to succeed, their AI must “play nicely” with existing systems without disrupting clinicians’ workflows.
- Culture and trust matter: the company must win clinicians’ confidence, not only with performance metrics but with reliability, correctness, and ease of use.
Through these challenges, Ng and Buduma have emphasized listening to users, iterating fast, and grounding every feature in real clinical pain.
The Road Ahead: What’s Next
Ambience’s ambitions are bold but focused.
- Expand deeper into inpatient and high-acuity specialties, leveraging their CDI (Clinical Documentation Integrity) modules and reasoning models.
- Enhance AI modules for prior authorization, utilization management, referrals, and clinical decision support, turning Ambience into a full-stack clinical operations platform.
- Extend adoption into smaller and regional health systems, democratizing ambient AI beyond elite academic centers.
- Maintain compliance and safety by investing heavily in audit trails, guardrails, and explainability.
- Continue product enhancements like Chart Chat, which lets clinicians ask natural-language questions during patient care and get precise, context-aware responses.
