Suki, an ambient AI health care company, is taking another big step forward. The company is expanding its assisted revenue cycle automation to include more precise coding. This update now enables automatic generation of CPT and E/M codes, boosting efficiency in medical billing and documentation.
More innovative Tools for Healthcare Providers
Recently, Suki refreshed its brand to highlight its wide range of offerings. Its AI-enabled ambient clinical intelligence tool helps clinicians with daily documentation tasks. The tool can generate clinical notes, support dictation, and recommend ICD-10 and HCC codes.
Even better—it can seamlessly integrate with electronic medical records (EMRs), allowing smooth EHR integration by copying clinical notes directly into the system. This simplifies workflows and saves physicians valuable time.
Building on Advanced Coding Capabilities
Suki’s platform already had strong automation features. It could detect ICD-10 and HCC codes using ambient listening technology. Now, it’s going further—automating CPT and E/M code detection with even higher accuracy.
According to Dr Kevin Wang, chief medical officer at Suki, the company’s primary focus is on clinical accuracy rather than just coding precision. Speaking to MobiHealthNews, he explained, “Our primary goal isn’t just to make risk adjustment models accurate. It’s to perfect the note itself—the words, the ontology, and the diction.”
The Focus: High-Quality Clinical Notes
Dr Wang emphasises that accurate clinical documentation is the foundation for better coding. Suki’s platform aims to make every clinical note so clear and contextually correct that it naturally improves the revenue cycle management process.
The system uses advanced speech recognition to pick up on accents, tone, and nuances. It can even detect who is speaking during a conversation. This helps produce notes that reflect true clinical intent.
Intent Extraction: Understanding Context and Meaning
One of Suki’s standout features is its intent extractor. By combining speech data with a powerful language model, Suki identifies the meaning behind a clinician’s words.
Dr Wang shared that the platform is fine-tuned through scoring. “We don’t just transcribe,” he said. “We determine the intent behind each phrase and enhance the note quality accordingly.”
This intelligent AI health care automation ensures that the notes are more than text—they reflect accurate clinical understanding.
Scoring Notes at a Deeper Level
Initially, Suki scored notes based on broad clinical domains. But the team soon realised it wasn’t the entire note that needed assessment—it was the specific sections.
Now, Suki analyses segments like the history of present illness, physical exam, and treatment plan. Going even deeper, it can score at the sentence level. This sentence-level scoring makes it possible to fine-tune every part of a medical note for maximum clarity and coding accuracy.
Accuracy That Surpasses Humans
Suki’s AI can match an ICD code to a word with over 90% accuracy in some cases. However, E/M coding variability brings new challenges. According to Dr Wang, the medical decision-making process affects E/M code accuracy since visit severity and duration can differ.
Still, Suki’s results are impressive. “Our accuracy is already higher than that of a human coder,” Dr Wang said. The system also earns high approval from providers who review and verify the codes.
Reducing Errors and Audits
Another significant benefit is audit reduction. Many medical coders face issues where submitted codes are denied or queried during audits, like RADV audits.
Dr Wang explained that Suki’s ultimate goal is to minimise these errors. “We believe our notes will be so accurate that they’ll reduce the need for scrubbing and post-review,” he said.
A Step Toward the Future of AI Health Care
With strong internal testing results, Suki’s latest update is paving the way for more intelligent AI in healthcare. The company is proving that AI-enabled ambient clinical intelligence can deliver both coding efficiency and clinical precision.
By combining automation, medical transcription, and digital health innovation, Suki is reshaping how healthcare professionals manage documentation. As the technology continues to evolve, it’s setting a new standard for EHR integration, coding efficiency, and clinical accuracy—all while saving doctors time and reducing administrative burden.
Punit Soni, the CEO and co-founder of Suki, is on a mission to transform AI health care. His company, based in San Francisco, builds an AI assistant that listens, understands, and helps doctors in real time.
Unlike traditional scribes that only write notes, Suki works like a real assistant—helping doctors prepare for visits, take notes, code diagnoses, and manage records. The result? Less screen time and more patient focus.
In an interview with Healthcare IT News, Soni shared how ambient AI is changing digital health, the challenges of building reliable systems, and what the future of healthcare technology looks like.
How Suki’s AI Assistant Works
First, let’s understand how these systems work. Many companies claim to have AI in healthcare, but few create real value from start to finish.
Suki’s AI health care assistant is more than a note-taker. It acts like a personal helper standing beside the doctor.
Imagine a doctor saying:
- “Suki, show me my schedule.”
- “What things should I be aware of about Bill before meeting him?”
Suki instantly summarises Bill’s medical history, last visits, and care gaps. During the consultation, the doctor says, “Suki, pay attention.” The assistant then listens carefully, captures the conversation, and creates clinically accurate notes using problem-based charting.
Suppose Bill has three issues, and Suki lists and codes each one. It adds ICD-10 and CPT codes to ensure correct billing. If the doctor prescribes something, Suki adds it directly to the electronic health record (EHR).
Everything appears in the EHR as if the doctor entered it manually. But it’s faster, cleaner, and more accurate. That’s what AI health care should look like—technology that saves time and keeps doctors focused on patients.
Where It’s Used and Why It Works
Suki is used across hospital systems, clinics, and group practices. To measure its impact, Suki ran the Phyx Primary Care Study with 115 physicians in 37 clinics. The results were impressive:
- 41% less time spent per clinical note.
- 27% drop in documentation burden.
- 32% fewer rushed patient visits.
- 46% more notes completed before the next patient.
- 33% more notes were finished the same day.
These numbers prove one thing: when doctors truly adopt AI assistants, productivity improves fast.
Suki’s success lies in its deep EHR integration, especially with Epic EHR. It’s not just an app that pastes notes—it fully connects with clinical workflows.
Real EHR integration means:
- Pulling live patient data.
- Understanding patient context.
- Writing updates directly into the right EHR sections.
This makes AI in healthcare smoother, faster, and more efficient.
The Challenges of Generative AI in Health Care
Even the best AI health care tools face challenges. Punit Soni highlights three main areas where caution is needed.
1. Focus on Quality
Quality is key. Hospitals should always ask:
- How accurate is the AI output?
- What quality metrics are used?
- Is the system enterprise-grade AI or just a basic language model?
High-quality, clinically accurate documentation is vital. A small coding or note error can affect treatment or billing.
2. Scale and Security
A reliable AI health care platform must handle thousands of doctors at once. It should ensure privacy, data security, and full healthcare compliance. Without this strong foundation, AI can create risks instead of reducing them.
3. Real Integration with EHR
Many companies say they’re integrated—but they’re not. Proper integration means pulling live data, understanding the clinical context, and updating the EHR automatically.
Before choosing a system, hospitals should ask:
- “Is your EHR partner a real collaborator?”
- “Can your assistant both read and write data live?”
The answers will show if the ambient service is ready for real-world healthcare use.
What Makes Suki Stand Out
Soni says Suki’s success comes from three main principles.
1. A Mission Beyond Business
Suki isn’t just about profits. The team’s mission is to make clinicians’ lives easier. Passion for that mission keeps them going through tough times.
2. Putting Clinicians First
Every feature is built around the needs of doctors. When the tool helps doctors, everything else—results, revenue, and adoption—follows naturally.
3. Building with Humility
Real numbers always back Suki’s claims. When they talk about ROI or productivity gains, those results come from data verified with healthcare partners.
This mix of vision, purpose, and humility has made Suki one of the most trusted names in AI health care.
The Future of AI Health Care and Ambient Intelligence
According to Soni, the next decade will redefine how we experience AI in healthcare. He calls it the next epoch—as revolutionary as the printing press or the internet.
In this new age:
- AI becomes the new user interface (UI) for all interactions.
- Tasks like medical coding, revenue cycle management, and clinical documentation will be fully automated.
- Technology will fade into the background, letting clinicians focus on people, not screens.
Within five years, Soni predicts that hospitals and clinics will have invisible assistive AI systems running behind the scenes. These systems will quietly handle documentation, coding, and workflow automation, while doctors focus only on care.
This shift will:
- Lower healthcare infrastructure costs.
- Expand healthcare accessibility to more people.
- Accelerate digital transformation in healthcare globally.
Conclusion
Suki, led by Punit Soni, is changing how the world sees AI health care. It’s not just about automation—it’s about giving doctors their time and focus back.
By combining ambient clinical intelligence, EHR integration, and a clinician-first approach, Suki shows what AI in healthcare can truly achieve.
The goal is simple but powerful: make healthcare more human again. With AI-powered tools like Suki, the future of digital health looks brighter, smarter, and more connected than ever before.