How to Develop an AI Scribe App like Suki Assistant

The documentation burden in healthcare has grown significantly, often consuming a large portion of a clinician’s time. Traditional note-taking during or after patient visits can lead to burnout, workflow inefficiencies, and even missed details in medical records. This is where AI scribe apps are transforming clinical environments by offering real-time support in capturing, organizing, and summarizing patient interactions. Solutions like Suki Assistant are leading the way with voice-enabled automation that works silently in the background, allowing physicians to focus on what matters most: patient care.

In this blog, we will talk about how an AI scribe app like Suki Assistant works, the features that make it effective, the step-by-step development process, and the key technologies involved in building a high-performance clinical documentation tool. As we have developed multiple healthcare products for numerous enterprises, IdeaUsher brings hands-on experience in creating AI-driven solutions tailored for clinical environments. From understanding voice workflows to ensuring EHR compatibility

What is an AI Scribe App: Suki Assistant?

Suki is an AI-powered medical scribe that captures doctor-patient conversations in real time and automatically generates clinical notes. Unlike generic dictation tools, Suki uses ambient voice technology to understand context, apply medical logic, and create SOAP-style notes that can be directly integrated into EHR systems. It supports voice commands, note customization, and smart ICD-10 coding suggestions. Suki is designed to reduce the documentation burden on clinicians, saving them hours weekly while improving the accuracy and efficiency of medical recordkeeping.

Business Model

Suki operates primarily as a B2B SaaS provider, offering its AI voice-powered assistant to healthcare organizations, including clinics, medical groups, and large health systems. Its flagship product, Suki Assistant, listens to patient–clinician conversations and automatically generates structured clinical notes, streamlining documentation workflows. In parallel, Suki Platform enables other healthcare IT vendors to embed Suki’s voice AI via APIs, creating a B2B2B ecosystem beyond direct physician adoption.

Revenue Model

• Subscription Licensing: Paid per-user per month typically between $299 and $399 depending on EHR integration. Enterprise volume discounts and custom pricing are common for large systems.
• Platform Licensing: Suki Platform drives B2B2B revenue as partners license its voice AI engine to embed into their own products.
• Value-Based ROI Argument: Suki claims 72% faster note completion, a 5–29% increase in patient encounters, and up to 9× ROI in the first year, metrics used to justify subscriptions to clients.

How the AI Scribe App Suki Assistant Works?

Before replicating or building an AI scribe app, it’s crucial to understand how leading solutions like Suki Assistant function under the hood. Its strength lies in combining real-time voice tech, clinical reasoning, and EHR interoperability in one seamless workflow.

1. Ambient Voice Capture & Dual ASR Processing

Suki continuously listens during patient interactions using dual ASR pipelines one trained for clinical dictation and another for voice commands. This allows seamless transitions between note-taking and action-based prompts without disrupting the conversation or requiring a pause.

2. Context‑Aware Clinical Conversation Processing

The app processes audio using real-time natural language understanding that interprets clinical terminology, retrieves patient history, and formats content into structured SOAP notes. It adapts to each physician’s speech pattern, enhancing both accuracy and documentation efficiency.

3. Deep Bidirectional EHR Sync

Suki integrates with major EHRs like Epic, Cerner, and Athenahealth, automatically pulling in data such as vitals and medication history. Once notes are finalized, they are pushed back to the EHR without requiring manual copy-paste, ensuring speed and consistency.

4. Voice‑Driven Commands & Ambient Order Staging

Doctors can issue direct voice instructions such as “Suki, prescribe doxycycline 10 mg once daily,” and the assistant will stage the order instantly. All notes and prescriptions are created hands-free but are still clinician-reviewed before being saved.

5. Real-Time Draft Review

After generating a draft, Suki allows clinicians to make live edits. The platform learns from corrections, storing preferences to personalize future notes. This continuous learning loop boosts long-term accuracy and reduces time spent on edits.

6. Secure, Compliant Architecture

Suki ensures HIPAA and SOC 2 Type 2 compliance, encrypting all data and deleting patient audio or transcripts within seven days. This privacy-first approach helps maintain clinical trust and data governance in regulated environments.

Why You Should Invest in Launching the AI Scribe App?

According to Market.us, the market size of medical transcription software is projected to reach USD 190.2 billion by 2032, up from USD 77.8 billion in 2022, growing at a CAGR of 9.60% from 2023 to 2032. This growth is driven by the increasing adoption of AI in healthcare documentation, aiming to reduce physician burnout and streamline clinical workflows.

Suki Assistant, a pioneer in AI scribe solutions, has raised $165 million to date. This includes a $55 million Series C round in December 2021 and a $70 million Series D round in October 2024, led by Hedosophia and backed by Venrock, March Capital, and other investors. These investments underline investor confidence in the AI scribe ecosystem and its long-term value.

Ambience Healthcare, another major player, secured $70 million in Series B funding in 2024, bringing its total to over $100 million. The company’s AutoScribe platform has gained significant traction, with its ARR reportedly reaching $30 million, indicating strong market demand.

The AI scribe market is rapidly becoming vital in digital healthcare. It reduces documentation time, improves EHR accuracy, and boosts clinical productivity, making AI scribe apps essential in healthcare. Investing in this field offers access to a high-growth market with proven ROI, growing enterprise use, and real clinical benefits.

Why Healthcare Needs AI Scribe Apps?

As administrative demands rise, many physicians spend more time typing than treating patients. An AI scribe app reduces manual documentation, improves workflow, and lets clinicians focus on quality care.

1. Combat Physician Burnout

Excessive documentation contributes directly to physician fatigue and burnout. An AI scribe app alleviates this by automating note creation, reducing after-hours charting, and improving work-life balance while maintaining clinical accuracy and supporting compliance with institutional documentation standards.

2. Reduce Documentation Time

Creating SOAP notes manually consumes approximately 15 minutes of valuable clinical time. With an AI scribe app, doctors can dictate and generate structured notes in approximately 4 minutes in real-time, reducing administrative workload and freeing up hours for patient engagement and informed decision-making.

3. Improve Note Accuracy and Consistency

Manual notes often contain inconsistencies or missing details due to time pressure. An AI scribe app ensures structured, complete, and medically accurate documentation, reducing the risk of errors and enhancing the quality of the clinical record.

4. Support Value-Based Care Models

Value-based care relies on detailed, outcome-focused documentation. AI scribe systems help physicians capture standardized information essential for quality reporting, patient monitoring, and reimbursement alignment with evolving healthcare delivery models focused on efficiency and outcomes.

5. Make EHRs Less Distracting

Navigating complex EHR systems disrupts patient communication and adds to cognitive load. An AI scribe app minimizes this distraction by automatically populating notes and orders into the EHR, allowing doctors to stay present during consultations.

6. Enable Better Clinical Decision-Making

By organizing patient interactions into clear, structured notes, an AI scribe app provides a more reliable clinical reference. This improves diagnostic confidence, supports continuity of care, and reduces the likelihood of missing critical medical context.

Key Features to Include in Your AI Scribe App like Suki Assistant

Before diving into the development process, it’s important to understand the essential capabilities that make an AI scribe app like Suki Assistant effective. These features not only reduce administrative burden but also enhance clinical accuracy, productivity, and compliance in real-world healthcare environments.

1. Voice‑Enabled Ambient Dictation with Specialty Adaptation

A core feature of any AI scribe app is real-time, ambient dictation that captures conversations without manual input. It must recognize and separate voices, ignore irrelevant dialogue, and support medical vocabularies unique to each specialty such as cardiology or dermatology ensuring accurate and context-aware transcription during every patient encounter.

2. Real-Time Note Generation with Instant EHR Sync

An AI scribe app must auto-generate clinical notes such as SOAP or H&P formats during the conversation itself. It should instantly push this data into the EHR with correct headers, ICD-10 codes, medication updates, and assessments, significantly cutting documentation delays and post-visit editing by clinicians.

3. Adaptive NLP Learning and Personalization

The app should evolve with each user. Over time, an AI scribe app needs to learn clinicians’ voice styles, templates, and phrasing preferences. It should intelligently adjust macros, snippets, and workflows, improving accuracy and speed while adapting to personal documentation habits and preferences in daily clinical routines.

4. Specialty‑Focused Templates and Snippets

Different specialties require different documentation standards. A well-built AI scribe app should offer tailored templates and dynamic snippets that allow clinicians to auto-insert structured data such as review of systems or counseling details with voice commands or shortcuts, ensuring consistency in high-volume or subspecialty practices.

5. Multilingual and Accent-Aware Recognition

Given the diversity in healthcare settings, your app must support multilingual communication and recognize a wide range of accents. An AI scribe app should allow doctors to converse in local languages while transcribing accurate English notes in real time, improving inclusivity without compromising clarity or quality.

6. Security, Compliance & Auditability

Since the app handles sensitive patient data, end-to-end HIPAA-compliant security protocols are critical. An AI scribe app must use encryption, access logs, audit trails, and conform to SOC 2 Type II or ISO 27001 standards to ensure traceability and regulatory compliance in every use case.

7. Multimodal Context Integration and Document Upload Support

Allowing clinicians to upload and attach documents like labs, referrals, or PDFs is essential. An AI scribe app should intelligently extract relevant data from these files and merge it into structured notes, giving providers a complete view of the patient’s condition without toggling across systems.

8. Embedded AI Chat Assistant and Clinical Decision Alerts

To enhance usability, the AI scribe app should include a built-in assistant for editing and note improvement. It should assist with refining summaries, filling gaps, and even providing real-time clinical suggestions such as potential diagnoses, missed history elements, or drug alerts during the note-taking process.

9. Billing Automation and Coding Suggestions

The app should go beyond transcription and support revenue cycle management. A robust AI scribe app must auto-suggest CPT/ICD-10 codes, flag ambiguous entries, and prepare billing summaries to reduce claim denials and speed up reimbursement, all while maintaining documentation standards.

10. Scalability and Cross‑Platform Availability

Healthcare providers work across devices and settings. An AI scribe app should be built for iOS, Android, web, desktop, and even wearables, with scalable backend architecture that supports both solo practitioners and large healthcare networks without sacrificing performance or stability.

11. Real-Time Analytics and Insight Feedback

Built-in analytics can make every visit a learning opportunity. The AI scribe app should analyze notes to flag missing data, suggest documentation best practices, and offer improvement prompts that not only enhance quality but also drive compliance, clinical education, and better patient outcomes over time.

12. Wearables and Remote Patient Monitoring Integration

The rise of RPM and wearable devices makes real-time vitals tracking essential. An AI scribe app should pull in data like blood pressure or glucose levels, interpret trends, and incorporate them directly into visit summaries, especially for patients in chronic care programs or virtual consultations.

Step‑by‑Step Process to Develop an AI Scribe App like Suki Assistant

To create a reliable AI scribe app, development must go beyond transcription accuracy. It requires clinical context, secure data handling, and adaptability across specialties. Our AI and healthcare product teams follow a layered development process that ensures the app is accurate, secure, and seamlessly fits into real-world clinical workflows.

1. Consultation

We begin with a detailed consultation phase where our team works closely with you to understand your product vision. We discuss your goals, target users, clinical focus, desired features, and expected outcomes from the AI scribe app. This helps us shape a development plan that aligns with your priorities while ensuring the final product meets real clinical demands and regulatory obligations.

2. Design the Core App Architecture

Our developers design a modular architecture that includes layers for speech input, summarization, template generation, EHR integration, and secure compliance. We use cloud infrastructure that adheres to SOC 2 and HIPAA standards. For transcription, we integrate domain-specific LLMs to convert spoken content into structured notes that align with SOAP and H&P documentation templates.

3. Integrate Voice Recognition & NLP

We implement ambient voice capture technology that isolates clinician and patient speech in real time. To reduce ASR errors, we train the voice model on specialty-specific medical speech datasets. Our NLP pipelines extract structured clinical data and tag it with coding ontologies like ICD-10 and SNOMED for consistent downstream use across clinical and billing workflows.

4. Build Contextual Note Summarization and Formatting

Our AI developers create summarization pipelines that convert transcribed dialogue into SOAP-style notes, medication details, billing codes, and assessments. The interface supports macros, customizable templates, and live edit capabilities. We also add an adaptive learning loop where clinician corrections feed back into the model to refine the app’s note accuracy over time and reduce hallucination risks.

5. EHR/EMR System Integration

We build FHIR and HL7 integrations with major EHRs like Epic, Athena, and Cerner to enable write-back of final notes, orders, and referrals. For unsupported systems, we offer clipboard-based fallback options. We design workflows where physician edits inside the EHR automatically trigger AI updates, and audit logs are maintained for every version to ensure traceability and compliance.

6. Conduct Testing and HIPAA Compliance Review

Our QA team conducts transcription accuracy checks against gold-standard notes and performs penetration testing for security. We complete a HIPAA risk analysis, BAA verifications, and implement patient consent protocols. The app is deployed in a pilot clinic, iterated based on real usage, and gradually scaled. Throughout, we track documentation time, burnout metrics, and billing precision for improvements.

Cost to Develop an AI Scribe App like Suki Assistant

Total Estimated Cost: $65,000 – $140,000

Note: The above estimates show average industry costs to build a HIPAA-compliant AI scribe app in 2025. Actual prices vary based on your app’s complexity, specialties, EHR integration, and customization. We recommend a consultation for a tailored quote based on your goals and clinical workflow.

How To Mitigate Challenges in Building an AI Scribe App?

AI scribe apps must operate in real-time, handle complex medical language, and fit into existing clinical systems. These demands introduce several challenges during development that require thoughtful, technically sound solutions to ensure reliability and adoption.

1. Handling Multiple Voices 

Challenge: In real clinical settings, background chatter, machine noises, and overlapping speech between doctors and patients can seriously impact transcription accuracy. This can confuse the AI scribe app, resulting in missing or misattributed details, especially during fast-paced consultations or emergencies.

Solution: To solve this, we use advanced noise-canceling voice APIs like Deepgram, train models with diverse multi-speaker clinical datasets, and apply real-time speaker diarization to differentiate speakers. These tools help the AI scribe isolate relevant voices even in complex environments.

2. Maintaining Clinical Accuracy in Transcription

Challenge: Clinical conversations are dense with jargon, acronyms, and contextual nuances. If the AI misinterprets these, it could lead to incorrect diagnoses or medical orders, making trust and reliability a major concern during adoption.

Solution: We address this by fine-tuning NLP models on real-world medical transcripts, continuously validating with domain-specific datasets, and applying clinical rule engines that flag inconsistencies. This ensures the AI scribe app generates notes that meet both clinical and legal standards.

3. Integrating with Legacy EHR Systems

Challenge: Many clinics still use older, fragmented EHR platforms that are not built for third-party integrations. This slows down deployment and increases manual effort, undermining the core benefit of automation.

Solution: To tackle this, we create middleware layers that translate between proprietary EHR formats, build custom APIs, and leverage HL7 and FHIR protocols for compatibility. This allows the AI scribe app to work smoothly even with outdated systems, without disrupting existing workflows.

Tools, APIs, and Frameworks Needed

Creating a high-performing virtual AI nurse app like Gyant requires robust APIs, scalable infrastructure, and healthcare-compliant tech. To ensure seamless conversations, real-time processing, and secure EHR integration, the right tech stack is vital. Here’s a breakdown of essential tools across voice, NLP, integrations, front-end, and deployment.

1. Voice Recognition APIs

To accurately capture patient speech in real time, you need a medical-grade speech-to-text engine. This forms the base of voice interaction and ensures clarity in transcription, even in noisy environments or with varying accents.

• Google Cloud Speech-to-Text: Known for its speed and accuracy, it supports medical vocabulary and can be optimized with custom phrase hints.
• AWS Transcribe Medical: Offers HIPAA-compliant voice transcription and supports real-time streaming for clinical use cases.

2. NLP Engines and Language Processing Libraries

The core of an AI nurse lies in its ability to understand and interpret patient input. These tools help structure conversations, extract clinical insights, and deliver medically accurate responses.

• NVIDIA NeMo: Useful for training medical-specific ASR and NLP models. Offers pre-trained pipelines that can be customized for healthcare
• spaCy: Lightweight and efficient for building rule-based or ML-based NLP pipelines. Good for real-time environments.
• MedSpaCy: An extension of spaCy tailored for clinical NLP tasks, such as extracting symptoms, medications, or diagnoses from patient input.

3. EHR Integration Frameworks

To make the AI nurse practically useful in a hospital setting, you must integrate it with electronic health record systems. These frameworks ensure structured data exchange in a compliant and standardized format.

• FHIR APIs: The foundation for healthcare interoperability. It helps sync patient data, appointments, and treatment history.
• Redox: A middleware layer that simplifies integration with legacy EHRs and modern systems alike.
• Health Gorilla: Offers national-level access to clinical records and lab networks via secure FHIR APIs.

4. Voice SDKs for In-App Recording

In-app voice capture should be smooth and device-agnostic. Whether users are on mobile or web, these SDKs allow you to integrate reliable audio capture functionality.

• Twilio Voice SDK: Ideal for integrating real-time audio in both mobile and web apps. Supports secure communication and transcription readiness.
• Agora SDK: Offers scalable and high-quality voice streaming. Good for apps needing dynamic voice environments with low latency.

5. Cross-Platform App Development

For consistent user experience across devices, choosing a cross-platform framework is essential. These tools allow for rapid development without compromising on performance or UI.

• React Native: Offers fast development cycles, strong community support, and is highly customizable.
• Flutter: Provides better performance and native feel with a single codebase. Suitable for building highly interactive health apps.

6. Deployment and Scalability

Healthcare platforms often face usage spikes. Scalable deployment solutions ensure your app remains stable, secure, and responsive under all conditions.

• Docker + Kubernetes: Ideal for containerizing app components and orchestrating them efficiently. Helps in scaling NLP models and APIs with minimal downtime.
• CI/CD Pipelines with Jenkins or GitHub Actions: Automate testing, deployment, and updates to ensure faster releases with fewer errors. This is crucial for maintaining high availability in clinical environments.

7. HIPAA-Compliant Cloud Storage

Storing sensitive patient data requires healthcare-grade cloud infrastructure. These services provide encryption, access control, and compliance certifications.

• AWS: Offers HIPAA-eligible services and a wide range of healthcare tools.
• Azure Health Data Services: Built specifically for protected health data with built-in security and compliance.
• Google Cloud Platform (GCP): Known for real-time analytics and healthcare API support, with full HIPAA compliance.

Use Case: Implementing a Suki-Like AI Scribe in a Telehealth App

To help visualize the impact of building an AI scribe app, let’s look at a sample use case that reflects real-world challenges and outcomes. This example shows how a multi-specialty clinic network can streamline documentation using a solution like Suki Assistant.

MediPort, a telehealth and specialty clinic app, aimed to reduce clinician documentation time by 60% without disrupting existing EHR workflows.

Working with IdeaUsher, the solution included:

• A real-time AI scribe app accessible via both mobile and web for clinicians across departments
• Full integration with Epic EHR using secure FHIR protocols to push finalized notes directly into patient records
• HIPAA-compliant AWS infrastructure with encryption-at-rest and in-transit, along with access control and audit logging

Results:

• Clinician satisfaction scores rose by 38%
• Note completion time dropped from 12 minutes to under 4 minutes
• Patient throughput improved, allowing more appointments per day without increasing staff workload

Conclusion

AI scribe apps like Suki Assistant are changing the pace of clinical documentation by offering intelligent, voice-powered support that blends into existing medical workflows. By reducing time spent on manual note-taking, clinicians can dedicate more attention to their patients and deliver care with greater efficiency. Developing such a solution requires a thoughtful approach to data security, voice technology, compliance, and EHR integration. With the right technical foundation and user-focused design, an AI scribe app can become a reliable assistant in busy healthcare settings, helping providers streamline documentation while maintaining the accuracy and context that quality care depends on.

Why Choose IdeaUsher to Build an AI Scribe App?

IdeaUsher brings deep expertise in healthcare automation, especially in building ambient AI scribe apps that reduce clinician burnout and improve documentation accuracy. Whether your focus is on voice-enabled transcription, SOAP note generation, or seamless EHR integration, we help bring your vision to life with cutting-edge solutions.

Why Work with Us?

• Clinical Workflow Understanding: We build apps that blend into real-world clinical settings without disrupting your operations.
• Voice and NLP Proficiency: Our AI scribes use advanced voice recognition and medical NLP models for high-quality note generation.
• Trusted by Health Brands: With platforms like Vezita, CosTech Dental App, Allied Health Platform, and Mediport, we’ve helped many healthcare providers streamline their documentation systems.
• Secure and Scalable: We prioritize data security, compliance, and long-term performance from day one.

Check out our portfolio & let’s work together to build a smart AI scribe that enhances care delivery. 

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