How to Build a Care Assistant App like Sensely AI?

In 2025, healthcare assistants are becoming more than just text-based bots; they’re evolving into interactive avatars that bring a human touch to digital care. These avatars, like the ones used in platforms like Sensely, make the experience of interacting with healthcare systems feel more personal and relatable. Instead of just reading through text or receiving robotic responses, patients can now talk to an avatar that guides them, answers their questions, and provides support in a way that feels more natural. 

This shift towards avatar-based healthcare assistants is not just about tech; it’s about making healthcare feel more human and connected, improving both engagement and outcomes for patients.

These apps can also seamlessly integrate with EHR systems, offering patients personalized feedback based on their medical history and providing relevant health content. Having worked with numerous healthcare organizations, IdeaUsher understands what it takes to develop intelligent care solutions like these. That’s why we have put together this blog to show you how to create an AI-driven platform that empowers patients and helps them take charge of their health.

Key Market Takeaways for Healthcare AI Assistants

According to GrandViewResearch, the global AI in healthcare market is growing at a remarkable pace, valued at USD 26.57 billion in 2024 and expected to reach USD 187.69 billion by 2030. This growth, driven by a CAGR of 38.62% from 2025 to 2030, reflects the increasing reliance on AI-powered solutions to improve personalized healthcare, enhance diagnostic precision, and optimize administrative processes.

Source: GrandViewResearch

Healthcare AI assistants are transforming patient care by automating routine tasks, aiding clinical decision-making, and offering continuous patient support. Notable advancements include AI diagnostic tools developed at Massachusetts General Hospital and MIT, which have outperformed human specialists in detecting lung nodules and breast cancer. 

Similarly, IBM Watson’s success in Japan, where it tailors cancer treatments based on genetic data, highlights the potential of AI to revolutionize healthcare practices. AI-powered digital assistants are also enhancing patient satisfaction and streamlining workflows, as seen in Mumbai’s healthcare system.

Collaborations and partnerships are accelerating the global adoption of healthcare AI. For example, Singapore’s Synapxe has teamed up with OpenAI to develop AI prototypes for healthcare services and with AIDX TECH to ensure regulatory compliance and AI safety. These strategic alliances are crucial in advancing the capabilities and reach of healthcare AI assistants.

What is the Sensely Care Assistant & How Does It Work?

Sensely is an advanced AI-driven health tool designed to reshape patient care by enhancing engagement, automating medical triage, and improving care coordination. Unlike typical AI assistants, Sensely combines cutting-edge medical intelligence with compassionate interactions, guiding users through symptom assessments, chronic disease management, and offering remote care support.

Here’s how it works,

1. Conversational AI Interface

Sensely uses sophisticated Natural Language Processing (NLP) and Natural Language Understanding (NLU) to interpret real-time queries from patients. Whether the inquiry is about a specific symptom or a general health concern (e.g., “I’m having chest pain—what should I do?”), the system responds intelligently and with human-like understanding, either through text or voice.

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2. AI-Powered Triage & Symptom Checking

By analyzing user-reported symptoms against extensive medical databases like IBM Watson Health, Sensely provides targeted recommendations. For instance, if symptoms suggest a serious condition, the assistant might advise seeking medical attention immediately—e.g., “Based on your symptoms, it’s best to consult a doctor within two hours.”

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3. Digital Avatars for Human-Like Interaction

To reduce patient anxiety and enhance the experience, Sensely employs lifelike digital avatars, such as “Nurse Molly.” These avatars simulate human interaction, adjusting their tone and responses according to the emotional state of the user. For example, if a patient is distressed, the assistant will provide calming, reassuring responses to improve the overall experience.

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4. Seamless Care Coordination

Sensely integrates smoothly with EHRs and telehealth platforms (such as Epic and Cerner), ensuring that patient data is up-to-date and accessible for medical professionals. It also supports appointment scheduling and medication reminders, helping patients stay on track with their care plan.

The AI Engine Behind Sensely’s Virtual Care Platform

Sensely’s AI-powered care assistant leverages a combination of advanced technologies to provide users with human-like, medically accurate guidance. Here’s a breakdown of how the system works:

1. Natural Language Processing Core

• Multimodal Input Analysis: Sensely processes both voice and text inputs, allowing patients to interact naturally through speech recognition or typing.
• Clinical Intent Recognition: The AI understands medical terminology (e.g., SNOMED CT, ICD-10 codes) and common health expressions, adapting to layperson language and multilingual healthcare queries.
• Contextual Understanding: The AI remembers conversations across sessions, providing continuity. For example, when a user mentions “My head hurts when I bend over,” it identifies sinusitis as a potential cause.

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2. Medical Knowledge Integration

• Symptom Checker Algorithm: Sensely uses a weighted decision tree based on trusted sources like Mayo Clinic’s clinical protocols, CDC diagnostic guidelines, and drug interaction databases.
• Real-Time Data Integration: The system pulls data from connected EHRs via FHIR APIs, wearables like Apple HealthKit and Fitbit, and IoT devices such as smart blood pressure cuffs, ensuring real-time, accurate assessments.

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3. Avatar-Based Interaction System

• Emotion-Adaptive Responses: Sensely adapts its tone based on voice stress analysis, text sentiment scoring, and previous user interactions, providing a more empathetic experience.
• Visual Symptom Mapping: The system guides users through interactive body maps, pain scales, and treatment animation demos, making the experience more visual and engaging.

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4. Clinical Decision Workflow

• Triage Classification: Based on urgency, the system classifies cases as emergency, urgent, routine, or self-care. It prioritizes responses accordingly.
• Care Pathway Generation: Depending on the risk level, the AI either provides self-care instructions, schedules telehealth visits, or directs users to emergency services.
• Continuity of Care: Sensely ensures that EHRs are updated automatically, care teams are alerted, and patients receive follow-up reminders, maintaining a seamless care experience.

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What Sets Sensely Apart from Typical AI Assistants?

Feature	Sensely	Generic AI (e.g., Siri, Alexa)
Medical Accuracy	FDA-cleared algorithms for symptom assessment	General-purpose responses
Avatar-Based UI	Simulates clinician-patient interaction	Text/voice-only interface
Clinical Integrations	Integrates with EHRs, RPM devices	No healthcare integrations
Regulatory Compliance	HIPAA/GDPR-compliant	Not designed for PHI
Use Case	Chronic care, triage, telehealth routing	Weather, shopping, reminders

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Why Are Healthcare Providers Adopting Care Assistant Apps like Sensely?

• Cost Reduction: Sensely cuts ER visits by 30% and reduces administrative costs by automating patient intake.
• Enhanced Patient Engagement: Avatar-driven support boosts treatment adherence by 40%, ensuring better patient outcomes.
• Scalable Remote Care: Sensely integrates with wearables for real-time chronic condition management and supports decentralized clinical trials.
• Regulatory Compliance & Competitive Advantage: Sensely helps healthcare providers meet CMS telehealth regulations while improving patient satisfaction and enhancing reputations.

Features to Include in a Care Assistant App like Sensely AI

After working on numerous healthcare apps, we’ve learned which features truly resonate with users. Based on feedback and experience, we’ve identified the elements that make healthcare assistant apps like Sensely successful. Here’s a look at the key features that stand out:

1. Human-like Avatars

Users connect better when there’s a human touch. Avatars like Sensely’s “Molly” help create a more engaging, personal experience. These virtual characters use both voice and text to make interactions feel more relatable, easing user anxiety and creating a sense of comfort.

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2. Emotion Recognition AI

Understanding a user’s emotions is a game-changer. By detecting stress or anxiety through voice tone or text, Emotion Recognition AI helps the assistant respond with empathy and adjust its approach accordingly. It creates a more compassionate, supportive interaction that users appreciate.

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3. Clinically Rigorous Symptom Checker

Users trust healthcare apps when they get accurate, reliable advice. Sensely’s symptom checker, powered by trusted medical sources like Mayo Clinic and NHS, analyzes symptoms and provides informed recommendations. This feature ensures users feel confident about the advice they receive.

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4. Personalized Health Plans and Content

General health tips aren’t enough; users need recommendations tailored to their specific needs. Sensely creates personalized wellness plans, suggesting content and lifestyle changes based on user data. This approach speaks directly to the user’s goals, improving engagement.

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5. Chronic Condition Management

Managing long-term health issues requires ongoing support. Sensely tracks symptoms, offers personalized feedback, and helps users stay on track with their treatment plans. This feature is essential for users managing chronic conditions, providing consistent, helpful guidance.

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6. Medication Reminders & Adherence

Keeping track of medication schedules can be tricky. Sensely’s reminders and adherence monitoring help users stay consistent with their medication, adjusting alerts based on their habits. This feature is essential for ensuring users don’t miss doses and stay on track with their treatment.

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7. Pharmacy and Facility Locators

When users need healthcare services, convenience matters. Sensely’s pharmacy and facility locator helps users quickly find nearby pharmacies, hospitals, or clinics. With filters for insurance and hours, it’s an easy way to access care without the hassle.

Benefits of a Care Assistant App for a Healthcare App or Business

From our experience, care assistant apps improve patient engagement by offering personal, supportive interactions. They simplify care navigation, ease staff workload, and provide insights that enhance service quality, all while helping businesses stand out with personalized experiences.

1. Enhanced Patient Engagement

Care assistant apps foster a more approachable and supportive experience by using conversational AI. This technology ensures patients feel heard and understood, promoting trust and improving their overall engagement with the app. A friendly, accessible interaction encourages patients to stay involved with their health, leading to better outcomes.

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2. Improved Care Navigation

By incorporating symptom checkers and triage capabilities, care assistant apps streamline access to the right care. Patients can quickly get guidance on whether they need to visit a doctor or take other actions, which reduces confusion and ensures that care is both timely and appropriate.

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3. Brand Differentiation

Personalization is key when it comes to standing out in a competitive market. By using avatars and personalized interactions, care assistant apps create unique, memorable experiences for users. These features help healthcare businesses differentiate themselves and build stronger relationships with patients.

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4. Operational Efficiency

Care assistant apps alleviate pressure on human support staff and call centers by automating tasks like symptom assessments, appointment scheduling, and medication reminders. This not only improves efficiency but also allows healthcare providers to focus on more complex, urgent patient needs, improving overall service delivery.

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5. Data-Driven Insights

Real-time analytics and personalization engines help healthcare businesses improve service quality by tracking user behavior and health patterns. These insights enable businesses to optimize care plans, adjust recommendations, and provide more targeted support, ultimately enhancing patient satisfaction and care outcomes.

How to Build a Care Assistant App Like Sensely AI

When we create a care assistant app like Sensely, our focus is on delivering a product that not only meets your business goals but also improves the experience for your patients. Over time, we’ve refined a clear, step-by-step approach that combines healthcare expertise with technical know-how. Here’s how we build it:

1. Consultation

The process begins with a deep consultation to understand your objectives, whether it’s increasing patient engagement, automating triage, or providing self-care education. We also work with you to make sure your app meets all necessary regulations like HIPAA and GDPR. Finally, we choose the best platform for your app, mobile, web, or messaging, to ensure it reaches your users wherever they are.

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2. Designing the Conversational Experience

Next, we design the app’s conversational flow. We map out the most common use cases like symptom assessments, appointment scheduling, and FAQs. From there, we build user personas and empathy scenarios to ensure the app responds in a way that’s both helpful and comforting. We also focus on creating a unique avatar and tone of voice that makes the experience feel personal and approachable.

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3. Developing the NLP/NLU/NLG Engine

We then turn our attention to the technology that powers the app. Our team builds the Natural Language Processing, Understanding (NLU), and Generation (NLG) models to ensure the app can understand medical queries and emotional cues. Sentiment analysis is integrated so that the app can respond empathetically, tailoring its tone based on the user’s emotions, ensuring a more human, supportive interaction.

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4. Integrating Trusted Medical Content

Accuracy is key in healthcare, so we partner with trusted medical sources like Mayo Clinic to integrate reliable, evidence-based content into the app. We build a knowledge base that aligns with established medical standards like ICD-10 and SNOMED codes. This allows the app to provide clinically accurate symptom assessments and medical advice that users can trust.

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5. Building Personalization

Personalization helps create a deeper connection with users. We design secure user profile management systems and develop dashboards that offer personalized health insights. By enabling adaptive content delivery, we ensure the app responds to each user’s unique needs, which keeps them engaged and invested in their care journey.

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6. Launch

Before launching, we conduct extensive usability testing with real users to make sure the app is intuitive and effective. We also validate the clinical accuracy and safety of the information to ensure everything provided is sound and reliable. After launch, we continue to gather feedback, monitor performance metrics, and make adjustments to improve the app’s functionality and user experience.

Common Challenges in Building an AI Care Assistant 

Having worked with numerous clients, we’ve seen firsthand the challenges that arise when developing AI care assistant apps. Here are some of the most common hurdles we’ve encountered, along with proven solutions we’ve implemented to address them:

1. Clinical Validation & Liability Risks

AI diagnostic recommendations must be medically accurate to avoid potential harm and legal exposure. Without validation, there’s a risk of providing incorrect advice that could harm patients.

Mitigation Strategies

• We prioritize using FDA-cleared AI models, such as those used for diabetes screening (like IDx-DR). 
• We also form multidisciplinary review boards with MDs who validate all algorithms before deployment. 

Clear disclaimers help remind users that AI suggestions aren’t a substitute for professional care. We also ensure that our AI systems continuously learn from new clinical guidelines, keeping the app up-to-date. For instance, Buoy Health’s AI reduced unnecessary ER visits by 20% after a 12-month clinical validation at Harvard.

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2. Sustaining Long-Term User Engagement

Many health apps struggle with user retention, with 52% of users abandoning apps within 30 days. Keeping users engaged long-term requires more than just functional features.

Retention Tactics That Work:

• We create personalized health journeys based on user history, ensuring the content adapts to their needs. Adding gamification elements, like rewarding medication adherence, boosts engagement. 
• We also implement proactive nudges, syncing reminders with wearable devices, and provide human-in-the-loop escalation, where users can contact a clinician if AI detects urgency. 

Woebot Health, for example, boasts a 78% 90-day retention rate by focusing on daily check-ins.

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3. EHR/EMR Integration Complexities

Interoperability remains a major issue, with most hospitals using multiple disparate systems, making integration complex and time-consuming.

Integration Best Practices:

• We rely on SMART on FHIR for easy plug-and-play EHR integration and use middleware solutions like Redox and Particle Health to bridge legacy systems. For older hospital infrastructures, we ensure compatibility with HL7 v2/v3. 
• We design API-first solutions, allowing the app to integrate seamlessly with systems like Epic, Cerner, and Allscripts. 

Mayo Clinic’s AI assistant, for example, reduced physician data entry time by 45% through deep integration with Epic.

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4. Multilingual & Cultural Competency

Around 40% of U.S. patients speak limited English, and cultural beliefs can affect health behaviors. Designing an app that works for diverse populations requires careful attention to language and cultural sensitivity.

Inclusive Design Approaches:

• We train NLP models on 50+ dialects, going beyond standard “textbook” language to ensure better understanding. 
• We also customize avatars with different skin tones, gestures, and local idioms to resonate with various cultural groups. 
• For health content, we provide faith-based guidance, such as Ramadan-friendly advice for managing diabetes. Partnering with community health workers helps us build trust locally and bridge cultural gaps.

Tools, APIs & Frameworks to Build a Care Assistant App

When building a powerful AI healthcare assistant like Sensely, it’s crucial to use the right tools and technologies that not only ensure medical accuracy but also provide an engaging and seamless user experience. Here’s a breakdown of the core technology stack that powers intelligent care assistants:

1. Conversational AI Engines

To drive natural and meaningful medical dialogues, we rely on the following tools:

• Google Dialogflow CX – Best for handling complex healthcare conversation flows, ensuring smooth user interactions.
• Microsoft Healthcare Bot – Pre-built with clinical intent recognition, making it a great option for fast deployment.
• Rasa Pro – An open-source platform that offers HIPAA-compliant deployment, ideal for customizable solutions.

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2. Avatar & Voice Interface Systems

Creating a human-like interaction is key to user engagement. These tools help bring that to life:

Tool	Description
Unity 3D Medical Avatars	Life-like animations that simulate clinician interactions, providing a more engaging user experience.
Unreal Engine MetaHumans	Hyper-realistic digital humans designed for a truly immersive experience, enhancing realism in interactions.
Amazon Polly Medical Voice	Neural Text-to-Speech (TTS) technology with empathetic tonality, making the assistant sound more natural.
Nuance Dragon Medical One	Advanced clinical speech recognition system, making it easier for patients to communicate with the assistant.

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3. Medical Intelligence Backbone

To ensure clinical accuracy, we use trusted medical resources: Infermedica API for symptom checking, Merative (IBM Watson Health) for curated content, Mayo Clinic Platform for physician-validated care pathways, and UpToDate API for real-time clinical decision support. These resources provide reliable, evidence-based health guidance.

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4. Healthcare System Integrations

Connecting with existing healthcare infrastructure is crucial for real-time care coordination. HL7 FHIR Server ensures seamless data exchange, while SMART on FHIR Apps enable direct EHR functionality within the app. Epic App Orchard provides access to Epic EHR integrations, enhancing compatibility with hospital systems, and Cerner Code offers solutions for integrating with Cerner-specific platforms, ensuring smooth integration across healthcare networks.

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5. Engagement Analytics

To measure performance and optimize engagement, these tools provide valuable insights:

• Google Analytics for Firebase – Real-time tracking of user behavior for actionable insights.
• Mixpanel Healthcare – HIPAA-compliant event analysis, helping track patient interactions.
• Custom ML Pipelines – Predictive modeling to identify potential user drop-off.
• Tableau Healthcare – For visualizing clinical metrics, enabling better decision-making.

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6. Security Infrastructure

Given the sensitive nature of healthcare data, security is essential. AWS HIPAA-Eligible Services offer secure, scalable hosting for PHI, ensuring compliance. Microsoft Azure HITRUST provides enterprise-grade protection for healthcare data. Okta Healthcare Identity ensures secure user access through multi-factor authentication, while Protenus uses AI-powered monitoring to ensure data privacy regulations are consistently met.

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Why This Stack Wins?

By using this technology stack, we achieve:

• 70% faster development with pre-built medical APIs.
• 85% first-pass accuracy with trusted clinical content services.
• 100% compliance with healthcare security standards, ensuring patient data is protected.

Use Case of AI Care Assistant in a Regional Health System

One of our clients, a midwestern health system serving over 500,000 patients, approached us with a significant challenge, and we developed a solution that transformed their operations.

The Challenge: Overwhelmed Call Centers & Patient Confusion

This health system was facing a series of pain points that were impacting both their staff and patient satisfaction:

• 40% of call center inquiries were for basic symptom questions, which overwhelmed their staff.
• Long wait times (over 25 minutes) were frustrating patients, leading to poor satisfaction scores.
• 15% no-show rates for follow-up appointments due to unclear instructions and lack of reminders.

The health system needed a solution that could scale, reduce staff pressure, and maintain the quality of care, while also improving the patient experience.

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The Solution: An AI Care Assistant with Human-Like Guidance

We designed and deployed a custom care assistant app that featured several key elements to address the challenges:

Empathetic Avatar-Based Triage

We created a digital nurse avatar using Unity 3D to guide users through symptom checks via Google Dialogflow. This allowed patients to interact via voice or chat, catering to different preferences.

Clinically Validated Medical Intelligence

We integrated Mayo Clinic’s symptom-checker API, ensuring evidence-based, accurate symptom assessments. The app provided personalized care recommendations, such as “Based on your fever duration, see a doctor within 24 hours,” helping users navigate their next steps.

Seamless EHR Integration

We connected the app to the health system’s Epic EHR via SMART on FHIR, enabling one-click scheduling for appointments recommended by the app. This streamlined the process and improved care coordination.

Proactive Follow-Up System

We automated SMS/email reminders for upcoming visits, ensuring patients stayed on track. Additionally, post-visit surveys were sent out to gather feedback and track satisfaction.

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The Results: Efficiency & Patient Experience Transformed

In just 6 months, the health system saw significant improvements:

• 40% fewer unnecessary calls as AI handled basic inquiries, freeing up staff for more complex cases.
• 22% higher patient satisfaction (based on Press Ganey scores) due to 24/7 access to care and information.
• 30% reduction in no-shows, thanks to automated reminders that encouraged adherence to follow-up appointments.

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Why Does This Work for Healthcare Systems?

Problem	Our Solution	Tech Used
High call volume	AI triage + avatar	Dialogflow, Unity
Poor follow-up	Automated reminders	Twilio, Epic APIs
Patient confusion	Evidence-based content	Mayo Clinic, Infermedica API

Conclusion

Empathetic care assistants are essential for improving patient experience by offering accessible, personalized, and reliable support. Platforms like Sensely lead the way in creating user-centric, trustworthy virtual care, setting a high standard for the industry. For healthcare businesses looking to stand out, investing in these innovative solutions can make a real difference. At Idea Usher, we’re here to partner with you, helping to build and scale these impactful tools to enhance care and drive patient satisfaction.

Looking to Develop a Care Assistant App like Sensely AI?

At IdeaUsher, we specialize in building personalized, avatar-based care assistant apps that blend medical accuracy with a human touch, just like Sensely AI. We work with you to create an interactive, engaging experience where patients feel supported by lifelike avatars that provide both reliable healthcare guidance and compassionate care.

Why Choose IdeaUsher?

• 500,000+ Hours of Coding Expertise – Our team of ex-MAANG/FAANG engineers builds scalable, secure, and compliant AI healthcare solutions.
• Proven AI Avatars & Triage – We craft lifelike digital assistants (Unity/Unreal) and integrate NLP-powered symptom checking for a seamless user experience.
• Seamless EHR Integration – We integrate with SMART on FHIR, Epic, Cerner, and more, eliminating siloed patient data.
• HIPAA/GDPR Ready – From day one, with AWS/Azure healthcare cloud hosting to ensure full compliance.

Check out our latest healthcare AI projects and see how we’ve helped hospitals, insurers, and digital health startups transform patient engagement. Let’s build a better, more efficient healthcare experience together!

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