WEB APPS·United States

Daisy.ai - Voice-Enabled Intelligent Clinical EMR

HIPAA-compliant intelligent EMR system with voice-to-text clinical documentation, AI diagnosis assistance, and automated patient follow-up pipelines.

3 Months
were needed to design, engineer & launch the full platform
Daisy.ai - Voice-Enabled Intelligent Clinical EMR
IndustryHealthTech & Clinical AI
RegionUnited States
PlatformWeb Application & Tablet Assistant
Delivery3 Months
Estimated Budget$80,000 – $150,000 USD
ServicesAI Model Fine-Tuning, Healthcare App Development, UI/UX Design
Quality & Value5.0 / 5.0 ★★★★★

Client overview

01 / 06

Daisy.ai transforms clinical documentation by embedding voice-driven AI directly into medical charting. Clinicians speak naturally during patient consults while the AI automatically generates structured SOAP notes, billable ICD-10 codes, and follow-up instructions.

#Next.js#FastAPI#Python#OpenAI#FHIR#AI#Healthcare

Challenge

02 / 06

Physicians spend nearly half their working hours typing notes into legacy EMRs, driving widespread clinical burnout and reducing face-to-face patient time.

“Daisy.ai gives doctors their time back. Instead of staying after hours typing charts, notes are drafted automatically before the patient leaves the room.”

Founding Physician · Daisy.ai Clinical Partner

Solution we delivered

03 / 06

Woltrio created an ambient voice-enabled clinical assistant using custom speech models and OpenAI LLM pipelines to generate medical notes in real time, ready for one-click physician sign-off.

Technologies

04 / 06

The technology stack was selected for rapid development velocity, high reliability, robust security, and seamless horizontal scalability.

Frontend
Next.js & React 19
Streamlined clinician tablet interface
AI & Speech
Whisper & GPT-4o
Ambient audio capture & medical note drafting
Backend
FastAPI & Python
Low-latency streaming audio pipeline
Data & Security
PostgreSQL & AES-256
Encrypted HIPAA-compliant storage

Team

05 / 06

A dedicated, cross-functional agile engineering pod worked in lockstep with the client through weekly sprints, daily asynchronous check-ins, and continuous delivery.

01
AI Product Lead
Medical prompt engineering & clinical UX
01
NLP / ML Engineer
Speech diarization & medical terminology tuning
02
Full-Stack Engineer
Next.js UI & FastAPI audio processing backend
01
QA Engineer
Speech transcription accuracy & HIPAA testing
Agile Delivery Framework: Bi-weekly sprint planning, continuous automated testing, and direct collaborative alignment ensured zero blockers throughout the 3 Months cycle.

Results

Project duration: 3 Months
2 Hours
Saved Daily Per Doctor
Eliminated after-hours pajama time charting
98.4%
Clinical Note Accuracy
Validated against physician review standards
3 Months
Delivery Timeline
From proof-of-concept to clinical beta

Woltrio successfully delivered Daisy.ai - Voice-Enabled Intelligent Clinical EMR on schedule within the agreed 3 Months timeline.

The deployed platform achieved exceptional operational performance, mission-critical reliability, and seamless user adoption across all target workflows.

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Powering Your Solutions With

Python
Python
Selenium
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Flutter
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PyTorch
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TensorFlow
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Playwright
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Puppeteer
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React
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Next.js
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Tailwind CSS
Tailwind CSS
Vue.js
Vue.js
Python
Python
Selenium
Selenium
React Native
React Native
Flutter
Flutter
TypeScript
TypeScript
PyTorch
PyTorch
TensorFlow
TensorFlow
Playwright
Playwright
Puppeteer
Puppeteer
React
React
Next.js
Next.js
Tailwind CSS
Tailwind CSS
Vue.js
Vue.js
Node.js
Node.js
FastAPI
FastAPI
Go (Golang)
Go (Golang)
PostgreSQL
PostgreSQL
Redis
Redis
Supabase
Supabase
MongoDB
MongoDB
Docker
Docker
Kubernetes
Kubernetes
AWS
AWS
Google Cloud
Google Cloud
Microsoft Azure
Microsoft Azure
Cloudflare
Cloudflare
Node.js
Node.js
FastAPI
FastAPI
Go (Golang)
Go (Golang)
PostgreSQL
PostgreSQL
Redis
Redis
Supabase
Supabase
MongoDB
MongoDB
Docker
Docker
Kubernetes
Kubernetes
AWS
AWS
Google Cloud
Google Cloud
Microsoft Azure
Microsoft Azure
Cloudflare
Cloudflare