HealthOrbit is a global ambient medical scribe platform operating across 12 countries. It enables healthcare providers to capture doctor-patient conversations and automatically generate clinical documentation. . As adoption expanded across specialties and geographies, HealthOrbit required a scalable approach to manage growing documentation customization demands.
Problem: Manual processes limited healthcare workflow automation
HealthOrbit receives 5 to 10 template customization requests daily from physicians seeking specialty-specific documentation formats. Each request required manual engineering effort to review samples, create prompts, validate outputs, and deploy templates.
As adoption grew across specialties and regions, this process became difficult to scale, increasing operational overhead, delaying physicians, and limiting healthcare workflow automation. The platform also faced challenges in managing diverse documentation standards, template governance, and compatibility with its existing ambient scribe infrastructure.
Solution: Healthcare workflow automation powered by Gen AI
GoML built an AI-powered healthcare workflow automation platform that enables physicians to create, customize, validate, and publish clinical documentation templates without engineering support. Powered by GoML's AI Content Generation Accelerator, the solution combines LLMs, structured template generation, validation frameworks, and secure backend services to automate template management while ensuring compatibility with HealthOrbit's existing clinical documentation infrastructure.
Conversational template creation and automation
Physicians can describe documentation requirements using natural language instead of submitting manual requests.
Key capabilities include:
- Natural language template creation
- Automated template generation
- Subsections and hierarchical layouts
- Structured table identification
- Template preview before publishing
- Schema validation and compliance checks
- Template sharing across individuals and organizations
This approach significantly improves healthcare workflow automation by reducing manual intervention throughout the template creation lifecycle.
Natural language understanding for clinical workflows
The solution uses Gen AI to understand physician intent and convert requirements into structured documentation templates.
Capabilities include:
- Identification of sections and subsections
- Recognition of specialty-specific medical terminology
- Generation of structured JSON templates
- Support for iterative template modifications
- Automated handling of complex clinical documentation requirements
By automating template interpretation, HealthOrbit can streamline healthcare workflow automation across diverse medical specialties.
Document upload and template extraction
Many physicians already have existing documentation formats in PDF or image form.
The platform supports:
- PDF uploads
- JPEG and PNG image uploads
- Secure storage using Amazon S3
- Template structure extraction
- Section header identification
- Field and formatting pattern recognition
- Automatic conversion of uploaded samples into reusable templates
This allows physicians to accelerate template creation while preserving existing documentation standards.
Template management and lifecycle automation
GoML developed backend APIs that automate the entire template management process.
Supported capabilities include:
- Template creation
- Template retrieval
- Template updates
- Template deletion
Dynamic section management
- Metadata management
- Version control support
- Naming convention enforcement
- Duplicate prevention
- Multi-tenant access controls
These capabilities create a scalable healthcare workflow automation framework for managing documentation templates across organizations.
Preview, validation, and governance
Before publishing, every template is automatically validated against HealthOrbit's documentation requirements.
Validation includes:
- JSON schema compliance
- Required field validation
- Prompt configuration validation
- Template completeness checks
- Confidence scoring
- Safety guardrails
- Automated retry workflows
When validation fails or confidence scores fall below thresholds, the platform automatically retries generation up to two times before requesting user input.
This ensures healthcare workflow automation does not compromise documentation quality or system compatibility.
Header and footer automation
The platform supports dynamic generation of headers and footers for exported documentation.
Capabilities include:
- Automatic physician information population
- License and practice ID insertion
- Organization logo integration
- Custom placeholders
- Organization-specific branding
This eliminates repetitive configuration work and supports consistent document formatting.
Infrastructure and deployment
The solution is built on a scalable AWS architecture.
Technology stack:
- Amazon Bedrock
- Claude
- AWS API Gateway
- AWS Lambda
- Amazon Textract
- Python REST APIs
- Amazon S3
- DynamoDB
- Cloud-native security and monitoring services
Quality assurance
Testing focuses on reliability, accuracy, and healthcare workflow automation performance across specialties.
Validation includes:
- End-to-end template generation testing
- Clinical documentation compatibility testing
- Specialty-specific output validation
- Complex template testing
- PDF extraction accuracy testing
- Integration testing with HealthOrbit systems
- Medical SME reviews
.svg)
Impacts
- 85% minimum field-level exact match accuracy
- Less than 10-15% hallucination rate
- 85-90%% extraction accuracy for digital documents
- Support for 80% of common template use cases without manual intervention
- Zero breaking changes to clinical documentation workflows
- Accurate population of physician and organization metadata
About
Before Gen AI and after Gen AI
"By introducing Gen AI-powered healthcare workflow automation, HealthOrbit transformed template customization from an engineering-dependent process into a scalable self-service experience for healthcare providers."
Prashanna Rao, Head of Engineering, GoML.
Key takeaways for healthcare organizations
Common challenges
- Manual documentation customization doesn't scale
- Engineering teams become workflow bottlenecks
- Specialty-specific templates increase complexity
- Template governance becomes harder at scale
Practical guidance
- Automate documentation workflows with Gen AI
- Enable natural language template creation
- Implement automated validation controls
- Support multi-tenant template management
- Ensure compatibility with existing systems
- Focus on high-volume workflows first
Ready to build healthcare workflow automation solutions
Partner with GoML to build secure, scalable healthcare workflow automation solutions using Generative AI with AI Matic.
