Explore OurAI Capabilities
Discover how our advanced AI agents, intelligent prompts, agentic workflow orchestration, and RAG systems transform healthcare documentation and clinical decision-making.
AI Agents
Intelligent agents that automate clinical workflows and decision-making processes
Smart Prompts
Context-aware prompts that guide AI models for optimal clinical outcomes
Workflow Orchestration
Seamless coordination of multiple AI agents for complex healthcare processes
RAG Systems
Retrieval-Augmented Generation for evidence-based clinical recommendations
AI Agents: Customizable Templates for Your Practice
Create and customize your own AI agents using our templates. Design specialized agents that handle specific clinical tasks tailored to your practice's unique workflows and requirements.
Clinical Documentation Agent
Automatically generates SOAP notes, clinical summaries, and treatment plans from client intake forms and assessments.
Risk Assessment Agent
Analyzes client data to identify potential health risks, drug interactions, and contraindications for early intervention.
Workflow Orchestration Agent
Coordinates multiple AI agents and clinical processes to ensure seamless client care workflows from intake to treatment.
Form Intelligence Agent
Dynamically triggers appropriate forms based on clinical findings and client responses, ensuring comprehensive data collection.
Clinical Decision Support Agent
Provides evidence-based recommendations and clinical insights to support healthcare providers in making informed decisions.
Quality Assurance Agent
Monitors and validates the quality of AI-generated content, ensuring accuracy and compliance with clinical standards.
How AI Agents Work Together
Data Input
Form Intelligence Agent processes client intake forms and triggers appropriate workflows
Processing
Multiple specialized agents analyze data, assess risks, and generate clinical insights
Output
Quality-assured clinical documentation and recommendations delivered to providers
AI Prompts: Intelligent Context-Aware Instructions
Our sophisticated prompt engineering ensures AI models receive precise, context-aware instructions that produce clinically accurate and relevant outputs tailored to each healthcare scenario.
Dynamic Prompt Generation
Our AI system dynamically generates prompts based on client data, clinical context, and specific healthcare workflows. Each prompt is carefully crafted to maximize accuracy and clinical relevance.
Context-Aware Prompting
Prompts adapt based on client demographics, medical history, and current symptoms
Specialty-Specific Templates
Customized prompt templates for different medical specialties and use cases
Real-time Optimization
Continuous learning and refinement of prompts based on clinical outcomes
Sample Prompt Structure
Current Symptoms: Chest pain (7/10), shortness of breath, diaphoresis
Include: Risk stratification, diagnostic recommendations, follow-up plan
Specialized Prompt Categories
Clinical Documentation
Prompts designed for generating accurate SOAP notes, clinical summaries, and treatment plans
Risk Assessment
Specialized prompts for identifying and evaluating clinical risks and safety concerns
Diagnostic Support
Prompts that guide differential diagnosis and clinical reasoning processes
Treatment Planning
Prompts for generating comprehensive, evidence-based treatment recommendations
Client Communication
Prompts for generating client-friendly explanations and educational materials
Quality Assurance
Prompts for validating and improving the quality of AI-generated clinical content
Prompt Engineering Best Practices
Clinical Accuracy
- Evidence-based prompt construction using clinical guidelines
- Integration of medical terminology and clinical reasoning patterns
- Validation against clinical standards and best practices
Contextual Relevance
- Dynamic adaptation based on client demographics and history
- Specialty-specific customization for different medical fields
- Real-time optimization based on clinical outcomes and feedback
Agentic Workflow Orchestration: Intelligent Process AutomationComing Soon
Our upcoming agentic workflow system will coordinate multiple AI agents to execute complex healthcare processes autonomously, ensuring seamless client care from intake to treatment completion.
Bidirectional Workflow Architecture
Client Registration
Initial intake forms triggered automatically
Clinical Assessment
AI-driven examination and risk analysis
Treatment Planning
Automated documentation and care coordination
Intelligent Form Triggering
Based on the dental practice workflow from our documentation, our system intelligently triggers appropriate forms based on clinical findings and client responses, ensuring comprehensive data collection.
Example: Dental Practice Workflow
Workflow Decision Tree
Medical History Analysis
Heart conditions detected → Medical Records Release triggered
Diabetes present → Enhanced monitoring protocols activated
Clinical Examination
Periodontal pockets >4mm → Scaling consent form
Missing teeth identified → Implant consultation workflow
Treatment Planning
Complex procedures → Sedation consent triggered
Surgical needs → Post-op instruction forms prepared
Multi-Agent Coordination
Data Collection Agents
Coordinate form presentation and data validation across multiple touchpoints
- Form Intelligence Agent
- Validation Agent
- Completeness Monitor
Analysis Agents
Process clinical data and generate insights for treatment planning
- Risk Assessment Agent
- Clinical Decision Support
- Diagnostic Assistant
Documentation Agents
Generate comprehensive clinical documentation and care plans
- Clinical Documentation
- Treatment Planning
- Quality Assurance
Workflow Orchestration Benefits
85% Time Reduction
In administrative tasks and form processing
99% Accuracy
In form triggering and data validation
Real-time Adaptation
Dynamic workflow adjustment based on clinical findings
Seamless Integration
Works with existing healthcare systems and workflows
AI RAG System: Your Custom Knowledge Base
Upload your own documents, research papers, protocols, and knowledge base materials. Our RAG system will use your specific content to provide contextual, evidence-based recommendations tailored to your practice.
RAG System Architecture
Query Processing
Clinical questions are analyzed and converted to semantic vectors
Knowledge Retrieval
Relevant clinical information is retrieved from knowledge bases
Context Augmentation
Retrieved knowledge is combined with client-specific context
Response Generation
AI generates evidence-based clinical recommendations
Your Custom Knowledge Sources
Upload your own documents and knowledge base materials. Our RAG system will process and use your specific content to provide contextual recommendations tailored to your practice protocols and preferences.
Practice Protocols
Your clinic's specific treatment protocols and standard operating procedures
Research Papers
Your collection of relevant research papers and clinical studies
Clinical Guidelines
Specialty-specific guidelines and best practices you follow
Reference Materials
Drug references, diagnostic manuals, and other clinical resources
RAG Query Example
Clinical Query
"What are the current treatment recommendations for a 65-year-old diabetic client with newly diagnosed atrial fibrillation?"
Retrieved Knowledge
- • 2023 AHA/ACC/HRS Atrial Fibrillation Guidelines
- • Diabetes-specific anticoagulation considerations
- • Recent clinical trials on DOAC efficacy
- • Drug interaction profiles with diabetes medications
Generated Response
"Based on current guidelines, recommend CHA2DS2-VASc score calculation. For this client (likely score ≥2), initiate anticoagulation with DOAC (apixaban or rivaroxaban preferred due to diabetes). Monitor renal function and consider cardiology referral for rhythm management."
RAG System Benefits
Real-time Updates
Knowledge base continuously updated with latest medical research
Evidence-Based
All recommendations backed by peer-reviewed clinical evidence
Contextual Relevance
Recommendations tailored to specific client contexts and conditions
Instant Access
Immediate retrieval of relevant clinical information when needed
Real-World Workflow Examples
See how our AI capabilities work together in real healthcare scenarios, from client intake to treatment completion with sample generated outputs.
Dental Practice Workflow Example
Workflow Steps
Client Registration
New client completes intake form online
AI Risk Assessment
System detects diabetes and heart condition
Clinical Examination
Dentist finds periodontal disease and missing teeth
AI Documentation
System generates comprehensive treatment plan
AI-Generated Clinical Documentation
SOAP Note - Subjective
58-year-old male presents for routine dental examination. Chief complaint: "My gums bleed when I brush." Client reports diabetes (Type 2, controlled with metformin) and history of myocardial infarction (2019). Current medications include metformin 500mg BID and atorvastatin 20mg daily.
Assessment & Plan
Diagnosis: Moderate periodontitis (K05.32), Missing teeth #14, #15
Treatment Plan:
1. Scaling and root planing - quadrants 1&2
2. Implant consultation for missing molars
3. Enhanced periodontal maintenance q3months
4. Coordinate with physician for cardiac clearance
AI Risk Alerts
- • Diabetes: Monitor healing, consider antibiotic prophylaxis
- • Cardiac history: Verify current cardiac status before procedures
- • Drug interaction check: No contraindications with current medications