Microsoft Dynamics D365 Use Cases

Clinical Documentation & Conversation AI solution | DynaTech

Written by Mehul Thacker | Jun 17, 2026 5:15:00 AM

DynaTech’s Clinical Documentation & Conversation AI is an invisible, highly accurate medical scribe sitting in the room during a patient visit.

Where earlier doctors had to type notes, fill in EHR information, and do everything else from memory, our AI clinical documentation solution listens to the conversation and captures the necessary details in real time.

Instead of working with a massive block of rough text, our solution picks out the important medical details, like;

  • Health issues
  • Symptoms
  • Medications
  • Treatment plan

It automatically sorts them into the correct sections of the hospital's electronic health record (EHR) system. The doctor reviews and approves the final note while eliminating hours of manual data entry, allowing providers to focus entirely on the patient while keeping hospital records highly accurate and searchable.

What Makes This Solution Different from Built-In Copilot?

Microsoft Copilot is an excellent productivity tool used for repetitive and time-consuming tasks like summarizing conversations, retrieving information, and assisting users with content generation. But it cannot work as a clinical documentation AI solution, as healthcare tasks require a different level of operational awareness.

DynaTech's Clinical Documentation & Conversational AI solution is designed specifically for clinical environments where documentation accuracy, structured medical outputs, compliance requirements, and healthcare interoperability standards are critical.

Powered by Copilot Studio and Azure OpenAI, the solution connects through secure integration layers to healthcare systems and configured clinical data sources. Rather than simply generating summaries, we have built the AI platform for clinical documentation to do the following tasks;

  • Capture clinical context
  • Structure information according to healthcare documentation requirements
  • Prepare EHR-ready outputs
  • Support downstream workflows

The result is an operational clinical documentation layer that helps healthcare professionals reduce administrative burden while maintaining documentation quality and consistency.

Key Capabilities of Clinical Documentation and Conversational AI Solution

1. Speech-to-Text Conversion

Since patient-doctor conversations contain highly sensitive information, our MS teams-compatible solution operates within enterprise-grade security frameworks and supports healthcare organizations that require strict privacy controls, auditability, and governed access to clinical data.

2. Real-time Clinical Transcription

Clinical conversations are transcribed as they occur, but they are often recreated on paper by memory. With our conversational AI for the healthcare industry, physicians, nurses, specialists, and care teams no longer need to rely on memory or post-visit note creation.

3. Automated EHR Field Population

Instead of generating unstructured transcripts, the solution identifies clinically relevant information and prepares structured outputs that can populate configured EHR fields through approved integration workflows. This means the solution parses data and insights into corresponding sections of the medical record.

4. Ambient Listening

Healthcare professionals should focus on patients and ensure they are not disturbed by keyboards, the solution continuously captures the conversation in the background, reducing the need for manual note-taking during consultations while preserving the natural flow of clinician-patient interactions.

5. Searchable Indexed Documentation

With our AI clinical documentation solution, unstructured verbal exchanges transform into structured and searchable data assets. This means every documented interaction is indexed and organized as per the configured requirements. As a result, the healthcare providers can retrieve the information they need from previous conversations, treatment discussions, and summaries when required.

6. Structured Medical Output

The solution transforms conversations into clinically structured outputs, including symptoms, diagnoses, medications, treatment plans, follow-up actions, and other healthcare-specific documentation elements required by care teams.

7. Multi-Specialty Support

The model evaluates terminology across various medical disciplines, adjusting contextual logic for cardiology just as effectively as orthopedics. Moreover, we can configure the solution to support specialty-specific workflow and documentation structures.

DynaTech Clinical Documentation & Conversation AI Solution

The Problem It Solves

The clinical staff in every healthcare organization has to endure a massive administrative burden, which adds to their already stressed work schedule. Doctors manually type post-visit notes, an exercise that routinely extends their workday and contributes heavily to physician burnout.

During these intense verbal conversations, critical subtleties often go unrecorded, which affects the treatment plans. The current operational standard forces highly paid specialists to function as data entry clerks, but even with this approach, manual transcription is fundamentally time-consuming.

Providers must re-enter identical information across multiple EHR fields, a redundant process that can lead to coding errors, and, as a result of fatigue, it impacts patient throughput and the overall quality of care delivered on the floor.

What the solution Actually Does?

The Clinical Documentation & Conversational AI solution functions as a documentation expert and intelligent healthcare partner trained to operate within any specific healthcare workflow. During a patient encounter, our system will;

  • Captures and transcribes the conversation in real time.
  • Azure OpenAI-powered reasoning processes the clinical context and prepares structured documentation outputs.
  • Using configured integration layers, the solution can retrieve relevant patient context, organize conversation data, generate visit summaries, prepare documentation structures, and support EHR workflows.

This is all the while healthcare professionals maintain complete control of clinical decisions and documentation review. Our conversational AI for healthcare solution only accelerates documentation creation while ensuring clinicians maintain oversight before information enters operational systems.

Agentic AI | Conversational AI Solutions for Healthcare

Scenario 1: The Routine Follow-Up

A primary care physician conducts a pre-scheduled 15-minute follow-up with a diabetic patient, and in this conversation, they talk about things like;

  • Blood sugar trends
  • Slight adjustment to insulin dosage
  • Referral to podiatry.

The ambient listening component captures all this information, and Azure OpenAI separates the casual greeting from the clinical data. Using the conversations and their specifics, the AI solution updates the new insulin dosage in the medication field, updates the plan with the next referral date, and generates a structured summary for the physician to sign off on before the next patient even enters the room.

Scenario 2: The Complex Multi-Specialty Consult

During an oncology consult, multiple treatment modalities and lab results are discussed rapidly between doctors, doctor-nurse, and doctor-patient. The solution evaluates the dense medical terminology against its multi-specialty framework while noting down the response of each party in the entire conversation. It parses the historical data discussed, isolates the specific chemotherapy protocols mentioned, and maps them to standard FHIR fields.

Operational Impact of Clinical Documentation and Conversation AI Solution

Business Challenge Agentic AI Solution
A high volume of manual data entry makes doctors spend extensive time on documentation. The AI clinical documentation solution captures real-time conversations and uses the speech-to-text capability to enter all information, effectively eliminating the need for providers to manually type out post-visit notes.
Loss of critical clinical details, as the doctors and nurses may not be able to remember every nuance of the conversation. The ambient listening feature of our conversational AI for healthcare tool listens closely to the entire interaction, ensuring important details discussed verbally are added on the portal, promoting documentation consistency across providers and departments.
Redundant data input across systems caused by inconsistent clinical note quality. Parsed data maps autonomously into standard EHR fields (HPI, meds, diagnosis), preventing manual re-entry and ensuring all information is added in real-time without causing delays.
Lengthy chart closure times due to a patient's information being spread across departments. By staging structured medical outputs directly via HL7/FHIR protocols, the review process shrinks from hours to minutes as all information from all departments, doctors, and labs is available on a single portal.
Unsearchable legacy medical records make all information difficult to search and retrieve. Verbal interactions are converted into searchable, indexed documentation, providing instant operational context for future visits.

How the AI Clinical Documentation solution Works Technically?

Execution of the conversational AI for the healthcare industry is done across several distinct architectural layers within the Microsoft ecosystem.

  • Azure Speech Services: This AI technology handles the initial audio ingestion, operating as the secure speech-to-text conversion engine.
  • Azure OpenAI: As the reasoning layer for our AI solution, Azure OpenAI interprets the clinical context, categorizing raw text into structured medical formats.
  • Azure Healthcare APIs: As our solution does not co-mingle the reasoning model with your core data storage, all data is routed to Azure Healthcare APIs, utilizing FHIR standards to format the payload correctly for your specific EHR architecture.

Apart from the implementation on these three layers, no core EHR schema changes are required.

Who Benefits from Clinical Documentation & Conversational AI Solution?

  • Physicians and Specialists: Doctors and healthcare providers now won't spend hours on charting and indexing as the solution takes care of these tasks.
  • Health Information Management (HIM) Teams: Medical coders receive structured, standardized documentation faster, directly within MS Teams, as our solution runs natively, and this reduces the time spent chasing down providers for chart addenda or clarifications.
  • Hospital Operations Leadership: Facility managers see increased patient throughput as the healthcare providers can now focus more on patients and safely manage slightly higher patient loads without compounding burnout.
  • IT and Compliance Officers: Technical teams deploy a secure, HIPAA-compliant solution that leverages existing Azure infrastructure, maintaining strict governance over patient data without managing standalone, unverified applications.

to know more about Clinical Documentation & Conversation AI Solution.

What Deployment Looks Like?

DynaTech deploys the Clinical Documentation & Conversational AI solution as an extension of your existing healthcare environment, and the implementation work scope includes;

  • Copilot Studio configuration
  • Azure AI services setup
  • Healthcare integration configuration
  • Entra ID security provisioning
  • API permission management
  • Workflow customization based on clinical requirements

The deployment does not require core EHR schema changes, as we have built the best conversational AI tools for healthcare to operate through secure integration layers designed to work alongside existing healthcare systems.

The Return is Measurable, Not Theoretical

After deployment, healthcare organizations will experience success through reduced clinician documentation time, faster record completion, improved documentation consistency, lower administrative workload, and improved provider productivity. The objective of our solution is simple: to allow healthcare professionals to spend more time delivering care and less time documenting it.