AI Clinical Documentation & Ambient AI Medical Scribe

Enable Accurate, Real-Time Clinical Documentation with Workflow-Aligned AI Medical Scribe

Automatically capture encounters in real time and generate structured notes directly within your EHR.

Embedded AI Scribe in
Custom EHR

Specialty-Aligned SOAP
Templates

Structured Clinical
Data Mapping

HL7/FHIR Interoperability
Sync

Embedded AI Scribe in Custom EHR

Ambient AI Scribe: Real-Time Documentation Inside Your EHR.

Custom EHR software dashboard with voice-assistant feature on custom EHR mobile app showcasing AI scribing

Embedded AI Scribe in Custom EHR

Ambient AI Scribe: Real-Time Documentation Inside Your EHR.

Securely capture provider-patient conversations during visits without manual prompting, giving complete attention to patients and not documentation.

Convert patient encounters into structured, review-ready clinical notes within seconds, reducing documentation backlog.

Enable quick review, edit, and approve generated notes directly within the EHR interface, keeping care continuous and documentation under control.

Generate structured notes aligned with clinical standards automatically as per visit type, specialty requirements, and patient history.

Support live audio capture, voice dictation, and structured manual input, ensuring flexibility across different provider documentation preferences.

Specialty-Aligned SOAP Templates

Smart SOAP Templates: Aligned to Your Clinical Workflow.

Patient appointment scheduling screen on custom EHR

Specialty-Aligned SOAP Templates

Smart SOAP Templates: Aligned to Your Clinical Workflow.

Automatically organize captured encounter details into Subjective, Objective, Assessment, and Plan sections, reducing manual formatting and ensuring standardized documentation.

Create clinically relevant visit notes aligned with specialty-specific requirements such as primary care, cardiology, or behavioral health.

Reduce ambiguity, maintain clarity, and support accurate coding with standardized clinical language, abbreviations, and data formats.

Adapt documentation templates to suit the organization’s internal standards, workflows, and compliance expectations.

Ensure documentation completeness alignment with reimbursement requirements and regulatory guidelines, minimizing gaps that can delay claims.

Structured Clinical Data Mapping

Structured Data Mapping: From Conversation to Billable Data.

Patient portal dashboard in custom EHR with pop-up with specific patient records detailed

Structured Clinical Data Mapping

Structured Data Mapping: From Conversation to Billable Data.

Extract diagnoses and clinical findings from encounter notes and map them into structured problem lists directly within the EHR.

Identify medications, dosage changes, and allergy updates from conversations and convert them into trackable data fields.

Seamlessly link documented assessments to appropriate coding-support fields, improving documentation clarity for billing teams.

Distribute relevant information automatically into vitals, labs, history, and other structured EHR fields to reduce repetitive manual data entries.

Structure captured data in a format ready for quality reporting, performance tracking, and value-based care metrics.

HL7/FHIR Interoperability Sync

HL7/FHIR Sync: Real-Time Interoperability Without Disruption.

Custom EHR dashboard of providers and mHealth EHR app interface

HL7/FHIR Interoperability Sync

HL7/FHIR Sync: Real-Time Interoperability Without Disruption.

Support modern FHIR standards to exchange structured clinical data seamlessly with EHRs and connected healthcare platforms.

Ensure compatibility with legacy systems such as lab interfaces, imaging platforms, and billing workflows without any lapses.

Keep documentation, structured fields, and updates consistent across all integrated systems instantly.

Protect patient data in transit and at rest with end-to-end encrypted data pipelines and communication protocols.

Quickly validate updates before synchronization, preventing data duplication, errors, and conflicts across integrated systems.

WHO IT’S FOR & WHAT PROBLEM IT SOLVES

AI Medical Scribe to Reduce Documentation Overload and Eliminate Scribe Dependency

Designed for healthcare organizations facing documentation overload, scribe dependency, and workflow inefficiencies, ready to modernize with embedded ambient AI.

Primary Care & Multi-Specialty Practices

For practices where providers spend hours completing charts after the clinic. Embedded ambient AI captures encounters in real time, generates structured SOAP notes, and reduces after-hours documentation without disrupting clinical workflows.

Health Systems Reducing Scribe Dependency

For organizations seeking to scale documentation without expanding scribe teams. Automate note generation, standardize documentation quality, and maintain billing accuracy across locations with EHR-integrated AI.

Healthcare IT & Revenue Leaders

For IT and revenue teams, modernizing clinical workflows. Deliver structured, billing-ready documentation with secure HL7/FHIR integration, governance controls, and real-time synchronization across systems.

Faster AI Adoption

Electronic Health Records (EHR)

Reduced Risk

Hospital Information Systems (HIS)

Scalable Infrastructure

Revenue Cycle Management (RCM)

Aligned AI Investments

Patient Management Systems (PMS)

Ready to Reduce After-Hours Charting?

Directly integrate an AI medical scribe to automate clinical notes in real time and give your providers their evenings back.

Client Testimonials

Trusted by Healthcare Leaders Modernizing Clinical Documentation

See how providers, IT leaders, and revenue teams are reducing after-hours charting, lowering scribe dependency, and improving documentation accuracy with embedded Ambient AI.

"We reduced after-hours charting significantly within weeks..."

After deploying the embedded AI scribe, our providers stopped taking charts home. Documentation is generated during visits, reviewed quickly, and submitted the same day. It’s improved morale across our practice.

Dr. Michael Reynolds
Medical Director, ClearView Family Health

"It replaced our need to expand the scribe team..."

We were planning to hire additional scribes as we scaled. Instead, we implemented the AI documentation agent inside our EHR and reduced documentation overhead without compromising note quality.

Jennifer Collins
COO, Riverstone Medical Group

"Structured documentation improved our billing accuracy..."

The structured data mapping and SOAP alignment made our notes more coding-friendly. We’ve seen fewer documentation-related billing delays and cleaner claim submissions.

David Thompson
Director of Revenue Cycle, Summit Primary Care Network

"Providers adopted it faster than expected..."

Because it works in real time and allows in-EHR review, there was minimal resistance. The human-in-the-loop controls gave our clinicians confidence in the AI output.

Dr. Lisa Carter
Clinical Operations Lead, Liberty Multi-Specialty Clinic

"We modernized documentation without disrupting care..."

The HL7/FHIR interoperability ensured all documentation stayed synchronized across labs, billing, and reporting systems. It felt like a workflow upgrade — not a risky overhaul.

Anthony Walker
CIO, Midwest Integrated Health System

"Integration was seamless with our existing EHR..."

Unlike standalone AI tools, this solution was engineered into our workflow. No duplication, no extra dashboards — just embedded documentation where providers already work.

Robert Mitchell
Director of Healthcare IT, Evergreen Regional Health

WHY THINKITIVE?

Empowering Healthcare Technology Innovation

250+

Healthcare Projects

400+

Healthcare Experts

98%

Client Retention Rate

150+

Healthcare Customers

50%

Cost Saving on Development

What Would 2 Extra Hours Per Provider Mean for Your Practice?

Explore how embedded AI documentation can reduce documentation time, lower scribe dependency, and strengthen revenue workflows.

Frequently Asked Questions

Get answers to all your questions

Still have questions ?

The AI captures the full encounter audio during the visit but processes it to extract only clinically relevant information for documentation. Non-medical or casual conversation is filtered out, ensuring that generated notes remain focused, compliant, and appropriate for the medical record.

The system uses speaker diarization and voice recognition models trained for clinical environments. It identifies and separates speakers based on voice patterns and contextual cues, ensuring that statements are accurately attributed to the provider, patient, or additional participants during the encounter.

Yes, the AI can automatically generate structured documentation formats such as SOAP, HPI, ROS, and Physical Exam sections. It organizes extracted clinical content into standardized note structures aligned with specialty requirements and your organization’s documentation protocols.

On average, providers can save 1–2 hours per shift, depending on specialty and documentation volume. Real-time draft generation significantly reduces after-hours charting and minimizes the need for post-visit dictation or manual note completion.

Yes, all AI-generated notes go through a human-in-the-loop review process. Physicians can edit, refine, or approve documentation directly within the EHR before finalization, maintaining full clinical control and accountability.

The AI uses advanced speech recognition models trained on diverse accents and multilingual speech patterns commonly encountered in clinical settings. Continuous learning and contextual language modeling help improve transcription accuracy across varied patient populations.

Yes, the system can be deployed across multiple devices, including desktop workstations, tablets, and secure mobile configurations, depending on your infrastructure. This allows flexibility across exam rooms while maintaining secure EHR integration.

The AI can analyze documented assessments and suggest relevant ICD-10 codes for review. These suggestions support coding accuracy but remain subject to provider or coding team validation before submission.

Depending on the deployment architecture, the system can buffer audio locally and resume synchronization once connectivity is restored. Enterprise deployments can also include redundancy configurations to minimize workflow disruption.