Freed AI

The implementation of Freed AI typically involves several stages, designed to integrate the software smoothly into existing workflows while ensuring users can effectively leverage its AI capabilities. The process varies depending on the complexity of your business needs, the number of users, and whether you require custom configurations.

Steps:

• Assessment & Planning: Analyze business needs, define objectives, and determine key workflows to integrate with Freed AI.

• Account Setup & Configuration: Create user accounts, assign roles, and configure initial settings.

• Data Integration: Connect existing databases, CRM systems, or other relevant data sources to the software.

• Customization & Training: Tailor AI models and workflows to meet specific business requirements. Provide training sessions for staff to ensure smooth adoption.

• Testing & Validation: Run pilot programs or limited deployments to test performance, identify bugs, and refine processes.

• Full Deployment: Roll out the software across the organization with monitoring and support in place.

• Ongoing Optimization: Continuously review AI performance, gather user feedback, and update configurations as needed.

Typical Timeline:

• Small-scale deployment: 2–4 weeks
• Medium-scale deployment: 1–2 months
• Large-scale or highly customized deployment: 2–4 months

Freed AI is designed to be flexible, allowing businesses to tailor the platform to their unique operational requirements. Customization ensures the AI outputs are aligned with your business goals, workflows, and reporting standards.

Capabilities:

• Workflow Customization: Adjust AI workflows to match internal processes and task priorities.

• Model Tuning: Train AI models using your own data for more accurate and relevant outputs.

• User Roles & Permissions: Define access levels and functionality based on employee roles.

• Integration with Existing Tools: Connect Freed AI with CRMs, project management tools, and other business systems.

• Custom Reporting & Analytics: Create reports and dashboards tailored to your business KPIs.

While Freed AI’s pricing typically includes the base subscription, additional costs may arise depending on the scale of implementation, customization, and ongoing support requirements. Understanding these costs helps plan budgets effectively.

Potential Additional Costs:

• Setup Fees: Initial configuration, data migration, and integration costs.

• Training Costs: Optional or specialized training sessions for staff.

• Maintenance & Updates: Fees for premium updates, software patches, or extended system support.

• Support Charges: Costs for priority or dedicated support, especially for large organizations.

• Customization Fees: Charges for custom AI model training, workflow development, or specialized integrations.

Freed AI prioritizes user-friendly design and accessible support to ensure clinicians can quickly adopt the platform with minimal training.

Key Features:

• Intuitive Interface: Designed for ease of use, reducing the learning curve for new users.

• Onboarding Resources: Provides self-guided tutorials and documentation to help users get started.

• Customer Support: Offers responsive support channels to assist with any inquiries or issues.

• Community Engagement: Fosters a community where users can share experiences and tips.

Freed AI implements robust security protocols to protect sensitive patient information, ensuring compliance with healthcare regulations.

Security Protocols:

• HIPAA Compliance: Adheres to HIPAA standards to safeguard patient data.

• SOC 2 Type II Certification: Undergoes regular audits to maintain high security standards.

• Data Encryption: Utilizes TLS 1.2-1.3 encryption for data in transit and at rest.

• Data Residency: Stores data within the United States, specifically in Azure data centers in Arizona and Virginia.

Freed AI ensures the platform remains current and secure through regular updates and proactive maintenance.

Update Practices:

• Regular Updates: Releases updates to enhance features and address any issues.

• User Notifications: Informs users of upcoming updates and any necessary actions.

• Seamless Implementation: Implements updates without disrupting user workflows.

• Feedback Integration: Considers user feedback to guide future improvements.

Freed AI places a strong emphasis on user control and transparency regarding data ownership and portability. This approach ensures that healthcare providers maintain full autonomy over their data, aligning with best practices in data privacy and compliance.

Key Policies:

• Full Data Ownership: Clinicians and healthcare organizations retain complete ownership of their data within the platform. Each user operates within a secure workspace, ensuring that data remains under their control.

• Data Export and Deletion: Users have the ability to export or delete their data at any time, both during and after the contract period. This flexibility supports compliance with data retention policies and facilitates data management.

• De-Identification for AI Training: Freed AI does not utilize identifiable data for training its models. Instead, it employs strict de-identification and privacy protocols, ensuring that patient information remains confidential and is not shared externally.

• Compliance with Regulations: The platform adheres to HIPAA standards and other relevant data protection laws, providing users with confidence in the security and privacy of their data.

Freed AI offers flexible scaling options to accommodate the evolving needs of healthcare organizations. Whether expanding to include more users or adjusting to a smaller team, the platform's scalability ensures seamless transitions.

Key Terms:

• User-Based Pricing: The subscription model is typically based on the number of users, allowing organizations to scale up or down by adjusting their user count. This model provides cost efficiency and aligns expenses with actual usage.

• Flexible Subscription Plans: Freed AI offers various subscription tiers to cater to different organizational sizes and requirements. This flexibility enables organizations to select a plan that best fits their current needs and budget.

• Support for Growing Practices: As practices expand, Freed AI can accommodate additional users and integrate with existing Electronic Health Record (EHR) systems, facilitating smooth transitions and maintaining workflow continuity.

• Adaptability to Organizational Changes: The platform's design allows for easy adjustments in user roles and permissions, ensuring that as organizational structures change, Freed AI can adapt accordingly without disruption.

Freed AI offers flexible subscription management options, allowing users to adjust their plans as needed. Understanding the terms for renewal and cancellation ensures that organizations can manage their subscriptions effectively.

Key Terms:

• Auto-Renewal: Freed AI subscriptions automatically renew at the end of each billing cycle unless canceled by the user.

• Cancellation Process: Users can cancel their subscription at any time through their account billing page or by contacting support at support@getfreed.

• Service Continuation: Upon cancellation, users retain access to the service until the end of the current billing period.

• Refund Policy: Freed AI does not provide refunds for any prepaid portion of the subscription fee.

Freed AI is committed to maintaining high standards of security and privacy, ensuring compliance with relevant regulations to protect user data.

Compliance Highlights:

• HIPAA Compliance: Freed AI adheres to the Health Insurance Portability and Accountability Act (HIPAA), ensuring the protection of patient health information.

• SOC 2 Type II Certification: The platform has undergone rigorous audits and has been certified for its controls relevant to security, availability, and confidentiality.

• HITECH Act Compliance: Freed AI complies with the Health Information Technology for Economic and Clinical Health (HITECH) Act, promoting the adoption and meaningful use of health information technology.

• Data Encryption: Protected health information is encrypted both at rest and in transit using TLS 1.2-1.3 protocols.

• Data Residency: All data is stored within the United States, specifically in Microsoft Azure data centers located in Arizona and Virginia.