What is Freed AI and who is it primarily designed for?
Freed AI is an intelligent ambient medical scribe and documentation assistant created specifically to alleviate administrative burnout for medical professionals. Unlike sprawling corporate AI tools built for massive hospital systems, Freed is purposefully engineered for solo clinicians, community care practitioners, physical therapists, and mental health professionals. It operates quietly on a mobile device, tablet, or desktop during a patient visit, listening to natural conversation and instantly distilling it into structured, healthcare-grade clinical text.
What specific tools are included in Freed's post-visit automation suite?
Beyond standard text summaries, Freed acts as a full-service documentation assistant to handle downstream clinical tasks right after an appointment:
AI Clinician Assistant: A natural-language editing copilot that allows users to issue prompt commands (e.g., "make the summary more concise" or "restructure the subjective section") to modify the text.
Visit Prep & Pre-Charting: Intelligently analyzes previous visit notes to surface quick patient history summaries and necessary follow-up tasks before the next appointment begins.
Coding & Documentation Generation: Instantly predicts accurate, billable ICD-10, CPT, and E/M codes based on the context of the live visit, while simultaneously drafting referral letters, school/work sick notes, and plain-language patient instruction sheets.
How does the platform handle EHR connectivity and "Learn My Format" training?
Freed is designed to adapt to the clinician's workflow rather than forcing them to adopt rigid software templates. Its Learn My Format feature allows a provider to copy and paste their personal historical notes, training the AI to mimic their exact stylistic shortcuts, preferred vocabulary, and shorthand structural habits over time. When notes are complete, a single click transmits the finalized documentation straight into standard Electronic Health Record (EHR) systems—such as Athena, eClinicalWorks, and SimplePractice.