getfreed.ai

Freed is an AI platform for independent medical clinics, built around two products: an AI medical scribe for clinicians and an AI Front Desk for reception and communications. It turns patient conversations into clinical notes, suggests billing codes, answers clinical questions with cited sources, and handles incoming calls — with the stated goal of reducing documentation time and clinician burnout. It is aimed at independent practices rather than large health systems, and pricing starts at $39/mo for the scribe and $149/mo for Front Desk.

The two halves of the platform

Freed splits its offering by who uses it:

Both are positioned as tools that "give time back to independent clinics," covering the span from the first patient call to the last clinical note.

What the AI Scribe does

The scribe is the more feature-dense side of the product. Its components:

• Ambient note-taking — converts patient conversations into accurate, customized notes that can sync to your EHR, with the aim of saving hours per week.
• Clinical Evidence — you can ask any clinical question and get answers cited from 50+ trusted sources, tailored to the patient in front of you.
• Coding Assistant — suggests ICD-10, CPT, and E/M codes at the highest justified E/M level, embedded directly in the scribe workflow, framed as a way to reclaim revenue.
• EHR integration — pushes notes to top browser-based EHRs, and the site claims it works across any EHR.

What the Front Desk does

Front Desk is an AI receptionist and communications platform. It answers calls when your team can't — during lunch, after hours, or for call overflow — so the practice doesn't miss patient contact outside staffed hours.

Who it's for

Freed explicitly targets independent and community practices, not massive healthcare systems. The site states this is deliberate: "We're not made for massive healthcare systems. Freed is built to bring focus back to community care, one local clinic at a time."

Within a practice, it's designed to serve the whole care team — clinicians, front desk staff, and practice management — across all four modules.

Accuracy, setup, and support claims

• Clinical accuracy: 98% recall on medical terms across 30+ specialties, tested against thousands of clinical concepts. Freed says it is "continually selected over competitors for high note quality."
• Setup speed: adapts to a clinic's workflows "in minutes, not months" — you can update templates, summarize context, and build a clinic knowledge base in one app.
• Support: US-based, with live human support via scheduled calls, live office hours, or pre-recorded walkthroughs.
• Adoption: the site reports it is "loved by 26k+ clinicians."

Pricing at a glance

• AI Scribe: affordable plans starting at $39/mo
• Front Desk: affordable plans starting at $149/mo

Both products offer a free trial ("Try for Free"), and there's a separate contact-sales path for practices that want to talk to someone first.

How to decide if it fits

Freed is worth a closer look if you run or work in an independent clinic and your main pain is documentation load — late-night charting, coding accuracy, or missed calls. The combination of scribe, cited clinical evidence, coding suggestions, and a receptionist in one stack is unusual for a single vendor.

It's likely a poor fit if you're part of a large health system with its own enterprise tooling, or if you only need one narrow function (for example, just an answering service) rather than an integrated clinical workflow.

The practical next step is to start a free trial of the AI Scribe, run it against your own templates and EHR, and check note quality on your specialty before committing — the accuracy claim is specialty-dependent, so your own notes are the real test.

Freed's Coding Assistant generates ICD-10, CPT, and E/M code suggestions inside the same workflow where the AI scribe produces clinical notes, and it recommends codes at the highest justified E/M level. It is built for independent practices rather than large health systems, and it sits alongside the scribe, Clinical Evidence, and Front Desk products on getfreed.ai. If you are evaluating whether it fits your clinic, the deciding factors are usually how much of your coding you still do by hand and whether you want coding handled at the point of documentation rather than in a separate review step.

What the Coding Assistant actually produces

According to the product page, the Coding Assistant covers three code families:

• ICD-10 — diagnosis codes
• CPT — procedure codes
• E/M — evaluation and management codes, suggested "at the highest justified E/M level"

The phrase "highest justified" is the important qualifier. The tool is described as recommending the top E/M level that the documentation supports, not the top level available. That distinction matters because upcoding beyond what the note supports is a compliance problem, not a revenue strategy.

Where it sits in the workflow

The Coding Assistant is described as "embedded in your scribe workflow." In practice that means the sequence runs:

1. The ambient scribe captures the patient conversation.
2. It turns that conversation into a customized note.
3. Coding suggestions appear as part of that same documentation flow, rather than in a separate coding module you open afterward.
4. The note can then be pushed to a browser-based EHR.

The stated goal is that you are not re-reading the encounter later to assign codes — the codes are proposed while the encounter is still fresh and the note is being finalized.

What problem it is meant to solve

The page frames the Coding Assistant around revenue: "Reclaim revenue with ICD-10 and CPT coding suggestions." Two mechanisms are implied:

• Missed codes — codes that should have been billed but were not captured.
• Level selection — E/M visits billed below the level the documentation justifies.

Both are common sources of leakage in independent clinics, where the same person often documents and codes. The assistant is positioned as a way to close that gap without adding a separate coding hire.

How it fits with the rest of Freed

Freed's broader pitch is that it is "made for independent practices" and not for "massive healthcare systems." The Coding Assistant is one of four named capabilities:

The company reports 98% recall on medical terms across 30+ specialties and says it is used by 26,000+ clinicians. Those figures describe the scribe's accuracy generally; the page does not break out a separate accuracy number for coding specifically.

What to check before relying on it

• Who signs off on codes. The page describes suggestions, not autonomous submission. Confirm your own review step and who owns final code selection.
• EHR compatibility. Integration is described as pushing to "top browser-based EHRs." If your EHR is not browser-based, verify support before assuming it works.
• Your payer mix and specialty. Coding rules vary by payer and specialty. Test the suggestions against a sample of your own encounters rather than trusting a general accuracy claim.
• Pricing tier. The page lists AI Scribe plans starting at $39/mo, but it does not state whether the Coding Assistant is included at that tier or requires a different plan. Check the pricing page or ask sales directly.

The practical takeaway

Freed's Coding Assistant is a documentation-adjacent coding tool: it proposes ICD-10, CPT, and E/M codes at the highest level the note justifies, inside the scribe workflow, aimed at independent clinics that want to stop leaving revenue on the table. It is a suggestion layer, not a replacement for your coding judgment — so the right way to evaluate it is to run a set of your own recent encounters through it and compare its codes against what you actually billed.

Freed is an ambient AI scribe that listens to a patient visit and converts the conversation into a customized clinical note, then pushes that note into a browser-based EHR. It is built for independent practices rather than large health systems, and the site reports 98% recall on medical terms across 30+ specialties. If your clinic uses a browser-based EHR and you want notes generated during or right after the visit, this is the workflow Freed is designed for.

The core mechanism: ambient capture, then structured output

Freed works as an "ambient" scribe, meaning it captures the visit conversation rather than requiring you to dictate or type. The site describes the output as "accurate and customized notes that can sync your EHR." The customization matters: a note template for a primary care visit differs from one for a specialty consult, and Freed lets you update templates and summarize context so the note matches your clinic's format.

The pipeline, in plain terms:

1. Capture — the visit conversation is recorded ambiently.
2. Transcribe and interpret — the system converts speech to text and identifies medical terms, which is where the reported 98% recall on medical terms across 30+ specialties applies.
3. Structure into a note — the content is organized into your template rather than a raw transcript.
4. Sync — the finished note pushes to a top browser-based EHR.

What "customized" actually means for a clinic

Freed's site says it "flexes to fit your clinic's workflows in minutes, not months," and that you can update templates, summarize context, and build a clinic knowledge base in one app. Practically, that means:

• Templates — you define the note structure your practice already uses, so the output fits existing documentation habits.
• Context summarization — the system can condense relevant history or visit context rather than dumping everything.
• Clinic knowledge base — reusable clinic-specific information that shapes how notes are produced.

The claim to test during a trial is whether your specific specialty's terminology and note format survive this process without heavy editing. The 98% figure is a vendor-reported benchmark against "thousands of clinical concepts," so treat it as a starting expectation, not a guarantee for your patient mix.

Beyond the note: coding and clinical evidence

Freed bundles two features that sit next to the scribe workflow:

If your main pain point is note-writing alone, the scribe is the core. If you also lose time on coding or looking up evidence mid-visit, those two features are the reason to evaluate Freed as a bundle rather than a single-purpose scribe.

Who this fits — and who it doesn't

Freed states plainly that it is "not made for massive healthcare systems" and is "built to bring focus back to community care." The site reports it is "loved by 26k+ clinicians" and "continually selected over competitors for high note quality."

Choose Freed if:

• You run an independent or community clinic.
• Your EHR is browser-based (the site specifies "top browser-based EHRs" for sync).
• You want scribe, coding, and cited evidence in one workflow.
• You value US-based live human support — the site offers scheduled calls, live office hours, and pre-recorded walkthroughs.

Look elsewhere if:

• You are part of a large health system with non-browser EHR infrastructure.
• You need only transcription with no note structuring or coding.

Pricing and how to start

The site lists AI Scribe plans starting at $39/mo and Front Desk plans starting at $149/mo. Front Desk is a separate product — an AI receptionist that answers calls during lunch, after-hours, or for overflow — so don't assume the $39 figure covers it.

To evaluate the scribe specifically:

1. Go to the pricing page to confirm the current plan that matches your clinician count.
2. Start the free trial the site offers ("Try for Free").
3. Run it on real visits in your specialty for a few days.
4. Compare generated notes against your existing templates and count how many edits you make per note.
5. Test the EHR sync with your actual browser-based system before committing.

The decision hinges on one measurable thing: how many edits per note you make after the trial period. If that number is near zero in your specialty, the workflow is doing its job.

Freed's Front Desk is an AI receptionist and communications platform built for independent clinics. It answers patient calls when your staff can't — during lunch, after-hours, or when call volume overflows — so the practice doesn't miss inquiries just because no one is at the desk. It's sold as a separate product from Freed's AI Scribe, with plans starting at $149/mo, and is designed to work alongside the clinical tools rather than replace them.

What Front Desk actually does

The core job is call coverage. According to Freed's site, the AI receptionist "answers calls when they can't — during lunch, after-hours, or for overflow." That framing matters: Front Desk isn't positioned as a full replacement for your front desk staff, but as a backstop for the gaps where calls would otherwise go unanswered or roll to voicemail.

Freed describes it as an "AI receptionist and comms platform," so it covers both answering calls and handling front-desk communication more broadly. The site does not detail specific call-routing rules, scheduling integrations, or message-taking workflows, so treat those as things to confirm directly with Freed before assuming they're included.

Who it's built for

Freed is explicit that it targets independent practices, not large health systems: "We're not made for massive healthcare systems. Freed is built to bring focus back to community care, one local clinic at a time." If you run a small or mid-sized independent clinic, you're the intended user. If you're part of a large hospital network, this product line isn't aimed at you.

The broader pitch is that Freed serves the whole care team — clinicians, front desk staff, and practice management — across four products:

Front Desk is the piece that sits before the clinical encounter — handling the first patient contact so the rest of the workflow can run.

Pricing and how it fits with the scribe

Freed lists Front Desk plans starting at $149/mo, separate from the AI Scribe plans starting at $39/mo. The two are distinct products with separate login paths ("Log in to AI scribe" and "Log in to front desk"), so a clinic can adopt one without the other. The site presents them as complementary: Front Desk covers incoming calls, while the scribe covers documentation once the patient is in front of you.

What to verify before committing

Freed's page doesn't specify how calls are routed, whether the AI can book appointments, how messages reach your staff, or what happens with complex or clinical calls. Those are the practical questions that determine fit for a given clinic. Before signing up, ask Freed directly:

• How does the AI decide what to handle versus escalate to a human?
• Does it integrate with your scheduling or phone system?
• What does a call summary or handoff look like for your front desk team?
• What's included at the $149/mo starting tier versus higher plans?

Freed does offer a free trial and US-based live human support (calls, office hours, and recorded walkthroughs), which gives you a low-risk way to test call handling against your actual volume before committing.

Freed's Clinical Evidence feature lets a clinician ask a clinical question in plain language and get back an answer that cites its sources — drawn from 50+ trusted sources — and is sharpened to the patient in front of them. It sits inside the same workflow as the AI scribe, so the question can be asked without leaving the note-taking context. The description below reflects what Freed states on its site; it does not cover pricing tiers, which sources are included, or how citations are formatted, since those details aren't published in the available material.

What the feature does

According to Freed's site, Clinical Evidence works in three connected steps:

• Ask any clinical question. The clinician poses a question directly, rather than searching a database manually.
• Get cited answers from 50+ trusted sources. Each answer is backed by references, so the basis for the answer can be checked rather than taken on faith.
• Answers are sharpened to the patient in front of you. The response is framed around the specific patient context, not a generic textbook answer.

Freed positions this alongside two other clinician-facing tools — the AI Scribe (visit prep and note generation) and the Coding Assistant (ICD-10, CPT, and E/M code suggestions) — as part of one workflow rather than a separate lookup product.

Why the "cited" part matters

A cited answer is useful because it separates two things that are easy to blur together:

1. The answer itself — what the tool suggests.
2. The evidence behind it — where that suggestion comes from.

For a clinician, the second is what makes the first checkable. If an answer doesn't match your own reading of the literature or the patient's situation, the citation is the point where you can verify, disagree, or dig further. Freed's claim is that answers come from 50+ trusted sources; the site does not list them, so treat "trusted" as Freed's characterization until you confirm the specific sources yourself.

Where it fits in the workflow

Freed describes Clinical Evidence as embedded in the scribe workflow, not a standalone research tool. In practice that means the sequence looks like this:

• A patient conversation is captured by the AI Scribe.
• A clinical question comes up — during visit prep, while reviewing the encounter, or while drafting the note.
• The question is asked in the same environment, and the cited answer comes back tied to that patient's context.

The intended benefit is avoiding a context switch: no separate tab, no re-entering patient details into a search box. Freed frames the overall product around reducing documentation burden for independent clinics, and Clinical Evidence is one of the pieces meant to serve that goal.

What to verify before relying on it

Because the public material is thin on specifics, confirm these directly with Freed or in a trial:

Who this is for

Freed states it is built for independent practices rather than large healthcare systems, and says it is used by 26k+ clinicians. If you work in a small or independent clinic and want cited clinical answers available at the point of documentation, this feature is aimed at you. If you need a full evidence-review tool with transparent, auditable source lists, treat Freed's Clinical Evidence as a workflow convenience and verify the sourcing before depending on it for decisions.

The practical next step is a trial: ask a question you already know the answer to, check whether the citation matches, and see whether the patient-specific framing is useful or noise. That tells you more than any feature list.