Argentina reenters the global conversation on digital health with a launch that directly targets the most sensitive—and most in-demand—aspect of modern healthcare: quick access to clinical guidance and medical documentation. This is RealMD, a beta-stage application that promises to provide an AI-supported “diagnosis,” but reviewed by real doctors before issuing an electronic prescription or ordering a test.
According to information shared about its operation, the proposal rests on a very specific idea: AI does not replace the doctor, but it can serve as the initial filter, the “triage” that quickly gathers symptoms, context, and medical history. From this conversation, a human professional steps in to validate the case and, if appropriate, formalize it as a prescription or instruction.
A flow designed to reduce friction
The process envisioned by RealMD is a hybrid system:
- The user begins a chat with an AI, describes their issue, and answers questions.
- The conversation is recorded as the basis of the case.
- A doctor reviews that exchange and decides whether to validate it, request more information, or refer for another type of care.
- If validated, the doctor issues an electronic prescription or orders a test.
In terms of timing, RealMD makes an aggressive promise for this type of service: deliver a prescription or order in about 15 minutes if doctors are available at that moment, or within a maximum of 12 hours when they are not. This component—the availability of connected doctors—is key, as it defines the real user experience: when “human coverage” is present, the app feels like an almost-instant response service; when not, it functions more like a clinical inbox with deferred validation.
The app also offers test interpretation, a feature that often attracts users who receive lab results or reports and need an understandable explanation before an in-person consultation or during times when the traditional system is slower.
The role of doctors: freelance, shift-based, with validation
One of the most distinctive elements of the model is how doctors are integrated. Instead of functioning as a fixed staff operating in traditional shifts, RealMD relies on freelance professionals who, during their free consultation times, review a case, check the prior chat with the AI, and, if they agree, turn it into a prescription or order. All of this happens via chat, though there is the possibility that, in some cases, the doctor may request a video consultation with the patient.
This approach has a clear technological interpretation: AI acts as an “assembly assistant,” preparing the case so that the clinician can invest clinical judgment rather than basic interrogation time. In theory, this could increase capacity—more cases reviewed per hour—and reduce the common bottleneck in telemedicine: waiting for initial guidance.
The legal aspect: where does the “medical act” start?
In healthcare, the product is not just the interface—it’s the responsibility. And in this regard, RealMD seems to have constructed a very explicit perimeter. According to the information shared about the service, in Argentina, responsibility falls on a specific entity (Flora Fertility Arg SAS). Furthermore, a framework of disclaimers is established: the AI the user interacts with is not considered medical advice; it can only be regarded as such when a real doctor takes over the case, assuming responsibility from that moment forward.
This distinction is important for two reasons. The first is regulatory: it makes AI a preliminary layer, not the prescriber. The second is reputational: it aims to prevent users from confusing a “plausible response” with a “clinical decision.” In practice, the success of such models depends on the user understanding this line: AI can provide guidance and structure, but medicine begins when human signature, human judgment, and human responsibility come into play.
Why are these kinds of apps appearing now
The idea attributed to founder Martín Varsavsky aligns with an increasingly common experience: consulting with a general chatbot and receiving a useful recommendation, but without the ability to turn it into a valid health document. That “leap”—from recommendation to prescription—is precisely the space where hybrid models emerge: AI to accelerate, doctors to validate.
In a context of strained health systems, saturated schedules, and users accustomed to instant responses, the promise of a prescription or order within minutes is compelling. But it also carries risks: it encourages using digital channels even when the case should be referred for in-person care. Thus, the true value of RealMD will be measured not only by speed but by the quality of its referral judgment: when to prescribe, when to ask for more data, when to request a video, and when to say “this isn’t the right path.”
Technological opportunity, operational challenge
RealMD’s approach sums up a clear direction for digital health: automation at the system entry point and human oversight in decision-making. It’s a formula that can scale better than traditional telemedicine if it achieves two things simultaneously: clinical consistency (ensuring different freelance doctors operate under comparable standards) and user trust (that the app isn’t perceived as “AI prescriptions,” but as “a doctor quickly validates what AI helped order”).
In this beta and free phase, the focus will be on the experience: real-time timings, quality of responses, flow safety, and clarity of responsibilities. If successful, RealMD could become a benchmark case in Latin America—not for “diagnosing with AI,” but for designing a practical bridge between automated conversation and formal medical acts.
Frequently Asked Questions
Does RealMD provide an automatic medical diagnosis, or does a doctor always intervene?
According to the described model, AI initiates the process, but the final validation and issuance of prescriptions or orders depend on a human doctor.
How long does it take for RealMD to issue an electronic prescription or test order?
It’s indicated to take about 15 minutes if doctors are available online, or up to 12 hours if they are not.
Can the app interpret analyses and medical reports?
Yes, it is presented as one of its functions: assisting in interpreting studies and results through AI flow plus human review.
Who assumes responsibility for the service in Argentina, and what is the role of AI?
Responsibility is claimed by Flora Fertility Arg SAS, and interactions with AI are not considered medical advice until a real doctor takes over and assumes responsibility.