Maulana Azad Institute of Dental Sciences is not a dental clinic. It is one of India's premier government dental teaching hospitals — and it operates at a scale that demands a different kind of thinking about everything, including technology.
Over 1,000 patients walk through its doors every single day.
The dental wing spans multiple departments - Oral Medicine, Comprehensive Dentistry, Paediatric Dentistry, Public Health Dentistry, and more. Every patient interaction is simultaneously a clinical service and a teaching exercise. Every examination is a learning moment. Every case is a classroom.
Dr. Gyanendra has led the Department of Paediatric Dentistry here for years. When three scanO devices arrived at MAIDS, he was watching closely, not to see whether they would increase patient numbers, but whether they would help his department serve better within the capacity it already had.
MAIDS already has 1,000 patients a day. The challenge was never footfall.
The challenge was time. Specifically, how to use it better.
Every patient at MAIDS follows the same journey. They register at reception. They walk to the relevant department, in many cases, Oral Medicine first, where a full case history is taken and a clinical examination is done. They wait. They see a student. A faculty member supervises. A referral may follow.
At every stage, time is the rarest resource. And running through all of it is a tension unique to teaching hospitals: every patient interaction must serve two purposes simultaneously - the patient's health, and the student's education. You cannot rush one without compromising the other.
This is the environment scanO entered at MAIDS.
Three devices. Two primary deployment points.
Two machines in the Oral Medicine department. One in Comprehensive Dentistry. All three placed as waiting-time tools, patients are directed to scan while waiting, before their clinical examination begins.
The integration was deliberate in its simplicity. Making scanning mandatory for all 1,000 daily patients would be operationally impossible. Instead, the devices became structured engagement tools during dead time, the minutes between registration and examination, between arriving and being seen.
A patient who has already seen their oral condition on a screen, already processed what the AI found, that patient arrives at the dental chair in a different state than one who has been sitting in silence. The scan does not replace the clinical examination at MAIDS. It precedes it and changes the nature of it.
At MAIDS, students present cases to faculty. The student examines the patient, documents findings, formulates a diagnosis, and brings that assessment to a faculty member for review before treatment proceeds. This process is repeated dozens of times a day, this is where much of the time is consumed.
The scanO report quietly changes the dynamic of that exchange.
When a student presents a case and the faculty can cross-reference AI findings against the student's clinical assessment, something educationally significant happens. Conditions the student was uncertain about are confirmed. Conditions missed are flagged. The AI doesn't replace faculty judgement, it gives both student and faculty a shared, objective reference point for the conversation.
At approximately 75% correlation between AI findings and clinical examination findings, the tool is not infallible, and Dr. Gyanendra is clear-eyed about that. But in a teaching environment, that number is not a limitation. It is a teaching opportunity. The cases where the AI and the student diverge become some of the most instructive clinical discussions of the day.
At MAIDS, the goal is not to get patients in and out faster. The goal is to use the time that already exists, the waiting time, more productively.
What the scan does is convert passive waiting into active engagement. A patient who spends 15 minutes with the device, seeing their findings, reading about their condition, that patient arrives at the chair already informed. For faculty, this means less time spent on explaining obvious findings and more time spent on clinical nuance and the teaching conversation that actually develops a dentist.
Many patients at MAIDS are first-generation dental visitors from low-income households, with conditions they have never been told about because they have never seen a dentist before. They are often reluctant to accept treatment, even heavily subsidised treatment, because they don't understand why it is necessary.
For a patient who cannot feel their calculus, verbal explanations of why scaling matters fall on uncertain ground. The trust gap between an educated clinician and an underserved patient is real.
The scan bridges it visually.
At a government hospital where subsidised treatment still requires the patient's cooperation, time, and return visits, that acceptance improvement is not a commercial metric. It is a public health outcome.
At around 75% correlation with clinical examination findings, the devices are functioning appropriately for this context. For conditions like malalignment, calculus, and soft tissue findings, correlation is strong. For specialised cases requiring radiographic investigation - skeletal relationships, CBCTs, OPGs , the AI is not the tool, and Dr. Gyanendra never expected it to be.
What it does well is the large majority of OPD cases, the conditions that a well-trained student should catch, and that the AI catches consistently. It provides a quality floor, not a diagnostic ceiling.
The Public Health Dentistry department at MAIDS runs approximately 120 dental camps per year — roughly 6 camps per week, reaching schools, communities, underserved localities, and government facilities across Delhi. At each camp, mass screening is a core activity.
scanO has not yet been deployed at these camps, but Dr. Gyanendra sees an immediate, specific opportunity that he described with conviction.
At a mass screening camp, the constraints are real: limited faculty, no clinic infrastructure, and sterilisation cycles that create operational bottlenecks when instrument-based examination is the only tool available. scanO is camera-based and entirely non-invasive, no instruments enter the mouth, no sterilisation cycle is triggered per patient.
And with the scanO Engage app running on faculty mobile devices, the entire screening capability travels with the team. No device to transport. No setup required beyond a phone.
"The manual labour will definitely reduce - because the patient doesn't need an instrument-based examination for initial screening."
Delhi's public health patient population has significant tobacco and smoking prevalence. Oral cancer and precancerous lesions are not rare findings in the communities that MAIDS camp programmes serve, and they are almost always caught too late.
Dr. Gyanendra was unambiguous on this point.
The scanO Engage app's Tissue AI feature screens 13 soft tissue surfaces - buccal mucosa, labial mucosa, surfaces of the tongue, hard palate, floor of the mouth and generates a probability-scored report flagging precancerous and cancerous lesion possibilities, with confidence scores that segregate findings clearly.
For a department running 120 camps a year in communities where oral cancer is caught late, often fatally late, because there is no systematic early screening at the community level, this is not a software feature. It is a clinical intervention with life-saving potential.
Dr. Gyanendra had one specific product request that reflects the depth of how MAIDS has engaged with the scanO ecosystem:
Radiograph integration within the Engage application.
In a teaching hospital, radiographic data is central to diagnosis. OPGs, CBCTs, and periapical X-rays are taken daily across departments. The ability to upload these into the scanO Engage platform and receive AI-assisted analysis of anatomical landmarks and pathological findings would complete the clinical picture that scanO currently provides for visible hard and soft tissue conditions.
This feature is already on the scanO roadmap and Dr. Gyanendra is expecting it within the year.
"If another government dental college is considering scanO - integrate it. The device works. The students use it. The patients respond to it. And for public health and camp screening, the Tissue AI on the Engage app alone justifies the entire deployment."
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