India’s hospitals, clinics and diagnostic labs are entering a phase where software decisions matter as much as medical ones. With AI coming into the picture, healthcare might be going through a revolution.
AI adoption in healthcare remains modest across the country, with deployments largely in radiology-assisted diagnostics, administrative automation (documentation, scheduling, billing), and early EMR integration, as per a report by EY.
However, this transformation is gathering pace, according to Arjun Nagulapally, CTO at AIONOS, which calls itself a next-generation AI-first digital transformation company.
“I would not even say transformation, it’s going to be a revolution,” Nagulapally claimed in an exclusive interaction with AIM. He joined AIONOS a year ago to drive its product and technology strategy, and the company has since taken a focused bet on AI-driven industry products for travel, logistics, telecom and healthcare.
The CTO described AI as “the new programming language” that now defines how AIONOS builds all its products, across voice, text and vision models. The approach is simple, he said, to build domain-specific solutions that can later be reapplied across industries.
A Healthcare Sector Already in Flux
According to Nagulapally, Indian patients have changed more over the last five years than healthcare systems have in 15 years. Smartwatches, chat-based AI agents and always-on health alerts have already shifted patient behaviour. As he put it, “Patients are using information online to treat themselves,” a trend that bundles opportunities with risks.
He called radiology one of the first fields to feel AI disruption. AI is now fast enough to preprocess X-rays before radiologists step in, which has altered clinical workflows. Doctors, though, still expect technologies to work around them, not the other way round. “Doctors are the late adopters,” Nagulapally said, since medicine has never been a technology-first discipline.
Yet, an equally important shift is underway. Doctors now want systems that let them focus on patients rather than screens. This is where Nagulapally believes generative AI can create impact.
He said, “You really want to go and meet somebody because you know that specialist you’re talking to has skills to understand you better. AI is enabling that experience”. And, for a doctor, AI through ambient listening, automated insights and patient-centric interactions is helping improve the experience.
Some of the more surprising examples came from his earlier work in patient engagement apps. Many clinics still rely on images uploaded by patients, food photos, glucose meter displays or weight readings.
“If the person takes a picture where [AI] cannot understand a nine and a zero, it is going to make a mistake,” he recalled. The danger becomes clear when such misreads translate into medication choices.
Nagulapally highlighted an example where AI, getting confused between a nine and a zero, going through a pharmacy prescription, would recommend 90 milligrams instead of 9 milligrams, resulting in overdose. Those are critical mistakes that AI can technically make today.
This, he believes, is exactly why healthcare requires guardrails, judgement and traceability.
AI With Guardrails, Not Blind Trust
Nagulapally argued that customers today want to know what AI vendors are doing to mitigate failure. His answer is the IntelliMate platform, which sits at the heart of all AIONOS deployments. It records every agent action, decision and data source. The company highlights that it focuses on driving business outcomes instead of just performing tasks.
“Every suggestion and action has complete traceability from action to data,” he explained.
If an AI agent steps outside defined bounds, the system triggers a human in the loop. “We invoke a human whenever something looks out of range. A notification goes out immediately,” Nagulapally said, adding that the intention is to build confidence, not full autonomy.
Although the platform is proprietary, AIONOS does not tie itself to any single model family. Nagulapally confirmed that the company fine tunes open-source models like Llama, Falcon and Mistral while also working with OpenAI, Gemini and Grok. “We are an application company,” he said, which means AI choices depend entirely on the use case.
Some of AIONOS’ healthcare work is already visible in diagnostic labs, where the company helps explain blood reports in simple English or regional languages. Instead of looking at raw values and ranges, patients receive natural language interpretations like whether a value is normal or needs follow-up. The aim is to reduce anxiety and improve early action.
On the business side, IntelliMate offers hospitals a single view of all their AI agents. From utilisation to cost and containment metrics, the platform works as a dashboard for AI workforce planning. “You do not have HR to monitor an agent,” Nagulapally noted. The system allows hospitals to decide which activities belong to humans, and which can be shifted to AI agents over time.
Personalised AI to be the future
Nagulapally believes the adoption curve for healthcare AI in India will steepen sharply in the next three years. He expects “much more personalised healthcare, new drugs invented, better access and better quality of life” as AI matures across drug discovery, hospital operations and patient-doctor interactions.
AIONOS plans to expand its footprint through two pricing models, either value-based (cost per agent outcome) or usage-based (minutes consumed), depending on the client.
Across the conversation, one thing stayed constant. AI, for him, is not here to replace the doctor. It is here to make every part of the system more aware, more responsive and more personalised than before.
The post How AIONOS Wants to Rewrite Healthcare AI, One Agent at a Time appeared first on Analytics India Magazine.
