Mulk Technology and OnClarity Link Hospital Operations Into One AI Platform
Mulk Technology has launched an AI-powered digital healthcare platform for India and international markets after a strategic partnership with OnClarity USA was signed in Dubai on 23 October 2026. The rollout joins hospital management, patient communication, billing, claims, telehealth and ABDM-linked workflows inside a single environment designed to reduce the friction that often slows care delivery after the clinical decision has already been made.
A hospital can deliver excellent treatment and still lose money, time and patient trust when information sits in separate systems. Registration, electronic medical records, laboratory reports, radiology studies, pharmacy dispensing, billing and insurance claims often move through disconnected software, creating gaps that can delay discharge, trigger claim rejections or leave patients waiting for answers. This platform is built around the premise that the administrative layer of care should move as continuously as the clinical one.
A Single Database for Clinical, Financial and Patient-Facing Workflows
The integrated system combines patient registration, electronic medical records, laboratory services, radiology, pharmacy, billing, insurance claims, telehealth and a patient application on one database. Clinical orders, bed-days and consumables can be tied directly to billing, while clinical documentation feeds into the claims process. In practical terms, that kind of linkage reduces the need for repeated data entry and lowers the chance that a service delivered at the bedside never makes it into the final invoice or payer submission.
The platform includes 22 AI-enabled modules along with ABDM compliance features and hospital management tools for hospitals, clinics, laboratories and imaging centres. Facilities can adopt the full stack or integrate the AI functions with existing systems, a structure that may appeal to institutions that are already invested in legacy software but still want stronger automation around revenue cycle management and patient engagement.
Claims Workflows Aim to Reduce Rejections and Administrative Drift
The claims engine is one of the most consequential parts of the launch. AI-enabled tools support claim preparation, validation and review, while staff remain responsible for checking and approving the final submission. The system can reconcile procedures, diagnostic tests, bed-days and consumables against bills before discharge, then recommend medical codes with supporting documentation, identify missing information, validate claims against payer rules and pre-authorisation requirements, and flag potential duplicate claims.
Hospitals know how much revenue can disappear in small administrative failures. A missing code, an unlinked diagnostic order or an unresolved authorization mismatch can turn a completed admission into a denied payment and a longer appeals cycle. By surfacing those problems before discharge, the platform tries to move claims work upstream, where it is less expensive to fix and less disruptive to patients and staff.
Work queues can also be prioritised based on claim value, likelihood of approval and deadlines, which gives revenue teams a way to focus limited attention on submissions most likely to affect cash flow. Rejected claims can be reviewed and resubmitted inside the same system, reducing the number of places where a denied file can stall.
Patient Communication Extends Across Languages and Channels
On the patient side, OnClarity USA’s AI tools support communication through WhatsApp, voice calls, SMS, web chat and mobile applications. The support system is designed to operate around the clock in more than 40 languages, with functions that include appointment booking, reminders and query routing. In a country as linguistically diverse as India, multilingual access is not a cosmetic feature; it is the difference between a patient completing a visit and a patient dropping out somewhere between scheduling and follow-up.
An agent-assistance tool gives staff access to patient history and policy-related information during interactions. The Voice of the Patient system reviews calls, chats, surveys and online feedback to identify recurring concerns, which can help providers see where operational breakdowns are accumulating. If a large share of complaints cluster around a single step, whether scheduling, billing or post-visit follow-up, the data can expose a process problem faster than anecdotal review alone.
Telehealth Kiosks and Preventive Care Expand the Model Beyond the Hospital Walls
The platform also includes telehealth kiosks that hospitals can deploy under their own brands at offices, pharmacies and shopping malls. Those kiosks enable video consultations with hospital doctors and on-site medicine dispensing, extending access beyond the conventional outpatient department. For systems struggling with congestion, this model may offer a lower-friction entry point for routine consults, triage and medication pickup.
Its AI Longevity Module is designed to expand laboratory testing into a physician-led preventive home-care programme. While the launch materials do not describe outcome data, the model reflects a familiar shift in digital health: moving from episodic encounters toward ongoing monitoring, earlier identification of risk and closer follow-up between visits. Preventive care becomes easier to operationalize when the software can track the patient across settings rather than forcing every interaction to begin from zero.
ABDM Compatibility Places the Platform Inside India’s Digital Health Framework
The platform supports the Ayushman Bharat Digital Mission, including ABHA creation during registration and consent-based health record sharing across ABDM-linked facilities. Compatibility with the national digital health stack is a major practical feature because it determines whether the system can operate as a standalone product or as part of the broader public infrastructure for health record exchange.
Cloud-based subscription pricing may also lower the barrier for adoption, particularly for facilities that want to scale digital functions without building their own technical architecture from scratch. The same model could suit large hospitals, smaller clinics, diagnostic laboratories and imaging centres, though implementation will likely depend on local workflows, staff training and how smoothly the new platform can sit alongside existing hospital information systems.
Dr Nawab Shafi Ul Mulk, founder of Mulk Technology, said the partnership is intended to support the expansion of AI-enabled healthcare across multiple markets. He pointed to telehealth delivery to more than 1.5 million insurance members in the UAE and in Africa through the DR Congo, while saying the company is in the final stages of implementation in India and has signed an MOU with the Maldives.
Abed Kasaji, co-founder and CEO of OnClarity USA, framed the problem as fragmentation rather than a shortage of software. Hospitals, in that view, do not lack tools; they lack continuity. A platform that follows the patient from the first call to the final claim may reduce the handoff failures that have long separated clinical care from the systems meant to support it.
Even so, the launch remains a platform announcement rather than a clinical validation study. The real test will be whether hospitals using the system can document fewer claim denials, faster throughput, better patient response times and smoother ABDM-linked workflows once the software is embedded into live operations.