Patient messaging that works
Booking, rescheduling, reminders, and routine questions handled on WhatsApp in Arabic and English. Fewer no-shows, fewer phones ringing at reception.
AI implementation · Jeddah · Healthcare & Clinics
AI for clinics and healthcare in Jeddah.
Hephon is an AI agency in Dubai (Hephon L.L.C-FZ) that builds AI systems for clinics and healthcare providers in Jeddah. For a Jeddah clinic, the AI worth building first answers patients in Saudi dialect, Hijazi included, on WhatsApp: booking, intake and straight answers on cover and price, so an enquiry becomes an appointment. The insurance admin behind it is usually the second win. Clinical questions stay with clinicians. Fixed price after a short discovery.
Private healthcare in Jeddah serves a city where patients write the way they speak, in Hijazi Arabic with English mixed in, and where a large share of visits run through private insurance. Insurance in the Kingdom now moves through NPHIES, the national health-insurance exchange platform overseen by the Council of Health Insurance, which carries eligibility checks, prior authorisations and claims between providers and insurers. That digitised the plumbing, but the patient-facing questions (is my plan accepted, do I need approval, what will I pay) still land on the front desk, by phone and WhatsApp, often after hours.
We build the patient layer to answer those: booking, rescheduling and intake in the patient’s dialect, cover questions answered from the information your clinic maintains, reminders that cut no-shows, and a clean handover to your team for anything that needs a person or a live eligibility check. Health data is sensitive data under Saudi Arabia’s Personal Data Protection Law, enforced by SDAIA since September 2024, so where data is stored and what reaches a model are decided in the scope, not after launch. Saudi dialect at production scale is something we have shipped, inside the Panda app for one of the Kingdom’s largest retailers.
What we build for Healthcare & Clinics here.
Documents that draft themselves
Plans, reports, and follow-up summaries generated from your data and reviewed by your clinicians, not instead of them.
Decision support with an audit trail
For the calls that matter, multiple AI models weigh in, a referee model synthesizes, and every step is logged. Built for operators who answer to regulators.
100+
models, one answer. We built a panel-of-experts AI system for a multi-country healthcare operator, with a full audit trail of every decision. Our own clinic platform generates AI meal plans for under 2 cents each.
Questions
Will it understand Hijazi Arabic, not only Najdi or formal Arabic?
Yes. We build for how patients actually write, and Jeddah patients write in Hijazi dialect, often mixed with English. We test the assistant on real phrasing from your own enquiries before launch rather than on textbook Arabic.
Does it work with NPHIES?
The assistant does not submit claims or prior authorisations; that stays in your billing system and with your team. What it does is answer the patient-side questions around them from the information you maintain, and collect what your team needs before the visit, so the NPHIES steps start with complete details.
How do you handle patient data under the Saudi PDPL?
We scope it before building: what is stored, where it lives, who can reach it, and what is never sent to a model. Patient content does not train external models, and data-residency needs are part of the design. We are not your legal adviser, so we work to the position your compliance team sets.
Other industries in Jeddah.
Healthcare & Clinics AI in other markets.
See what we’d build for your business first.
The free AI audit maps your operations and shows the three systems we’d build first, in plain language, with a fixed price to start.