Services · Artificial intelligence · Healthcare AI agents

Agents that run the front desk, not the diagnosis.

Q: How is patient data protected?

Data handling is designed around GDPR and the data protection law in each market and your own policies. Patient data stays in your cloud tenancy or an approved region, with encryption, role based access and full audit logs. We use model providers under terms that stop your data being used for training. Your data protection officer reviews the design before go live.

Q: What happens when the agent gets something wrong?

It will sometimes, so we design for that. Agents make mistakes, so anything with clinical or financial weight goes to a person for approval. Low confidence answers escalate automatically, every action is logged, and staff can correct the agent. We review errors with your team every week in the early months.

Q: Does it work with our hospital information system?

Usually, through the APIs or integration layer you already have. We connect to scheduling, EMR, pharmacy and billing systems through their supported interfaces, including HL7 and FHIR where available. Where a system has no API, we agree a safe alternative with your IT team. The agent only gets the access its task needs.

Q: Will this replace our reception or admin staff?

It removes repetitive work, not the people who look after patients. Staff move from answering the same questions to handling the cases that need judgement and care. They also supervise the agent and correct it. We involve them from scoping so the agent fits how they already work.

Q: Who signs off before patients use it?

Your clinical and compliance leads. We design the work around your regulatory obligations, but approval sits with your organisation. Your clinical governance and compliance teams review the scope, the evaluation results and the escalation rules before launch.

We build healthcare AI agents that take on booking, intake, reminders and paperwork for clinics, hospitals and pharmacies. They answer patients, prepare documents and draft notes for a clinician to check. They never diagnose, prescribe or give medical advice.

Every agent works inside your clinical governance, logs what it did and hands anything clinical to a qualified member of staff.

Get in touch All AI services

Built for: Clinic groups, hospitals and pharmacy chains whose front desk and admin teams are stretched by calls, forms and follow ups.
Typical timeline: A first agent, such as appointment booking, usually reaches a supervised pilot in eight to twelve weeks.
What you own: You own the prompts, workflows, integration code, evaluation sets and logs, deployed in your own cloud tenancy.
Rated: 4.7 / 5 from 23 Google reviews

200+ companies across the US and the UAEFrom a first store to a listed developer

What you get

The agents a healthcare provider actually puts to work.

Each agent has one job, a clear boundary and a person it hands over to. Most providers start with one or two and add more once the first is trusted by staff.

Explain your project

Appointment booking agent
Books, moves and cancels appointments over WhatsApp, web chat or phone, against live clinician calendars. It checks the right service, location and doctor before it confirms anything.
Patients book out of hours and reception spends less of the day on the phone.
Patient intake agent
Collects demographics, reason for visit, insurance details and consent forms before the patient arrives. Answers go into the patient record as structured fields for staff to verify.
Shorter queues at check in and fewer forms retyped by hand.
Reminder and follow up agent
Sends appointment reminders, preparation instructions and post visit follow ups that the clinic has approved. Replies such as a cancellation are handled and fed straight back into the schedule.
Fewer missed appointments, and empty slots are offered to other patients sooner.
Insurance pre-approval agent
Gathers the codes, notes and documents an insurer asks for and assembles the pre-approval request. A billing officer reviews and submits it, and the agent tracks the insurer's response.
Approval packs leave complete, so billing teams spend less time on rework and resubmissions.
Clinical note drafting agent
Turns a consultation recording or the clinician's shorthand into a draft note in your template. The clinician reads, edits and signs it, and nothing is filed without that sign off.
Doctors spend more of the appointment with the patient and less of it at the keyboard.
Patient FAQ agent
Answers questions on opening hours, services, preparation steps and what to bring, using content your team approves. Any symptom or clinical question is passed to a nurse or the right department.
Routine questions get an answer at once, and clinical ones reach a person.
Referral routing agent
Reads incoming referral letters, extracts the key details and routes each one to the right clinic list. It flags missing information so coordinators can chase it early.
Referrals stop waiting in a shared inbox before anyone looks at them.
Pharmacy refill agent
Takes repeat prescription requests, matches them to the patient record and queues them for a pharmacist to approve. It tells the patient when the order is ready to collect or out for delivery.
Pharmacists check and approve instead of answering status calls.

Who this is for

Where healthcare agents fit first.

The right starting point depends on where your staff lose the most time today.

Outpatient clinic groups

Multi branch clinics where reception handles bookings, reschedules and insurance questions for many doctors at once. One agent can take the routine load across every branch from a single set of rules.

Start with booking and reminders.

Hospitals

Hospital departments with referral backlogs, pre-approval paperwork and documentation pressure on clinicians. Agents sit behind existing systems and prepare work for staff to approve.

Start with pre-approvals and note drafting.

Pharmacies and pharmacy chains

Pharmacies fielding refill requests, stock questions and delivery updates by phone and WhatsApp. An agent queues requests for the pharmacist and keeps customers informed.

Start with refills and order updates.

How a healthcare agent goes from scoping to live use.

01ScopeWe sit with reception, billing and clinical leads to map one workflow, its risks and where a person must step in. Your compliance team agrees the boundaries in writing.
02BuildWe connect the agent to your scheduling, records and messaging systems through their APIs, with access limited to what the task needs. Clinical topics are blocked and routed to staff.
03EvaluateWe test the agent against an evaluation set of real, anonymised requests and difficult edge cases. Clinicians and your compliance team review the results before any patient sees it.
04SuperviseThe agent goes live with a small group first, with every conversation logged and reviewable. We tune it from what staff flag and widen use only when you are ready.

How we work together

Ways to work with us on healthcare AI.

Some providers want one agent built and handed over. Others want a team that builds, runs and improves several agents over time. We agree the model, the scope and the review points before any build starts.

Discovery and pilot

Teams deciding where AI should start

A short, fixed piece of work: the use cases ranked, the data checked, and one pilot built against real examples so you can judge it on evidence rather than a demo.

Use cases ranked by value and risk
Data and systems review
A working pilot on your own examples
A written plan for what comes next

Get in touch

Build and launch

A use case that is ready to go live

A written scope and a fixed quote, then the build: integrations, guardrails, an evaluation set and a launch with your team trained to use it.

Written scope and acceptance tests
Integration with your systems
Evaluation set and human review steps
Launch, training and handover

Get in touch

Run and improve

AI that is live and needs looking after

A monthly plan to watch quality, cost and usage, update prompts and models as vendors change them, and add the next use case when the first one earns it.

Quality and cost monitoring
Model and prompt updates
A monthly report on usage and results
The same team that built it

Get in touch

Technology

What we build this with.

Models are chosen per use case for quality, cost and where your data is allowed to go. The systems around them run on the stack below.

01Web

React
Next.js
TypeScript
Node.js
Laravel
WordPress

02Data and cloud

PostgreSQL
MySQL
MongoDB
AWS
Azure
Docker

Questions healthcare leaders ask us.

Will the agent ever diagnose or give medical advice?

No. It is built to decline and hand over.

The agent handles admin and information your team has approved. Any symptom, medication or clinical question is routed to a nurse, doctor or pharmacist. We test this boundary hard during evaluation and keep testing it after launch.

How is patient data protected?

What happens when the agent gets something wrong?

Does it work with our hospital information system?

Will this replace our reception or admin staff?

Who signs off before patients use it?

Services that usually go with this one.

AI agent developmentAgents that do real work, with a person signing off.AI security, risk and governanceUse AI with controls you can explain to an auditor.AI integrationAdd AI to the systems you already run.

Tell us what the business needs. We will tell you what to build first.

Schedule a free consultation and get a written recommendation, with costs, before you commit to anything.

Get in touch

PROVEN RESULTS

4.7 / 5from 23 Google reviews

Agents that run the front desk, not the diagnosis.

The agents a healthcare provider actually puts to work.

Appointment booking agent

Patient intake agent

Reminder and follow up agent

Insurance pre-approval agent

Clinical note drafting agent

Patient FAQ agent

Referral routing agent

Pharmacy refill agent

Where healthcare agents fit first.

Outpatient clinic groups

Hospitals

Pharmacies and pharmacy chains

How a healthcare agent goes from scoping to live use.

Ways to work with us on healthcare AI.

Discovery and pilot

Build and launch

Run and improve

What we build this with.

Questions healthcare leaders ask us.

Services that usually go with this one.

Tell us what the business needs. We will tell you what to build first.