Custom healthcare software development
Web, mobile, and enterprise clinical applications built from the ground up for medical data protection, clinical ergonomics, and scalability.
Healthcare products carry obligations ordinary products do not
General teams scope the visible features. In healthcare the invisible ones decide the outcome: permissions, consent, behaviour when an integration drops, and what an auditor asks for two years later. Cheap to design in, expensive to retrofit.
What we build
Product discovery
Working out what the first version needs to do, who uses it, what it connects to, and what can wait.
Patient applications
Web and mobile applications for booking, intake, results, messaging, education and follow-up.
Clinician and staff applications
Tools for care teams, coordinators and administrators, designed around the process rather than around the database.
Platform and backend engineering
Services, APIs, authentication, permissions and the data model, sized for the volume the product will reach rather than the volume it starts with.
Cloud infrastructure
Environments, deployment, monitoring and cost control on AWS, Azure or Google Cloud.
Modernisation
Moving an existing healthcare system onto current infrastructure without interrupting the service or losing its integrations.
Quality assurance
Functional testing, automated regression, security testing, and testing against the real process with real users.
Ongoing engineering
New features, performance work, dependency and security updates, and support after launch.
AI integration
Adding AI capability to a product you already run, without rebuilding what works.
Applications we have built
Two or three real product screens carry more weight here than any capability list.
What this looks like in practice
| Product type | What it involves |
|---|---|
| Patient portal | Identity and access, record display, appointment booking, secure messaging, document access, EHR integration |
| Care coordination tool | Task assignment, care plans, handover between teams, notifications, a record of who did what |
| Clinical operations platform | Scheduling, capacity, reporting, role-based permissions, integration with existing administrative systems |
| Device companion application | Pairing, data display, alerts, account management, synchronisation with a device platform |
| Digital therapeutic | Content delivery, adherence tracking, outcome measures, a clinician oversight view |
How a product takes shape
Each stage ends with something usable: an agreed scope, a clickable prototype, a working product in front of pilot users, a live service, then continued development. Clients join at whichever stage matches where they are.
Discovery
The process, the users, the constraints and what the first version needs to do.
Prototype
Something clickable to put in front of users and investors before the build starts.
MVP
A working product your pilot customers can actually use, with the groundwork done properly.
Production
Security review, monitoring, documentation and the arrangements to run it.
Scale
The architecture work that volume, new customers and new integrations actually require.
Design and delivery
Technology
| Group | Typical technologies |
|---|---|
| Frontend | React, Next.js, TypeScript |
| Mobile | React Native, Swift, Kotlin |
| Backend | Node.js, Python, Java |
| Databases | PostgreSQL, MongoDB, time-series stores for device data |
| Cloud | AWS, Azure, Google Cloud |
| Interoperability | HL7, FHIR, REST APIs, SMART on FHIR where relevant |
The list is indicative. Choices follow the requirement, the team who will maintain the product, and the environment it has to run in.
Frequently asked questions
It depends mainly on the number of integrations, the sensitivity of the data and the number of user types. A single-purpose application with one integration is a very different piece of work from a platform serving patients, clinicians and administrators across several clinical systems. We give a range after discovery rather than a figure before it.
Yes. A common arrangement is that we take a defined area such as the device layer, the data services or an AI feature while your team continues on the core product. Interfaces and ownership are agreed at the start.
Yes, after a technical review. We look at the current state, test coverage, dependencies and infrastructure, then set out what can be improved incrementally and what would be better replaced.
You do. Ownership transfers under the contract, and the repository, infrastructure and documentation are handed over so another team could take the work on.
Development and testing use synthetic or de-identified data. Access to any environment holding real patient data is restricted, logged, and agreed with you in writing before it is granted.
Tell us about the product you are building
Bring the process, the users and the systems it has to work with. We will tell you what is realistic before anyone writes a proposal.