Healthcare

Move fast is fine. Break things is not

Healthcare software carries consequences most products do not: a wrong record, an exposed identifier, or a workflow that adds three clicks to a clinician's day. The speed is still available, the guardrails just have to be real rather than stated.

8+
Years building software
500+
Projects delivered
350+
Clients served
What we build for healthcare

Systems that respect the clinical reality

Two things sink healthcare software: a data model that ignores privacy obligations, and an interface that ignores how a clinic actually runs. Both are avoidable, and both are decided early.

Privacy and consent by design

Data minimisation, granular consent, role-based access and encryption treated as architecture rather than a settings page. Who can see what, and on what basis, gets decided before the schema does.

Interoperability: HL7 and FHIR

FHIR APIs, HL7 v2 interfaces, CCDA documents and the integration engines between them. Meeting the standard is the easy half; making another vendor's interpretation of it behave is the real work.

Patient-facing products

Booking, intake, results, messaging and remote monitoring, designed for people who are unwell, distracted or elderly. That is a different accessibility bar than a consumer app, and it shows in the build.

Clinical workflow tools

Software that fits how a clinic runs rather than how the process diagram says it does. Anything that adds time to a consultation gets worked around, and a worked-around tool is worse than no tool.

Access logging and audit trails

Every access to patient data recorded with actor, purpose and timestamp. Required for review, and the only way to answer "who looked at this record" with confidence rather than a guess.

AI with a clinician in the loop

Documentation drafting, intake summarisation, coding support and administrative automation, assistive by construction, with a named human approving anything that reaches a chart.

How we handle the risk

Where the guardrails go

PHI stays where you put it

Deployment inside your cloud account and data boundary, with self-hosted models available so patient data never leaves an environment you control.

Nothing clinical runs unattended

AI drafts; a person signs. That is a design constraint we hold regardless of how good the models get, because the accountability does not transfer with the output.

Built to be audited

Access logs, encryption, key management, retention rules and change control documented as we build. Your compliance team is a design stakeholder, not a final reviewer.

Tested against real workflows

Validated with the people who will use it during an actual working day. Clinical software that is technically correct and practically unusable fails in the same way as broken software.

How we start

Constraints first, then build

01

Map the data and the duty

What data the product touches, where it may live, who may see it, how long it is kept, and which regulations and institutional policies apply. This shapes the architecture, so it comes first.

02

Prototype with clinicians

Working software in front of real users early, in the context they will use it. Assumptions about clinical workflow turn out wrong far more often than assumptions about technology.

03

Roll out in a controlled way

Staged release starting with one site or cohort, with monitoring, an incident path and a rollback. Broad release is earned once the workflow has held.

Stack

What we build with

Interoperability
HL7 FHIRHL7 v2CCDADICOMSMART on FHIR
Product
ReactNext.jsReact NativeFlutterTypeScript
Backend & data
Node.jsPython.NETPostgreSQLFHIR servers
Security
Encryption in transit & at restKMS / HSMRBACAudit loggingSSO / SAML
Deployment
AWSGCPAzurePrivate cloudOn-premise
FAQ

Questions healthcare buyers ask

Compliance belongs to the organisation operating the system, not to a codebase or a vendor. What we do is build software that supports your obligations under HIPAA, GDPR or the local equivalent, encryption, access control, audit logging, minimum-necessary access, retention and breach detection, and sign a BAA where the engagement calls for one. Any agency telling you its code is "HIPAA certified" is describing something that does not exist.
Usually. FHIR APIs where the vendor exposes them, HL7 v2 interfaces where they do not, and an integration engine in between when the mapping gets ugly. The technical work is rarely the constraint, vendor access, interface fees and scheduling are, so we plan around those explicitly and start them in week one.
Ambient documentation, intake and history summarisation, coding and billing support, prior-authorisation paperwork, and administrative triage, each with a clinician reviewing before anything is committed. Autonomous diagnosis or treatment recommendation is a regulated medical device question rather than a software project one, and we say so at the first meeting rather than the last.
We do not develop against production patient data. Synthetic and de-identified datasets for build and test, restricted and logged access where real data is genuinely unavoidable, and environments separated so a development mistake cannot reach a live record.
On the build itself, close to it. What is genuinely slower is the front and the back, the data and access design at the start, and the staged, validated rollout at the end. Anyone quoting you consumer-app timelines for a clinical system has not priced those two parts.

Building for patients or for clinicians?

Tell us the workflow and the data it touches. We will come back with the constraints that shape the architecture and an honest view of the timeline.

Talk to a healthcare engineer

Reviews

Clutch
5.0
Upwork
5.0
Google
5.0
Freelancer
5.0