Healthcare
Clinical systems built around the people using them.
Digital health platforms, interoperability, and clinical workflow tools for providers where software friction translates directly into clinician time and patient outcomes.
30+
Provider deployments
2M+
Patient records handled
40%
Less admin time
100%
Audit pass rate
The pressure
What healthcare teams are actually dealing with
Systems that add to clinician workload
Software that requires the same information to be entered three times, in three places, by the most expensive people in the building.
Data trapped in incompatible systems
A patient's record split across a PAS, a lab system, an imaging archive, and a spreadsheet, with no reliable identifier tying them together.
Privacy obligations against clinical urgency
Access controls that must be strict enough for regulators and fast enough that they are not bypassed during an emergency.
Procurement cycles longer than the technology
Multi-year selection processes that specify a solution which is already dated by the time it is implemented.
What we build
What we build for healthcare providers
Designed with clinicians in the room, because software that adds a click per patient will be worked around by lunchtime.
Clinical workflow systems
Order entry, results review, and care pathways designed around observed clinical practice rather than an idealised process diagram.
- Time-and-motion informed
- Single-entry capture
- Offline tolerance
Interoperability & integration
HL7 v2, FHIR, and DICOM integration with the identity resolution needed to make a longitudinal record actually trustworthy.
- FHIR APIs
- Master patient index
- Terminology mapping
Patient engagement
Portals, appointment management, and remote monitoring built to accessibility standards that assume users are unwell and in a hurry.
- WCAG 2.2 AA
- Low-bandwidth tolerant
- Multi-language
Privacy & access control
Role and context-aware access with break-glass procedures that are monitored rather than merely permitted.
- Context-aware access
- Monitored break-glass
- Immutable access log
Clinical analytics
Operational and outcome reporting with the definitions and lineage a clinical governance committee will accept.
- Governed definitions
- Cohort analysis
- Outcome tracking
Administrative automation
Referrals, coding support, and billing workflow that reclaims clinician and administrator hours from re-keying.
- Referral automation
- Coding assistance
- Billing reconciliation
Compliance
The regulatory surface we build against
Controls are designed into the architecture and evidenced in the pipeline, so an audit is a report rather than a project.
Outcomes
What these engagements produced
Representative results from engagements in this sector.
- 01
Hospital group
Forty per cent reduction in documentation time
Redesigned the clinical note workflow around single-entry capture, removing duplicate data entry across four downstream systems.
- 02
Diagnostics network
Results delivered in minutes rather than days
FHIR-based integration between the laboratory system and referring practices replaced a courier-and-fax process across 90 sites.
- 03
Community provider
One patient record across five source systems
A master patient index and terminology mapping layer produced a longitudinal record that clinical governance signed off for care decisions.
How we deliver here
Three things that make healthcare delivery different
Clinical time
Every extra click is measured in clinical minutes
A workflow that adds fifteen seconds per patient costs a busy clinic hours a week. We observe the work before redesigning it, because the friction that matters is almost never the friction described in the requirements document.
- Time-and-motion baseline captured on the ward, not in a workshop
- Single-entry capture rather than re-keying downstream
- Designed with clinicians, tested during real shifts
- Repeat study after rollout to verify the claim
Patient data
Consent and audit designed into the schema
HIPAA, DPDPA and ABDM each constrain how patient data is stored, shared and erased. Retrofitting consent onto a record model that never anticipated it is the most expensive rework in this sector.
- Consent captured as data, versioned per purpose
- Access audited at record level, not just at login
- Encryption and key rotation with documented runbooks
- Breach notification path defined before go-live
Interoperability
Standards-first integration, because the estate outlives us
HL7 and FHIR are unglamorous and they are how your systems will still talk to each other in ten years. Point-to-point integrations are quicker to build and become the reason the next programme costs what it does.
- FHIR resources rather than bespoke payloads
- Terminology mapped to standard code systems
- Integration contracts tested against real message volumes
- ABDM-ready where the deployment requires it
Regulatory surface
Which regime applies, and what it actually changes
Most healthcare deployments answer to more than one of these at once. Each constrains a different part of the build.
| Regime | Applies when | Main constraint | Where it lands in delivery |
|---|---|---|---|
| HIPAA | Serving US healthcare, wherever you are registered | PHI encryption, access audit, breach notification | Data model, logging and hosting region |
| DPDPAIndia, mandatory | Any Indian product touching personal data | Consent at collection, erasure, fiduciary duties | Consent model and data lifecycle |
| ABDM | Participating in India's health data ecosystem | Health ID linkage and consent artefacts | Identity resolution and record sharing |
| GDPR | Any EU patient in scope | Right to erasure, portability, processor terms | Deletion design and sub-processor contracts |
HIPAA
- Applies when
- Serving US healthcare, wherever you are registered
- Main constraint
- PHI encryption, access audit, breach notification
- Where it lands in delivery
- Data model, logging and hosting region
DPDPA
India, mandatory- Applies when
- Any Indian product touching personal data
- Main constraint
- Consent at collection, erasure, fiduciary duties
- Where it lands in delivery
- Consent model and data lifecycle
ABDM
- Applies when
- Participating in India's health data ecosystem
- Main constraint
- Health ID linkage and consent artefacts
- Where it lands in delivery
- Identity resolution and record sharing
GDPR
- Applies when
- Any EU patient in scope
- Main constraint
- Right to erasure, portability, processor terms
- Where it lands in delivery
- Deletion design and sub-processor contracts
Questions
What healthcare clients ask first
Usually about clinical disruption and about patient data.
Delivery and data
Will this disrupt clinical services during rollout?
That is the primary design constraint, not an afterthought. Rollouts are cohort-based behind feature flags, changes land outside peak clinical hours, and there is a tested path back to the previous workflow. We would rather take three months longer than take a ward offline.
How do you handle patient data in non-production environments?
Synthetic or irreversibly de-identified data, always. Production data does not enter a lower environment, which occasionally makes reproducing an issue harder and is not negotiable. Where a realistic dataset is genuinely needed we generate one that matches the statistical shape without the people.
Can you integrate with our existing EMR?
Usually, via FHIR or HL7 where the vendor supports it, and via a documented integration layer where it does not. The honest answer depends on the vendor and their licensing — we assess integration feasibility during discovery rather than assuming it, because it is the most common source of late surprises in this sector.
Working in a different sector?
The engineering practice is the same across every vertical we serve. Browse the full list, or tell us what you are dealing with.
All industriesStart with a clinical workflow review.
Four weeks observing how your systems are actually used, and a ranked list of the friction that costs the most clinical time.