Healthcare, reimagined with AI.
EHR overlays, telemedicine, clinical decision support, patient engagement, revenue-cycle AI, and life-sciences tooling — engineered for clinicians, validated for regulators, and designed around the patient's day.
A five-year transformation, compressed into one.
Telehealth, EHR modernization, and clinical AI converged faster than the decade anyone planned. See adjacent verticals in our industries index for comparable patterns.
Projected global telemedicine market by 2026. Virtual care is permanent, and every provider now runs hybrid by default.
US office-based physicians using EHRs. The digital record is the baseline — the next wave is interop, AI, and experience around it.
Surgical robotics market growth in 2025. AI-augmented procedures, imaging, and diagnostics are moving from research into protocol.
Pressures rewriting
how care gets delivered.
Virtual care, EHR modernization, clinical AI, workforce shortages, and consumer-grade expectations all converge on the same answer — software that takes load off clinicians and gives it back to patients as access.
Virtual care is permanent
Global telemedicine is a $185.66B market by 2026. Hybrid care — virtual first, in-person when it matters — is now how modern systems deliver.
Digital records are the baseline
90% of US office-based physicians already work in an EHR. Interop, FHIR, and modern analytics layers are the next frontier — not the EHR itself.
AI enters the clinical loop
From imaging to ambient scribing to decision support, clinically-validated AI is moving from pilot to protocol — the ROI case is measurable and auditable.
Workforce pressure keeps rising
Clinician burnout, staff shortages, and aging populations demand software that removes administrative load — not software that adds to it.
Patients expect consumer-grade experience
Scheduling, messaging, bill-pay, records, and outcomes — patients want the digital experience they get from their bank, delivered at the care setting.
Transition to value-based care
Software moving from volume-based fee-for-service to outcome-based reimbursement models that track longitudinal health improvements and quality metrics.
Software we ship
for providers, payers, and pharma.
Each block composes with the others. Pair with our AI & ML engineering practice and applied AI team for the clinical-AI and imaging work.
- 01
Electronic Health Records
Modern EHR cores and specialty workflow overlays — built around FHIR, clinician ergonomics, and outcome capture.
- 02
Telemedicine platforms
Low-latency video, store-and-forward, remote triage, and multi-specialty workflows — tuned for clinical use, not consumer calls.
- 03
Patient engagement apps
Scheduling, messaging, records, education, and outcomes — unified apps that patients actually open weekly.
- 04
Clinical decision support
Evidence-driven alerts, order sets, and risk scores integrated into the EHR workflow, with audit-ready explainability.
- 05
Remote patient monitoring
Device integration, cohort dashboards, and clinician alerting for CCM, RPM, and hospital-at-home programs.
- 06
Health information exchange
Interop layers that move records across providers, payers, and public-health registries — FHIR, HL7, CDA fluent.
- 07
Medical billing and coding
RCM automation, denial intelligence, and compliant coding workflows — front-office to closed claim.
- 08
Patient scheduling and access
Omnichannel scheduling, digital intake, and referral management that shortens time-to-first-appointment.
- 09
Inventory and pharmacy
Par management, supply-chain visibility, and 340B-aware pharmacy workflows for health systems and payers.
- 10
Analytics and reporting
Population health, quality-measure reporting, and clinical BI built on a governed healthcare data platform.
- 11
Life-sciences and trial tooling
eCOA/ePRO, site workflows, and trial analytics — built with Abbott, AstraZeneca-grade regulatory expectations in mind.
AI that clinicians
actually use.
Clinical AI fails if it adds clicks. Ours is built with clinical informatics in the room, validated on your data, and wired into the EHR — not parked next to it. Kick it off via a rapid POC on one specialty or care pathway.
Ambient clinical documentation
Speech-to-note AI that drafts the encounter in the clinician's style — reviewed and signed in-workflow, no separate app.
Clinical decision support AI
Risk models for sepsis, readmission, deterioration, and specialty-specific outcomes — with transparency clinicians will trust.
Medical imaging AI
Triage, measurement, and quality flags across radiology, pathology, and cardiology — integrated into the PACS, not around it.
Patient-facing care agents
Condition-specific assistants for chronic-care education, symptom triage, and adherence — clinically-governed and safe-by-design.
Revenue-cycle AI
Denial prediction, coding assistance, and prior-auth automation that reclaim revenue without expanding the team.
Operational and ops-AI copilots
Capacity forecasting, staff scheduling, and supply optimization — measurable reductions in overtime and waste.
Life sciences and
healthcare leaders.
A sample of enterprise health engagements. More across the case studies library.
Abbott
Digital and enterprise engagement with a global healthcare and life-sciences leader.
AstraZeneca
Pharma-grade digital delivery work supporting a global biopharmaceutical program.
Life Technologies
Life-sciences software partnership covering research workflows and enterprise systems.
Partner who's already
on the clinical floor.
Our healthcare work draws on engagements with Abbott and AstraZeneca. Compliance, clinical workflow, and validated delivery are default behaviors — not new territory. Review the engagement methodology for how delivery runs.
Enterprise healthcare experience
We've delivered across Abbott, AstraZeneca, and adjacent enterprise health programs — patterns that already cleared quality and regulatory review.
HIPAA, HITECH, GDPR-native
PHI handling, consent, audit trail, and breach-notification posture are architectural — not a retrofit before go-live.
FHIR, HL7, and interop fluency
We speak FHIR R4, CDS Hooks, SMART-on-FHIR, and a long tail of HL7 v2. Interop is where our healthcare builds start.
Clinical-grade UX
We design with clinicians in the room. Keystroke counts, alert fatigue, and after-hours click burden are metrics we optimize against.
AI the MRM and QA team will sign off
Every clinical AI feature ships with explainability, bias monitoring, and evaluation sets — the questions your clinical-informatics leadership is about to ask, already answered.
Delivery inside regulated guardrails
Validated SDLC, 21 CFR Part 11 capability, and documentation your QA team can hand to an auditor without translation.
Answers for
CMIOs, CIOs, and health founders.
01Are your healthcare builds HIPAA and GDPR compliant out of the box?
02Can you integrate with Epic, Cerner, Allscripts, and other EHRs?
03How do you validate clinical AI before it touches a patient?
04Can you build for life sciences and clinical trials, not just providers?
05How do you handle 21 CFR Part 11 or SaMD-style validation?
06What's a realistic timeline for a first telehealth or patient-app MVP?
07Who owns the AI models and clinical data pipelines?
Let's build your AI-native care stack.
One discovery call, a clinical-workflow walk, and a working prototype on your data in four weeks. Production rollout on a validated, audit-ready cadence your QA team will recognize.