Solutions // Healthcare AI

Healthcare AI, without the deck

Most healthcare AI pitches lead with a model. We lead with the workflow it has to survive inside — the clinician who has thirty seconds to look at it, the audit trail that has to hold up, the failure mode that can't be silent.

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Technical Scope

What this actually involves

Clinical decision support, triage assistance, documentation and coding automation, image or signal analysis, and the unglamorous work of getting a model to run reliably against real hospital data rather than a clean research dataset. We build the pipeline, the guardrails, and the interface a clinician will actually trust — not just the model.

Methodology

How we approach it

We look at the specific decision the AI is meant to support, and who is accountable if it's wrong.

We build against your real data — including its gaps, its inconsistent coding, and its missing values — not a curated sample.

We design for override. A clinician needs to see why the system said what it said, and needs an easy way to disagree with it.

Scoping Requirements

What we need from you to scope this

→ The clinical or operational decision you want supported, stated plainly
→ What data you have access to today, and in what format
→ Who is accountable for the output, and what "safe to ship" means for your organisation
→ Any regulatory pathway or clinical governance framework this needs to sit inside

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A working session or system diagram from an actual Healthcare AI engagement, not a generic "AI brain" graphic.

3:2 · Real photograph, never stock

Direct Technical Scoping

Talk to an engineer about a Healthcare AI project

What this actually involves

How we approach it

We look at the specific decision the AI is meant to support, and who is accountable if it’s wrong.

We build against your real data — including its gaps, its inconsistent coding, and its missing values — not a curated sample.

We design for override. A clinician needs to see why the system said what it said, and needs an easy way to disagree with it.

What we need from you to scope this

A few clear starting points help us design a solution that fits your clinical workflow, data, and safety requirements.

01 / THE DECISION

The clinical or operational decision you want supported, stated plainly

02 / YOUR DATA

What data you have access to today, and in what format

03 / ACCOUNTABILITY

Who is accountable for the output, and what “safe to ship” means for your organisation

04 / REGULATION

Any regulatory pathway this needs to sit inside (see note below)

Build healthcare technology with the right team.

Speak directly with senior healthcare technology specialists about architecture, interoperability, AI, compliance, integrations, and your next product milestone.

✓ Senior engineers

✓ Healthcare expertise

✓ No sales-layer handoff

Google Review

“Zero packet drops in our BLE biometric pipeline.”

“Pashupatastra engineered our continuous cardiac telemetry infrastructure from raw Bluetooth packets to FHIR R4 observations. Their understanding of low-power mobile Bluetooth reconnection and HIPAA BAA requirements gave our clinical advisory board complete peace of mind.”

Dr. David Vance, PhD

VP of Engineering · BioMetrics Connected Health

RPM · MedTech (Boston, MA)

“Saved our team 6 months of EHR integration delays.”

“Converting legacy HL7 v2 ADT/ORU messages into SMART-on-FHIR apps that launch inside Epic and Cerner was our biggest bottleneck. Pashupatastra resolved our schema impedance without disturbing hospital clinical staff.”

Elena Rostova

Chief Technology Officer · Regional Health Network

Interoperability · Hospital Systems (Chicago, IL)

“A truly clinical AI architecture with deterministic guardrails.”

“Unlike standard AI agencies peddling loose chatbot prompts, Pashupatastra engineered deterministic validation chains and clinician-in-the-loop escalation rules. Our doctors trust the outputs because every inference cites clinical guidelines.”

Dr. Kwesi Mensah

Head of Digital Health · Global Health Alliance

Clinical AI · HealthTech (Nairobi & London)

Healthcare AI, without the deck

What this actually involves

How we approach it

What we need from you to scope this

Talk to an engineer about a Healthcare AI project

What this actually involves

How we approach it

What we need from you to scope this

The clinical or operational decision you want supported, stated plainly

What data you have access to today, and in what format

Who is accountable for the output, and what “safe to ship” means for your organisation

Any regulatory pathway this needs to sit inside (see note below)

Where we work inside healthcare.

Connected care

Remote patient monitoring

Healthcare AI

MedTech and IoMT

Telehealth & engagement

Healthcare data

Interoperability

HealthTech product engineering

Healthcare AI in practice

Independent Client Reviews

“Zero packet drops in our BLE biometric pipeline.”

“Saved our team 6 months of EHR integration delays.”

“A truly clinical AI architecture with deterministic guardrails.”

Build healthcare technology with the right team.

Have a healthcare technology challenge?