AI-native transformation
for healthcare.
Seventeen years. Forty-plus healthcare clients. Patient-facing apps, enterprise platforms, IoT monitoring systems, and AI built for the full spectrum of healthcare: providers, payers, med tech, and pharma.
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Trusted across the care ecosystem
One of the most regulated,
high-stakes industries on earth.
Every stakeholder — the patient at home, the clinician at the bedside, the payer processing claims, the pharma team running a trial — operates under different constraints and needs different things from technology. We have built for all of them.
Most clients do not need a product at one point in the care chain. They need products at several points at once, and a partner who already understands all of them.
Across the full
healthcare ecosystem.
Six capability areas we ship most often for healthcare enterprises. Each is in production today for a real organisation, not a slide of what we could theoretically do.
Hold engagement across the whole care journey.
Mobile platforms for appointment scheduling, test booking, home collection, chronic illness tracking, medication management, and care plan adherence. Built for patients across literacy levels, geographies, and health conditions, and designed to sustain engagement across the full care journey, not just at intake.
The numbers behind
the engagements.
These are not projections. Every figure here comes from a system that is live, in production, and serving real patients and clinicians under regulatory scrutiny.
Healthcare AI
cannot afford to fail.
The stakes are clinical, regulatory, and human. Across our healthcare engagements, AI is embedded at multiple levels — part of how the product works from the ground up, not a feature bolted on at the end.
Structured pre-clinical assessment before a patient sees a physician
Fine-tuned health LLMs conduct structured intake interviews, reducing intake time and increasing diagnostic accuracy. They run in production, at scale, under regulatory scrutiny.
Computer vision for tumor detection
Models that identify and delineate tumor boundaries in MRI scans, reconstruct 3D structures from 2D slices, and flag anomalous growth patterns for clinical review.
Report delivery prediction
Machine learning that predicts diagnostic test report delivery times across thousands of test types and flags lab delays before they affect patient experience.
Predictive health monitoring
ML-powered risk scores put in front of physicians alongside patient history and diagnosed conditions, enabling earlier intervention before a risk becomes an event.
Surgical tool tracking
Computer vision that tracks instruments through a procedure in real time, part of the same vision stack we build for tumor detection and anomaly flagging.
These are production systems. They run at scale, under regulatory scrutiny, for real patients and clinicians.
Schedule a consultation →Live, in production,
making a measurable difference.
Every engagement here is live, in production, and making a measurable difference for a real organisation. A selection across diagnostics, hospital networks, med tech, payers, pharma trials, and clinical AI research.
Omni-channel patient engagement at national scale
One of India's largest diagnostics chains, serving 25 million patients a year. We rebuilt the patient engagement layer end to end — consumer app, phlebotomist app with route optimization, ML report-delivery prediction across 3,368+ tests, and 100x throughput scaling.
Bedside monitoring that catches deterioration
An FDA-cleared, HIPAA-compliant bedside system that detects early clinical deterioration in unmonitored patients. Heart rate, respiratory rate, SpO₂, and temperature captured via body sensor, surfaced to a nursing dashboard with criticality-based alerting.
ACO savings planner for field teams
The iPad app models annual ACO savings across performance factors, benchmarks against low, medium, and high performers, and generates action plans tied to specific value drivers — used live in client conversations.
Keeping trial patients engaged and compliant
An intelligent engagement platform for patients and site coordinators: structured onboarding, appointment tracking, schedule adherence tools, and an SOS alert for urgent clinical contact — improving data quality and reducing dropout.
AI for brain tumor detection in MRI
A deep learning system that delineates tumor boundaries across 2D MRI slices, reconstructs full 3D structures, calculates volume and growth rate, and flags unusual patterns — with an interactive 3D visualization layer built in.