Healthcare IoT (IoMT)

Healthcare IoT (IoMT) Software Development

One Platform for Every Connected Medical Device

Custom IoT healthcare software development, from connected medical device integration to secure, scalable IoT platforms.

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Reliable partner

Experienced team

Smart solutions

Case Study

“99% of hospitals manage IoMT devices with known exploited vulnerabilities, and 96% are tied to ransomware.” — The HIPAA Journal

Every connected device is an entry point, so secure IoT engineering puts device identity, segmentation, and encryption first, not bolted on after a breach.

IoT devices

IoT medical devices span wearables and biosensors, connected hospital equipment, and asset tags, all linked to one platform.

Data in motion

Devices stream IoT data in near real time, so clinicians and systems can act on it for decisions, automation, and analytics.

Broader than RPM

Remote patient monitoring is one use of IoT in the healthcare setting, but IoT in healthcare also covers in-hospital devices and smart infrastructure.

Secure by requirement

Because it carries health data and touches a medical device, IoT used in healthcare must be secure and, where applicable, meet FDA rules.

Zoolatech quickly delivers senior engineers through rigorous multi-stage screening and global sourcing, ensuring only high-performing, project-ready talent joins your team.

1 month

To fill a position

60%

Senior developers

1M

Global talent pool

98%

Client Retention Rate

300+

Successful Projects

Device integration

Connect an iot medical device from many vendors into one platform through the protocols it supports.

IoT platforms

Build device-to-cloud IoT applications that ingest, process, and route data at scale.

Smart hospital

Add asset and RTLS tracking, where healthcare IoT devices automate finding equipment, staff, and patients.

Wearables and biosensors

Develop apps for IoT devices and wearables that turn continuous signals into usable health data.

AI on device data

Apply AI and ML to device telemetry for predictive alerts and anomaly detection.

Telehealth and IoT

Combine connected devices with telehealth so remote care uses live device data.

Remote monitoring

Support remote monitoring devices as an IoT use case, linked to our remote patient monitoring practice.

Interoperability

Normalize device data to FHIR so it flows into EHR and clinical systems.

Edge computing

Process time-sensitive device data at the edge, close to where it is generated.

Managed IoT development

Run the whole IoT program through managed delivery, team extension, or a dedicated team.

Protocols and connectivity

Connect devices over Bluetooth Low Energy, Zigbee, Wi-Fi, cellular, and wired interfaces. Wireless IoT connectivity is matched to what each connected medical device supports.

Gateways and edge

Use gateways and edge devices for the integration of IoT devices to the cloud, handling connectivity drops and firmware variability across vendors.

Medical IoT device onboarding

Provision and onboard devices with unique identity, so every device and message on the platform is authenticated and trusted.

Regulated device software

When device software qualifies as a medical device, we take it through the SaMD and FDA pathway with our medical device software development practice.

“In the case of Zoolatech, it's a very tight partnership.

The team at Zoolatech is incredibly collaborative, and we work as a team despite being thousands of miles away from each other.”

Spencer Rascoff

CEO Match Group

5/5

“Zoolatech has been a key technology partner for Pandora,

enhancing our software development and deployment capabilities. They're ambitious, supportive, fast-moving, and well-skilled, with sound ethical values.”

Erika Romsics

Contract and Vendor Manager, Pandora

5/5

“The apps they’ve developed give us the opportunity to get more customers.

We’re providing more services to target big customers. We can install jobs faster and identify reduce bottlenecks, so we’re providing a better customer experience.”

Aida Youssef

Senior Director of Software Engineering, Complete Solaria

5/5

“Zoolatech has access to a deep talent pool and knows how to identify client's needs.

With the help of Zoolatech, went from a very early and incomplete prototype to the MVP release, the first production release, and the first paying customer!”

Greg Wagenhoffer

CEO, GreenVisr

5/5

“Zoolatech enabled us to build a world-class engineering team quickly and efficiently.

Zoolatech's pre-screening process and engineer training are customized for providing effective engineers that can contribute immediately to accelerating product roadmaps.”

Shariq Minhas

CTO, SVSG

5/5

“We can recommend Zoolatech

for their talent pool, attention, ability to understand our requirements, candidate screening process and constant communication.”

Chaitanya Pallapothula

SVP, Tailored Brands, Inc.

5/5

“Zoolatech’s developers quickly became an integral part of our team effort

with whom we shared daily stand up calls. Overall, Zoolatech fit well with our needs for agile development and continued to adapt as our needs evolved.”

Forrest Glick

UX Designer, Stanford University

5/5

“Working with Zoolatech has been a driving force in our business offerings.

The team utilizes it's experience and expertise meshing with our internal team creating a positive work environment. Zoolatech is by far one of the best teams to work with in the industry.”

Kris Naidu

CEO, Zeacon

5/5

Location systems

Real-time location systems help healthcare providers to track equipment, staff, and patients, so teams find what they need instead of searching for it.

Asset tracking

RFID and BLE beacon tags track assets across healthcare facilities, cutting loss and improving the efficiency of healthcare operations.

Environment and rooms

Environmental monitoring and smart rooms watch temperature, air quality, and equipment status, automating alerts when something drifts out of range.

Ingestion at scale

Edge computing

Normalization

Managed cloud

Handle the flood

IoT platforms ingest data from many devices at once, built as streaming pipelines that scale with device count.

Streaming: event-driven ingestion with tools like Kafka handles real-time, batch, and full-state device data.
Reliability: pipelines are designed for low latency and growth, so adding devices does not break the platform.
Buffering: message queues absorb traffic spikes and connectivity drops, so no device reading is lost in transit.

Process close to the device

Edge computing handles time-sensitive processing near the device, so decisions do not wait on a round trip to the cloud.

Edge AI: run inference at the edge for alerts that must fire immediately, independent of connectivity.
Filtering: process and filter data at the edge to cut noise and cost before it reaches the cloud.
Offline resilience: gateways keep collecting when connectivity drops, then sync to the cloud once the network returns.

One common format

Device data arrives in many formats, so we normalize it to FHIR before it reaches clinical or analytics systems.

FHIR and HL7: map device telemetry to standards so IoT data and EHR data line up.
Device to EHR: route normalized device data into the EHR and electronic health records.
Terminology: readings map to LOINC and SNOMED codes, so clinical systems interpret every value consistently.

Run it in the cloud

Managed cloud services carry the IoT data platform, so you scale without running the plumbing yourself.

AWS: AWS IoT Core and HealthLake connect devices and store health data in the cloud.
Azure: Azure IoT and Health Data Services provide a managed device-to-FHIR path.
Cost control: managed services scale with usage, so cloud spend tracks device count rather than idle capacity.

“The average hospital now runs 10 to 15 connected medical devices per bed, reaching hundreds of thousands of IoMT devices per facility.” — HIT Consultants

Data at that scale only works on a platform built for it, so we engineer ingestion, edge, and cloud that grow with your device count rather than stalling.

Predictive alerts

Models watch device data for early signs of a problem, so teams act before a situation becomes critical.

Anomaly detection

Anomaly detection flags device behavior that departs from the norm, surfacing failures and safety risks quickly.

Edge AI

Run models at the edge so time-sensitive alerts fire on the device, without waiting on the cloud.

Operational analytics

Aggregate telemetry across devices for population and operational analytics that inform how a facility runs.

Governed by design

Models are documented, monitored, and governed, so AI on health data stays accountable and safe.

Custom development

IoT healthcare solutions development

Custom IoT healthcare software development, end to end
Device firmware and medical device integration engineering
APIs and services connecting devices to systems
Architecture designed for scale and security

Cloud and edge

Where the data runs

Managed cloud on AWS IoT or Azure IoT
Edge computing for time-sensitive device processing
Device-to-cloud data pipelines built to scale
Infrastructure automation and reliability engineering

Data and analytics

Turn data into insight

Device telemetry normalized and stored for analysis
Dashboards and reporting on IoT data
Integration with our healthcare data analytics practice
FHIR normalization for clinical and analytics use

AI and ML

Act on the signals

Predictive and anomaly-detection models on device data
Edge AI for immediate, on-device alerts
Model governance and monitoring over time
Operational and population analytics from telemetry

Security and QA

Trust the platform

Secure IoT architecture with device identity and segmentation
Security testing across devices, network, and cloud
Automated testing and continuous delivery
Compliance with healthcare regulations built in

Device security

Data protection

FDA cybersecurity

Zero-trust

Trust every device

Every connected device gets a unique identity and is authenticated, so no rogue device joins the network unseen.

Device identity: each device is provisioned with credentials and authenticated on every connection.
Segmentation: network segmentation keeps a compromised device from reaching clinical systems.

Protect the data

Health data is encrypted in transit and at rest, with access controlled and logged across the platform.

Encryption: data is encrypted end to end, from device to cloud, protecting sensitive health information both in transit and at rest.
Access: role-based access and audit logging govern authentication and permissions for healthcare data.

When it is a device

For device software regulated by the FDA, premarket cybersecurity requirements and an SBOM apply.

Section 524B: premarket cybersecurity plans meet FDA requirements for regulated device software.
SBOM: a software bill of materials tracks components across the device lifecycle, cross-linked to our medical device practice.

Assume nothing

A zero-trust approach verifies every device and request, so trust is never assumed by location on the network.

HITRUST: security controls align with HITRUST and support compliance with healthcare regulations.
Monitoring: vulnerabilities are monitored and patched across the device lifecycle.

Medical device makers

MedTech and device makers get connected-device software, medical device integration, and the FDA cybersecurity work regulated products require.

Hospitals and health systems

Hospitals build smart hospital infrastructure and asset tracking, and IoT adoption improves safety and operations across the healthcare environment.

Digital-health and healthtech

Digital-health, wearables, and healthtech companies get the IoT platform and cloud engineering their connected healthcare products depend on.

Step 1

Discovery

We map your devices, protocols, connectivity, and goals, and define whether any software qualifies as a medical device. This is where scope, architecture, and security requirements become clear, so IoT for healthcare development fits the devices it will carry.

Step 2