Vendor-Neutral IoT Healthcare Solutions

Connect every device to the chart, keep it secure, and stay free to change vendors.

A hospital buys infusion pumps from one company, patient monitors from a second and home blood pressure cuffs from a third. Each ships with its own protocol and its own cloud portal. A year later a nurse checks three dashboards to see one patient, a cellular hub in a patient's home goes quiet and nobody notices for nine days, and the security team finds a fleet of devices that have not been updated since installation. Every device works as designed. Nobody designed the whole.

Our IoT healthcare solutions connect those devices through one vendor-neutral data path. We build the connectivity layer (Bluetooth Low Energy, Wi-Fi and cellular), the normalization that turns each vendor's payload into a single reading model, the integration that delivers readings to your EHR, and the device management and security that keep the fleet trustworthy. Medical device connectivity for patients at home, at the bedside or inside a product you sell comes from the same foundation, whether you call the work healthcare IoT solutions or IoT solutions for healthcare.

Most engagements begin with a device and data path audit that inventories your devices, protocols, network conditions and landing points in the chart, so you see the risks before you commit to a build. Tell us your device types, your EHR and the setting, and we will return a written scope with the integration and security questions that will set your timeline.

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99%

of the 351 healthcare organizations in Claroty's March 2025 analysis of more than 2.25 million connected medical devices had devices with known exploited vulnerabilities. Connecting a device is the easy part. Keeping it safe is the work.

86%

of those organizations had patient devices, such as patient monitors and ECG machines, with confirmed known exploited vulnerabilities. These are the devices closest to the bedside.

700+

projects delivered for more than 140 clients, with healthcare as the focus of our work.

What IoT healthcare solutions are, and how they differ from medical devices and remote patient monitoring

IoT healthcare solutions are connected systems of sensors, medical devices, gateways, cloud services and software that capture patient and equipment data and deliver it, securely and in a usable form, to the clinicians, records and applications that act on it.

Three nearby terms get confused with it, and the difference decides what you buy. The device itself, such as a glucometer or a pulse oximeter, is one component. The industry calls these IoMT devices, part of the wider Internet of Medical Things. Remote patient monitoring is a care program built on device data, with alert rules, staff workflows and billing. A device maker's own app and cloud, sold as IoMT solutions, move data from that one device and stop there. IoT healthcare solutions are the layer in the middle: the connectivity, the integration and the security that let many devices from many vendors feed one record.

For a leader, the test is simple. When you add a new device type next year, is that a configuration change or a new project? Many offerings behind the phrase connected devices for healthcare cannot answer that, and that gap is what this page is built around. Work that reaches beyond the device layer, into the platform and records underneath, sits with our healthcare software development practice, and the general build capability behind it comes from our IoT development team. Buyers searching for connected devices in healthcare, healthcare IoT or medical IoT are usually asking for this middle layer.

Why connected device programs stall on vendor portals, silent failures and fleets nobody patches

These are the six failure points that clinical engineering, IT and digital health leaders describe once IoT medical devices move from a pilot to a hundred rooms or a thousand homes. Better devices alone do not fix them.

Device data lands in vendor portals. Each manufacturer's cloud holds its own readings. The chart cannot read them, so clinicians open another screen, and staff copy values by hand.

Readings stop and nobody notices. A phone updates and the pairing breaks. A home Wi-Fi password changes. A cellular hub loses signal. The dashboard shows the last good value, not the silence, and a patient looks stable only because the data stopped.

Every device brings its own protocol and cloud. Adding a fourth device type means a fourth integration, a fourth contract and a fourth place where data can be trapped. Switching vendors means starting over.

Fleets sit unpatched on the clinical network. Devices are installed, accepted and forgotten. Firmware ages, credentials stay at factory settings, and the security team cannot say what is connected or what it can reach.

Alerts and raw streams have no owner. Readings flow in faster than anyone reads them. Thresholds were set once, by someone who left, and staff learn to ignore the noise.

Everyone owns a piece and nobody owns the whole. Biomedical engineering owns the device, IT owns the network, the vendor owns the cloud and clinicians own the response. The connection between them belongs to no one, and that is where the failures happen.

Clinical and administrative staff discussing hospital call handling and patient communication workflows (placeholder image, to be replaced)

The connected device capabilities our IoT healthcare solutions build and integrate

Six capabilities that healthcare IoT is built from, shaped to fit the devices, settings and EHR you already run. Some organizations need all six over time. Most start with the device class that causes the most pain today. Where the real need is the program around the devices, such as connected care solutions for chronic conditions, our remote patient monitoring work covers that side.

Device connectivity and data ingestion

Connections to Bluetooth Low Energy, Wi-Fi and cellular devices, with pairing support, missed reading detection and an offline fallback. Each vendor's payload is normalized into one reading model with device identity, timestamp and unit attached to every value.

Medical device integration with the EHR

Medical device integration that delivers readings to the chart as discrete data through FHIR R4 and HL7 v2 interfaces, so staff do not chart twice. Interface work sits with our healthcare integration services team, and apps that launch inside the record use SMART on FHIR.

Home and remote monitoring connectivity

Connected health devices for the patient at home: kits that pair without a nurse visit, cellular hubs for homes without reliable Wi-Fi, and a clear signal to staff when a patient has gone quiet.

In-facility device and asset connectivity

Connected healthcare devices and connected medical devices at the bedside and around the building: monitors, pumps, beds and equipment tracking, brought onto a governed network segment with readings routed to the right system.

Device management, updates and fleet monitoring

An inventory of every connected device, remote configuration, controlled firmware updates and health monitoring for the fleet, so you know which devices are online, outdated or silent.

Device security, identity and audit logging

Unique device identity, certificate based authentication, encryption in transit and at rest, network segmentation and a log of every connection and change. Readings that feed alerts can reach clinicians through clinical decision support inside the workflow.

What drives the cost of IoT healthcare solutions?

The price of IoT healthcare solutions comes down to seven things: how many device types and protocols are in scope, how many devices or patients the fleet will reach, how many systems the readings must reach, how much processing happens at the edge and how much in the cloud, which security tier applies, whether any component falls under FDA oversight, and the support model after launch. Integration and security are the pieces leaders most often underprice, so we cost each as a separate line. Start with a rough range from the calculator, then walk us through your devices and we will turn that range into a real estimate.

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Estimate your device build cost Ask an engineer about your devices

How we map your devices, data paths and risks before any build begins

Before development starts, we run a device and data path audit that answers four questions, in order, because each one changes the build rather than the backlog. The answers about IoT devices in healthcare come from a device inventory, from your clinical engineering, IT and clinical leads, and from tracing one real reading from the device to the chart.

Which devices and protocols are in scope

We list every device type, who makes it, how it connects and what it sends. Bluetooth, Wi-Fi and cellular devices behave differently in the field, so we rank them by volume and risk and choose where to start.

Where the data lands and who reads it

We follow a reading from the device to the person who acts on it. We settle which readings go to the chart as discrete data, which go to a review queue and which never leave the monitoring system.

What the network and security posture is

We look at segmentation, authentication, update practice and logging. This answer sets the security work and often the schedule, because a device that cannot be updated needs a different design.

What regulatory scope applies

We decide which components may be regulated devices, which handle protected health information and which agreements are needed. Your privacy officer and counsel confirm the result.

What does AI change in connected device programs, and what must it never do?

In IoT healthcare solutions, AI does the work that used to need a person watching every stream. It normalizes device payloads into one model, flags readings that drift or stop arriving, groups device failures by likely cause and drafts the mappings and tests that engineers review. The second use is design time: drafting integration code, test scenarios and documentation for your team to approve.

What AI should not do is set clinical thresholds, change a device configuration or write to the chart on its own. It does not decide what a reading means for a patient, and it does not push firmware. We use deterministic rules wherever a value or an alert must be exact, and we use AI where a person reviews the result before it matters. Where a model watches the data for patterns, our AI health monitoring agents work covers that side, and our healthcare AI consulting team starts from your data and your governance.

The same discipline applies to how we build. Three commitments are written into every engagement. We stay model neutral, choosing the right tool for each task rather than tying your pipeline to one AI vendor. A named engineer reviews every AI assisted change before it merges and answers for it as for code they wrote themselves. And we never train models on your code or your data. During development, real patient readings stay away from any outside model, and test data is synthetic or de-identified. Our AI development services describe the wider practice.

The tooling behind a Cabot IoT engagement

Healthcare IoT development goes best when the stack is set by your devices, your EHR and your hosting, not by our preferences, so we build in the cloud and the language your IT team has standardized on. Interface work sits with our healthcare integration services team, and exchange standards, including FHIR, shape the way readings reach the chart. The table below shows, stage by stage, what AI handles, what a person keeps and which tools are involved.

What we work in:

Connectivity and devices

Bluetooth Low Energy

Wi-Fi

Cellular LTE-M and NB-IoT

MQTT

Edge gateways

Device simulators

Integration and standards

FHIR R4

HL7 v2

SMART on FHIR

REST APIs

Terminology mapping

Event streaming

Cloud and security

AWS IoT

Azure IoT

Device certificates

Encryption

SBOM tracking

OpenTelemetry

What AI does at each stage of building IoT healthcare solutions, and what it never does

Every stage produces something you can review, and every stage has a person who signs it off. AI output does not enter your codebase, your device configuration or your patients' records until someone named has accepted it.

Build stage	What AI does	What stays human	Tools used
Device and data path audit	Summarizes device inventories, network diagrams and interview notes into the decisions they contain, and drafts acceptance criteria from a written intent.	Sitting with biomed, IT and clinical leads, choosing the device classes in scope, and committing to scope.	Claude, Jira AI
Connectivity and integration build	Drafts device payload mappings, FHIR resource transformations and repetitive code, following patterns already in your repository.	The data model, the integration design, and every decision about which readings cross which boundary.	GitHub Copilot, Claude Code, Cursor
Code review	Flags a first round of problems such as unhandled errors, gaps in input validation and common security mistakes.	Approving the merge. One named engineer accepts each change and remains answerable for it.	GitHub Copilot, SonarQube
Test	Writes test cases against simulated devices, including dropped connections, duplicate readings, clock drift, out of range values and a firmware update in the middle of a session.	Choosing what must be tested, which failure would harm a patient, and whether the suite proves it.	Playwright, GitHub Copilot
Release and operate	Drafts release notes and groups production errors, such as failed pairings or undelivered readings, by likely cause.	The go or no go call, the order devices and sites go live in, and when a firmware update is released.	GitHub Actions, Grafana

How Cabot IoT healthcare solutions differ from a single-vendor platform or a cloud IoT service alone

A single-vendor IoMT platform or a cloud IoT service works well when your fleet looks like the one it was designed around. In a build, buy or assemble decision, these six dimensions are where the difference shows when it does not.

Dimension	Single-vendor platform or cloud IoT service alone	Cabot
Which devices work	Works best with the devices the vendor sells or has certified, so a new device type means a vendor project.	A vendor-neutral data path, so you choose devices by clinical need and add a type without replacing the platform.
Depth of EHR integration	Offers the integrations on its list, often as a summary view or export, so staff still chart twice.	Integration is scoped against what your EHR exposes, and the first release returns readings to the patient's chart.
Who owns security	The vendor secures its cloud, and the devices and network between are left to you.	Device identity, segmentation, updates and logging are designed as one program, with a named owner for each.
What it costs as the fleet grows	Often priced per device or per message, so cost rises with every device and site you add.	A build cost you can plan, with run costs that follow your infrastructure rather than your device count.
Who owns the data	The vendor holds the readings, and exporting your own data can become a project.	You own the code, the data and the audit trail, and we do not train on your data.
Regulatory scoping	Left to you to work out, often after contracts are signed.	A scoping step in the audit that names which components may be regulated and what follows.

Who commissions IoT healthcare solutions, and where each one gets stuck

Three kinds of organization bring us connected device work. Each gets stuck in a different place, so here is what we understand about each.

Health systems and clinical engineering teams

The pressure is variety. Devices from many vendors, installed across years, each with its own portal, and a chart that sees few of them. The hard part is rarely a device. It is one inventory, one security standard and one path into the record that biomedical engineering, IT and clinicians all trust.

Home health, post-acute and monitoring operators

A thin staff cannot absorb silent failures. The work is kits that pair without a visit, connectivity that holds in homes with poor Wi-Fi, and a clear signal when a patient has gone quiet. Staff time per patient decides whether the program holds.

Device makers and digital health companies

A product team has a device or a clinical model that works and needs the connectivity, cloud and integration around it, including medical device software development for the connected layer. The work is reaching a pilot a hospital customer can approve, passing its security review, and then growing it in increments.

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How device data, access and audit trails stay protected and compliant

We treat security as a condition of finishing a feature, not a review scheduled at the end. Every device has its own identity, sign-in for staff runs through single sign-on with multi-factor authentication, data is encrypted in transit and at rest, credentials live in a managed vault instead of in configuration files, and every connection, change and user action is logged, starting with the first working version. Devices sit on segmented networks and receive only the access their job needs.

Which rules apply to IoT healthcare solutions depends on who runs the system and what it does. A provider or health plan is generally a HIPAA covered entity, and any vendor that handles protected health information, including a cloud provider, needs a business associate agreement. Whether a connected product is regulated as a medical device depends on its intended use. Section 524B of the Federal Food, Drug, and Cosmetic Act sets cybersecurity requirements for certain connected devices in premarket submissions, including a plan to address vulnerabilities and a software bill of materials, and FDA has issued guidance on how to meet them. Reviewer and patient screens follow the accessibility requirements set in the audit. Your counsel and regulatory advisers confirm what applies, and we keep the evidence trail that review needs. Our compliance practice covers the wider program.

Unique device identity

Network segmentation

Encryption in transit and at rest

Audit log of every connection

Business associate agreements

Software bill of materials

What happens, stage by stage, in a connected device engagement with Cabot

The work on IoT healthcare solutions runs in three stages, and each one closes with a choice that is yours to make. Many organizations commission the device and data path audit on its own first, which lets them see how we work before they sign up for a build.

Device and data path audit

We inventory the devices, protocols and networks, trace one reading from device to chart, review the security posture and scope the regulatory questions. The stage ends with a written scope, a risk list and a realistic integration timeline. Whether to go further is then your call.

Pilot one device class end to end

The first increment takes one device class in one setting from the device to the chart, and measures what matters: how many expected readings arrive, how often pairing succeeds and how fast a silent device is flagged. A named engineer approves every change before merge. After the pilot, you choose what gets built next.

Scale by device class and site

Rollout goes one device class or site at a time, with the support path and the update process agreed in advance. After launch, fleet health and reading arrival rates show where to widen scope, including the moments when a human check matters more than a planned feature.

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Who delivers your IoT healthcare solutions, and what each person answers for

Every role has a clear owner from day one. The tech lead answers for the architecture, the data model and the decision to merge each change. A connectivity engineer answers for pairing, offline behavior and cellular reliability. An integration engineer looks after every connection into and out of your EHR and terminology services. A security engineer answers for device identity, segmentation, updates and logging. A biomedical liaison works with your clinical engineering team on device behavior and acceptance. The quality lead answers for the test suite and for what it demonstrates. The delivery lead runs the schedule and keeps clinical and operational leaders informed between demos. For any decision, you know the person responsible and how to reach them.

Our strength in IoT healthcare solutions comes from connected device work concentrated in four areas. The first is the path from device to chart, so readings arrive as discrete data and not as screenshots. The second is connectivity that holds in the field, including pairing, offline behavior and cellular. The third is the device security lifecycle, from identity to updates to logging. The fourth is regulatory scoping before the build, not after. Where a single-vendor platform would serve you better than a build, we say so.

Your team and ours work inside an overlap window agreed in writing at the start, and anything that needs your decision is saved for it. Design decisions live in your repository as short written records, so a change of engineer does not cost you weeks. If the scope grows, we add engineers to the same team rather than standing up a second one.

Why healthcare leaders choose Cabot for vendor-neutral IoT healthcare solutions

Healthcare connected devices only pay for themselves if the data reaches the people who act on it and stays safe on the way. These are the reasons leaders give for choosing Cabot for IoT healthcare solutions.

One data path, whatever the device

A new device type is configuration and mapping, not a new integration project, so your choices stay open and a change of vendor does not mean starting over.

Readings that reach the chart

Output flows into your EHR through FHIR and HL7, with a review step where you require one, so the work does not end as another dashboard.

Silence is treated as a signal

We design for the patient who has gone quiet. Missed reading detection and offline fallback are part of the first increment, not a later phase.

Security across the device lifecycle

Identity, segmentation, updates and logging come first, and we never train models on your patient data. For related work, see our AI development services.

Rules you can follow

HIPAA, the FDA cyber device question and business associate agreements shape the design from the first increment, and your counsel reviews the evidence trail.

A clear answer on build, buy or assemble

After the audit we tell you which applies, including when a single-vendor platform or a cloud IoT service is the better choice.

Where to go next, depending on your situation

This page covers IoT healthcare solutions, meaning the device connectivity, integration and security layer. If one of these describes you better, start there instead.

You need a monitoring program on top of the devices

When the priority is alert rules, triage queues, patient onboarding and billing documentation, the work is a program build. Start at remote patient monitoring.

Readings now need something watching them

When the question is catching patterns across streams and routing them to the right person, the work is agent design with tight limits. Start at AI health monitoring agents.

The data now needs analysis

When devices are connected and the next step is reporting, trends and measures across a population, the work is analytics. Start at health data analysis.

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Our Clients

Client Success Stories

AI-accelerated discovery-to-MVP patient and physician marketplace platform screenshot

AI-Accelerated Discovery to MVP for a HIPAA-Compliant Patient and Physician Marketplace

A discovery-to-MVP marketplace build that confirms every booking is license and location eligible before it happens, delivered inside a HIPAA boundary.

Read the case study

AI-Powered Referral Document Analyzer using Local LLMs

Referral documents extracted into structured fields by AI and confirmed by a person, running on locally hosted models rather than a third-party API.

Read the case study

Automated Patient Summary Generation and Eligibility Assessment

AI drafts a patient summary and eligibility assessment, and a coordinator confirms it before it is used.

Read the case study

MyHealingMate patient engagement platform screenshot

A Digital Platform Connecting Lives and Transforming Care

A HIPAA-compliant patient engagement platform pairing appointment scheduling with virtual consultations and medical record management, lifting virtual doctor consultations 15% in six months.

Read the case study

See all Cabot case studies

Questions healthcare and digital health leaders ask about IoT healthcare solutions

What are IoT healthcare solutions?
IoT healthcare solutions are connected systems of sensors, medical devices, gateways, cloud services and software that capture patient and equipment data and deliver it securely to the clinicians, records and applications that act on it. The devices themselves are often called the Internet of Medical Things. The solution is the connectivity, integration and security around them.
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How do connected devices send data to the EHR?
A device sends readings over Bluetooth, Wi-Fi or cellular to a phone, gateway or cloud service, where each vendor's format is normalized into a common model. The data then reaches the EHR through an interface, typically FHIR R4 or HL7 v2, as discrete values the chart can store. What the EHR exposes decides the work, so we confirm it during the audit.
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Should we use Bluetooth, Wi-Fi or cellular for healthcare IoT?
Bluetooth Low Energy suits personal devices that sit near a phone or hub and run on a small battery, but pairing is where it most often fails. Wi-Fi carries more data and suits fixed devices, but it depends on network access and credentials that change. Cellular, including LTE-M and NB-IoT, works in homes without reliable Wi-Fi and removes the pairing step for the patient, at the cost of carrier fees and a hub. Many programs use two of the three.
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Are IoT healthcare solutions HIPAA compliant, and how is device data protected?
HIPAA applies to the organization that runs the system, and it requires safeguards for protected health information and a business associate agreement with each vendor that handles it, including a cloud provider. We give every device its own identity, encrypt data in transit and at rest, segment the network and log every connection. Your counsel confirms what applies to you.
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Does a connected device need FDA clearance?
It depends on the intended use. Software and devices that diagnose, treat or monitor a condition for clinical decisions may be regulated as medical devices, and Section 524B sets cybersecurity requirements for certain connected devices, including a software bill of materials. Software that only moves data may fall outside FDA oversight. We scope this during the audit, and your regulatory advisers confirm the answer.
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How much do IoT healthcare solutions cost?
Price follows scope, meaning the device types and protocols, the size of the fleet, the systems the readings must reach, the security tier and any regulatory work. A per-device fee tells you little about what a build will cost. Our cost calculator gives you a first range in a few minutes, and we then price it against your device list before anything is committed.
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How long does it take to connect devices to our systems?
One device class in one setting is the fastest part to reach. The full timeline is set less by the code than by access: which EHR interfaces exist, how soon devices and test accounts are available, and how long security and compliance review take. We establish all three during the audit, so the timeline you receive reflects them rather than a generic estimate.
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Should we build IoT healthcare solutions, buy a platform or use a cloud IoT service?
Buy a single-vendor platform when your devices come from that vendor and its integrations match your EHR, because it will be faster and cheaper. Use a cloud IoT service when you have engineers to build around it. Build or extend when your fleet spans vendors, when you need readings in the chart as discrete data, or when per-device fees will grow faster than your budget. We tell you which applies after the audit, including when the answer is to buy.