For over ten years, CHI Software has helped healthcare organizations ship software that works under real clinical load. We take on the hard parts: interoperability, data security, regulatory documentation, and AI that survives beyond the pilot.
CHI Software is a healthcare software development company that builds, integrates, and modernizes clinical systems for healthcare providers, medical device manufacturers, and digital health vendors. We have over ten years of experience in custom AI and software delivery, most of which is in the most challenging aspects of the industry: These include EHR and lab integrations, connected-device software, and AI features that must pass review and continue to function once they are live.
We treat the non-functional work as the real work. Building healthcare software is about more than releasing features. Safeguarding patient data, keeping clinical workflows running during releases, and documenting enough to satisfy auditors, security teams, and regulators who weren’t present when the code was written are just as much part of the job.
Our healthcare software development services cover the entire process, from the initial discovery call to production support. The process is straightforward. Every clinical integration, compliance control, and AI feature should correspond to something that a care team, operations lead, or CFO can measure. The WHO’s Global Strategy on Digital Health, extended through 2027, makes the same point at the policy level: digital health only delivers results when financial, organizational, human, and technical resources work together rather than in isolation.
Before writing a single line of code, we conduct a discovery process. This process involves mapping clinical and operational requirements, reviewing the existing stack, sizing the integration work, and flagging areas where privacy, safety, or regulatory constraints will influence the development process. You will leave discovery with an architecture sketch, a realistic estimate, and a roadmap—not a sales deck. If an idea does not survive discovery, that is the best place to find that out.
The core of our custom healthcare software development services includes bespoke clinical applications, patient-facing products, and back-office systems built around your workflows rather than a vendor’s template. Our teams specialize in web, mobile, and backend development. Our medical software development services include features that most packaged tools overlook, such as role-based access control (RBAC), audit trails, clean API integration, and secure exchange with your existing systems.
Most healthcare software either succeeds or fails at its edges, where it meets an EHR, lab system, billing engine, or device. We build and maintain these connections using the sector’s standard protocols, designing them so that a new clinic or lab can be integrated without a rebuild. For Trapelo Health, this required a configurable platform that can accept new partners, regardless of their underlying technology.
Legacy system modernization rarely happens in one move. Old clinical systems are modernized in place and under load, without losing data or disrupting the workflows nurses depend on at 2 a.m. We re-architect and re-platform, handling cloud migration where appropriate. We can take on a single component or the full product. See our software product modernization services for how we scope that work.
By rule, some clients run in the cloud, but others cannot. For example, one telemedicine client had to store and process data on physical servers. Instead of defaulting to AWS or Azure, we built and deployed a stable, high-load environment for them. No matter which side you’re on, we handle the underlying data engineering: pipelines, structured clinical data, and a foundation on which both reporting and AI can sit without a second copy of everything.
AI in healthcare only earns its place when it enters production and stays there. From the first sprint,we develop and fine-tune AI features that include data lineage, monitored inference, and a compliance trail. We don’t add these features after the fact. Our healthcare AI consulting practice offers a full range of services, including scoping the proof of concept and creating a monitored, retrainable system. We build documentation and oversight controls based on near-future risks and regulations, for e.g. the EU AI Act Omnibus, with full compliance required by December 2027 and transparency obligations starting a year earlier. We build documentation and oversight controls into every project from the outset.
Release is just the beginning. We perform functional, performance, and security testing, then move on to maintenance, monitoring, and iteration. For regulated products, testing also provides evidence, in the form of records, that a build did what it was supposed to do.
Connected medical devices require firmware, connectivity, and a companion app that behave as an integrated system. We develop the embedded layer and surrounding software, treating security and documentation as integral parts of the delivery process. Our embedded software development services support this process with dedicated engineers.
Healthcare software requires clinical integrations, compliance-ready architecture, and AI features capable of reaching and maintaining production. These capabilities are difficult to maintain in-house because the rules are constantly changing.
Request a healthcare software architecture reviewOur healthcare software development solutions span patient-facing apps, clinical systems, connected devices, and research platforms. Below are the kinds of products we build, extend, integrate, or modernize. Building the software well does not by itself prove clinical effectiveness or earn regulatory approval, and we are clear with clients about where engineering ends and clinical and regulatory validation begins.
We developed portals and digital health apps where patients can book appointments, send messages, view records, make payments, and follow care plans. We developed a telemedicine product that evolved from a pharmacy marketplace to include video consultations, e-prescriptions sent directly to pharmacies, a medical forum, and a directory of institutions. This product is available on native iOS and Android platforms, as well as a responsive web app that is kept in sync.
Telehealth and remote patient monitoring (RPM) integrate wearables, phones, and Internet of Medical Things (IoMT) sensors into one system. Often, predictive analytics flag risk before it becomes an emergency. For a U.S. company that monitors seniors’ health, we extended its existing AI remote monitoring solution, adding two patient engagement apps, wearable support, an emergency button, GPS tracking, medication reminders, and health graphs. This solution is designed to help nurses in assisted living facilities prioritize which patients need attention first.
Device software unites firmware, connectivity, companion apps, and security documentation. We develop this stack as a single, traceable pipeline to ensure that the connected product and its documentation remain synchronized.
Medical device software needs firmware, connectivity, companion applications, and FDA cybersecurity documentation delivered as a single traceable pipeline, not as separate workstreams.
See how we structure a MedTech delivery pipelineEHR-adjacent tools, claims automation, and administrative systems that are easier to use and reduce errors for clinicians and staff. In radiology, for instance, integrating PACS and RIS can result in faster readings and fewer handoffs between systems.
Decision support that helps clinicians act on data they already have. We worked on oncology diagnostics software that recommends the smallest, most cost-effective set of tests, which is decision support and cost control in the same feature. Support tools inform a clinician’s judgment; they do not replace it, and we design them on that basis.
We design platforms that transform years of messy clinical records into data that researchers and analysts can query. For a provider with about 30 million mostly unstructured documents, we designed a de-identified FHIR layer that provides OCR, clinical entity extraction, cohort search, and reporting on top of the existing system. This way, the operational record remains the single source, while research and analytics draw from a single foundation.
Healthcare AI features that reach production need documented data lineage, monitored inference, and a compliance trail built in from the first sprint, not added before submission.
Evaluate your AI feature against production requirementsThe priorities of healthcare buyers may vary. Device makers prioritize more embedded reliability. Digital health vendors emphasize integration and scalability. Providers prioritize reliable daily workflows. Research organizations prioritize reproducible data. The National Institutes of Health (NIH) has issued guidance on biomedical data repositories that outlines four principles for research data: findability, accessibility, interoperability, and reusability (FAIR). These principles closely align with the requests of each group.
MedTech teams need reliable and well-documented embedded and connected software to support cybersecurity and premarket efforts. Our company develops firmware, connectivity, and companion software, and we keep an up-to-date paper trail as the product evolves.
The success of digital health vendors hinges on integration and scalability. Our healthtech software development services provide product companies with the engineering expertise needed to integrate with existing systems, manage load, and maintain quality control as they scale.
We are a hospital software development company. Our systems are used by clinical and administrative staff every shift. Dependability is our top priority, including reliable workflows, accurate data, and smooth implementation of changes.
Above all, life sciences and research teams care about one thing: Can you reproduce the result and show where the data came from? That’s why we build pipelines and platforms where any output can be traced straight back to its inputs. There are no black boxes. This is the foundation of trustworthy, reusable data that others can build on. We also see the bind most healthcare organizations are in. They have to push new AI initiatives forward while keeping day-to-day systems stable and available, and those two goals pull against each other. That is where one engineering partner across modernization, integration, and ongoing support earns its keep. You can move on innovation without putting operational stability at risk.
Security is not something that can be added at the end of a healthcare project. ENISA’s analysis of incidents in the EU health sector revealed that ransomware was present in 54% of the studied cases. This serves as a stark reminder that resilience and secure engineering are integral to the product, not an afterthought. From the beginning, we design with privacy, traceability, and verification in mind, tailoring the controls to each product’s specific operating environment.
HIPAA, GDPR, medical device regulations, and research data controls do not apply to every product. Treating them as one leads to over- or under-engineering. Newer rules raise the bar further. The EMA’s guiding principles for AI in the lifecycle of medicines point to traceability, validated performance, and documented human oversight. The FDA’s Quality Management System Regulation (QMSR), now in effect, folds updated design controls straight into how software is built. And the EU Cyber Resilience Act (CRA) adds security obligations for connected devices sold in the EU, with its main requirements phasing in over the next couple of years. We sort requirements by product classification and jurisdiction, and then we build the appropriate privacy and access controls. While we help incorporate the right documentation and controls, we do not guarantee regulatory clearance.
Interoperability in healthcare relies on shared standards. We use HL7 and FHIR, including FHIR R4, to connect clinical systems, laboratories, and analytics, ensuring that data is transferred in a format that the receiving system can understand. We also handle DICOM and PACS for imaging, laboratory information systems (LIS), and health information exchange (HIE), where records cross organizations. Good interoperability is also a privacy decision. It involves moving the right data and de-identifying it where necessary, rather than simply moving more data. Our software architecture consulting services help set the structure where this meets broader platform design.
Everyday work involves secure engineering, including encryption, access control, and audit trails. It also encompasses quality assurance in functional, performance, and security testing. Rather than conducting these tests as a pre-launch scramble, they are conducted as part of the delivery process. After release, continuous monitoring provides an up-to-date picture of real-world risks.
Reproducible pipelines, documented data provenance, and governance aligned with the FAIR principles and EMA or FDA guidance for AI in research are required for bioinformatics and clinical research platforms.
Assess your clinical data infrastructureAs a medical software development company, we move healthcare software from the requirements stage to production in short, validated steps. This way, business continuity, design documentation, reproducibility, and delivery performance are visible throughout the process rather than discovered only at the end. Regulatory expectations are incorporated into this process. For example, the FDA’s updated final guidance on cybersecurity and premarket submission documentation for medical devices supersedes an earlier version and is the kind of input we incorporate into the process. We help incorporate relevant engineering and cybersecurity activities, but we do not guarantee clearance.
We begin by understanding the clinical and operational problems, the systems involved, and the constraints that will influence the development process. These constraints range from data residency rules to the state of the legacy stack. The end result is a written document that both parties can refer to and use to hold each other accountable.
Initially, we design the architecture. Then we test it under extreme conditions before finalizing it. These cases include load, integration points, failure handling, security, and the documentation required for a regulated product. Validating a design on paper is far cheaper than discovering its shortcomings during production.
We build in short iterations, integrating early and often with the relevant systems and reviewing with your experts throughout the process. We treat integration as first-class work, not a phase tacked on at the end, because that’s where healthcare projects usually run into trouble.
Our team deploys with security and monitoring in place. The team scales as usage increases and continues to make adjustments once the product is live. We provide daily, weekly, and monthly reports so distributed teams always know where delivery stands.
A Forward Deployed Engineer turned a complex healthcare data challenge into prioritized use cases, a FHIR-based architecture, and an implementation roadmap for 30M clinical records without replacing the existing MIS.
Our client is a promising telemedicine startup based in Central Asia. They are committed to revolutionizing the healthcare marketplace by creating an advanced healthcare communication platform, enabling real-time video calls
Our client is a rapidly growing US-based healthcare company that specializes in remote patient monitoring systems for seniors. Their advanced solutions enable caregivers and healthcare professionals to remotely track and
We select the technology that best solves the healthcare problem at hand. We use React, Flutter, Dart, Java, and Node for scalable clinical and patient-facing applications. These are supported by PostgreSQL, RabbitMQ, and Firebase. We develop embedded firmware for medical device connectivity, enabling real-time communication via protocols such as WebRTC.
We use ETL pipelines, optical character recognition (OCR), and clinical entity extraction for reproducible research and clinical data analysis. We also use FHIR R4 and Power BI reporting. Depending on the task at hand, our teams use PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face, spaCy, OpenCV, and others for healthcare AI. To ensure secure data exchange and interoperability, we implement HL7 and FHIR, along with encryption, role-based access control, and audit logging.
Procurement in healthcare asks a fair question of any vendor: what have you actually done, and what will you be responsible for. The HHS Office for Civil Rights draws a useful line here. A software vendor that accesses protected health information (PHI) while providing a service can qualify as a business associate, while simply selling software without that access does not automatically create the relationship. We are direct about which role we play on a given engagement, because that clarity is part of what a healthcare buyer is paying for.
We have experience delivering real healthcare products, including telemedicine, remote monitoring, and clinical data modernization. As a custom healthcare software development company, we have experience with the regulated, integration-heavy work, not just the demo-friendly parts.
Much of the healthcare industry relies on systems that are too important to shut down and too outdated to ignore. We modernize and integrate these systems in place and under load, which requires a different set of skills than building on a clean slate. Our custom enterprise software development services extend this approach to the wider enterprise estate.
A single healthcare product may require the expertise of embedded engineers, cloud and data specialists, app developers, QA professionals, and AI experts. We bring those skills together, so the firmware and AI teams don’t compete.
You can work with us as a full delivery partner, a dedicated team, or additional capacity to fill a specific gap. We offer fixed-price and time-and-materials options. Most internal teams cover some, but not all, of what a healthcare build needs.
Healthcare projects usually need specialists across clinical integrations, embedded engineering, AI deployment, and regulatory documentation. Most internal teams cover some of these, not all of them.
Discuss where your team needs engineering support
A healthcare software development company designs, builds, integrates, and maintains the software clinical and health organizations run on, from patient apps to device software to data platforms. A good medical software development firm also takes on the parts buyers underestimate: integration with existing systems, security, and the documentation regulated products require.
Off-the-shelf tools are faster to implement and ideal when your process aligns with the product. In contrast, custom software development for healthcare is the better choice when factors such as integration, workflow fit, data ownership, and scalability matter more than speed of initial login, as is often the case in healthcare. Many organizations use both types of software, and the real work lies in deciding where each belongs.
Yes. Electronic health record (EHR) and electronic medical record (EMR) integration is central to most of what we do, using standards such as HL7 and FHIR. We have connected lab systems, built FHIR layers over existing medical information systems, and designed integrations so new partners can be added without a rebuild each time.
We treat them as design inputs, not just something to check off at the end. In practice, this means managing patient data in a way that considers privacy, encrypting the data, implementing role-based access control, and creating audit trails that are tailored to your jurisdiction. We implement the appropriate controls and documentation. We also remain transparent about the fact that engineering supports compliance, but does not hand you a certification.
The timeline depends on the scope and extent of the integration. A focused healthcare build usually takes four to nine months, including planning, data preparation, testing, integration, and deployment. Heavier integration, device work, or regulatory documentation will extend the timeline. In any case, you will receive a realistic estimate after the discovery phase, rather than an estimate based on assumptions before we understand the scope of the work.
Cost tracks complexity: how many systems you integrate with, how much data you process, device and security requirements, and the documentation your product class demands. When you compare quotes from any healthcare software development firm, look for whether integration, security, and testing are included in the number or waiting as a surprise later.
Full-cycle delivery, dedicated teams, and staff augmentation, under fixed price or time and material. Whether you need a complete partner or extra hands, the right model depends on what your team already covers, and a healthcare software development agency should fit its model to your gap rather than sell you a fixed package. Whichever you choose, our healthcare software development services flex to the scope you actually have.
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