Redefining Healthcare with Digital Transformation
We merge innovation with excellence to create transformative healthcare experiences that shape the future.
GET /Slot?status=free
POST /Appointment
status: 201 Created
Trusted by healthcare organizations












Our Vision for the Future
“To care for lives around us by engineering great solutions that transform the way healthcare is delivered.”
Healthcare software development services
Six solution areas that connect data, clinicians and patients, built by a team whose core practice is healthcare.
Healthcare software, built for providers, payers and health technology companies
Healthcare has been our work since 2010, not a vertical we added later. We design and build the software that clinicians, administrators and patients use every day, and we connect it to the record systems you already run.

Healthcare Integration
Streamline patient care with data access, improved workflows, and enhanced clinical decision-making.
Know moreSMART on FHIR
Enhance interoperability and empower clinicians with apps built on SMART on FHIR standards.
Know moreInteroperability
Enable the secure and effective exchange of healthcare data across systems and platforms.
Know moreTelehealth
Redefine remote care through real-time interactions and personalized patient experiences.
Know moreManaged Care
Connect healthcare devices and systems to enable real-time monitoring and improve patient outcomes.
Know moreVoice AI Agents
Automate scheduling, reminders and follow-up calls, with every clinical call routed to a person.
Know moreProviders
Hospitals, health systems and specialty practices that need software around the EHR, not another system beside it.
- SMART on FHIR apps that launch inside the EHR
- Referral, intake and prior authorization workflows
- Patient portals, telehealth and remote monitoring
Payers
Plans and administrators that need clean data exchange, automated review and an audit trail a regulator can read.
- Claims, eligibility and prior authorization data exchange
- Member portals and care management platforms
- Reporting and audit trails built for regulators
Health technology companies
Product teams that need a healthcare native engineering partner to take a platform from first release to scale.
- MVPs and first releases built healthcare ready
- EHR connectivity through HL7 v2 and FHIR R4
- HIPAA ready architecture and release process
Which AI capability gets your program past the pilot
Most AI work does not fail on the model. It stalls on grounding, evaluation, security review and the handoff to the team that has to run it. Our AI development practice covers the full path from first use case to a supported production system, and each capability below has its own page, its own team and its own body of work.

End-to-end AI development, with one team accountable from use case to production
Model-neutral by design, so the choice of model follows your data and your risk rather than a vendor relationship. Engineers review every change before it merges, and client code and data are never used to train models. Start here if you are still deciding which capability you need.
You have data and a prediction you need to trust
Forecasting, classification, anomaly detection and recommendation, built with evaluation and monitoring from the first sprint rather than added after launch.
- Forecasting and classification
- Anomaly detection
- Recommendation systems
- Evaluation from the first sprint
A workflow needs software that acts, not only answers
Agents that plan, call your systems, and hand off to a person at the points where judgment is required.
- Planning and tool use
- Integration with your systems
- Human handoff by design
- Audit trail for every action
You want generative AI inside a product, without pilot sprawl
Copilots, document workflows and content generation that ship behind guardrails and a single owner.
- Copilots inside your product
- Document workflows
- Content generation
- Guardrails and a single owner
Off-the-shelf models do not fit your domain
Model selection, fine-tuning, prompt design and evaluation pipelines, tested against your own data before anything is rolled out.
- Model selection
- Fine-tuning
- Prompt design
- Evaluation on your data
Answers have to come from your documents, with sources
Retrieval pipelines, chunking, citations and access control, so the model answers from what you approved and shows where it found it.
- Retrieval pipelines
- Chunking and indexing
- Citations
- Access control
The model is live and nobody owns it
Monitoring, drift detection, cost control and release management for models already in production.
- Monitoring
- Drift detection
- Cost control
- Release management
Which product engineering service gets your software to market and keeps it there
Software products stall for ordinary reasons: a scope that grew before anyone validated it, a design clinicians route around, a legacy system nobody can change safely. Our product engineering practice covers each stage, with one team accountable from the first prototype to the supported release.
MVP Development
Put a first release in front of real users quickly, with scope held to what those users need to test before you fund the rest.
Know moreProduct Design
Research-led UX and UI for clinical and enterprise software, tested with the people who use it before engineering commits to a build.
Know moreApplication Modernization
Move legacy applications forward in increments, without a rewrite that stops the clinic or the business.
Know moreMobile App Development
iOS, Android and cross-platform apps for patients, clinicians and field teams, built to pass a security review.
Know moreQuality Engineering
Test automation and release discipline, so a change reaches production without breaking what already works.
Know moreKnow more
View all our product engineering services
Also part of the practice: web application development , cloud enablement and DevOps for healthcare .
What healthcare digital transformation actually involves
Healthcare digital transformation is the work of changing how care is delivered and administered by changing the systems underneath it, rather than putting a new interface on the process that already exists. In practice that means making clinical and financial data reachable across the systems that hold it, automating the administrative work that does not need a clinician, and redesigning the workflow so the new capability is actually used at the point of care.
The distinction that matters most is the one between transformation and digitization. Digitizing means the same process, on a screen. Transformation means the process itself changes, and the systems change with it. Most healthcare organizations have done a great deal of the first and very little of the second, which is why staff still re-key data between systems that were bought precisely to remove re-keying.
The constraint is almost never ambition. It is that the data sits inside an EHR, a practice management system, a claims platform and half a dozen point solutions that were never designed to talk to one another. That is also where AI belongs: at the point where a decision is made repeatedly, by a person, using information a system already holds. Cabot has been building healthcare software since 2010.
Same process, two outcomes
Why healthcare transformation programs stall
Almost none of it is a technology failure. Across our provider and payer work, the same six things come up, and every one of them is visible before a program starts if somebody looks.
The data you need is inside the EHR and comes out grudgingly. Every initiative begins with a queue for an interface engine slot, and the queue is owned by a team with its own roadmap.
Integration debt compounds quietly. Each point solution was bought to fix one problem and added two connections. After a decade nobody holds the map, so nobody can price a change.
Compliance arrives as a final gate. Security and privacy review lands after the build rather than shaping the design, so findings turn into rework instead of requirements.
Pilots succeed and go nowhere. One department proves the idea, and nothing in the funding model, the support model or the training model was built to carry it to a second site.
Clinician adoption is assumed rather than designed. Add clicks to a clinician's day and the workaround wins. The system then reports beautiful numbers about a process nobody follows.
No one owns the data model. Three systems define an encounter differently, so every report needs reconciliation and every analytics project starts by rebuilding the same mapping.
What a healthcare-native partner does differently
Plenty of capable firms deliver digital transformation. Fewer have stood in an interface engine queue, sat with a nurse to find out why a screen gets skipped, or produced audit evidence for a payer review. Here is where that difference shows up.
| Dimension | Generalist digital partner | Cabot, healthcare-native |
|---|---|---|
| Access to EHR and clinical systems | Builds to an API specification and hands the integration risk back to you when the specification turns out to be incomplete. | Interface work is scoped as part of delivery, inside the record systems our clients actually run, so the integration risk sits with the team that is building. |
| Interoperability standards | REST and JSON, with healthcare standards subcontracted to a third party or deferred to a middleware vendor. | HL7 v2, FHIR R4, SMART on FHIR and CDS Hooks written by the same engineers who build the application, so the standard is a design input rather than a translation layer. |
| Compliance and audit evidence | HIPAA raised at contract stage, controls retrofitted once the security review finds them missing. | Access control, audit logging and PHI handling designed into the first release, with the evidence a reviewer asks for produced as the build goes rather than reconstructed afterward. |
| Clinical workflow | Requirements taken from a product owner, validated against a specification document. | Workflow observed with the people who use it, then validated clinically before rollout, because a workflow that adds clicks does not survive contact with a shift. |
How a transformation program runs with Cabot
Six stages, each ending in a decision you make rather than a deliverable we hand over. You can stop after any one of them, which is the point.
Systems and integration assessment
We map the systems, the interfaces between them and the data each one owns.
Integration architecture
We design how data will move once rather than repeatedly.
First workflow in production
One real workflow, live, with real users. See how we approach healthcare application development .
Clinical validation
We test it against real data and a real shift rather than a demo script.
Rollout and change management
Site by site, with training and support planned before the second site rather than after it.
Run and improve
We operate what we built, measure what it changed, and bring you the next candidate.
Most engagements begin at stage 01, and the assessment is useful on its own even if nothing else follows. Start with the systems assessment
Worried about where your client and patient data goes? Here is how Cabot protects it
Security practice applies to every engagement, and it is built in from the first sprint rather than checked at the end. The regulatory and interoperability items apply where your data and your market require them, and we scope which ones during the assessment rather than assuming.
Access limited by role
Each person sees only what their role and task require, and who can see what is settled before the first sprint.
Every access logged
Every read and every change is written to an audit log your compliance team can query.
Encrypted and separated
Data is encrypted in transit and at rest, with PHI kept separate from everything else.
Business associate agreement
We sign a business associate agreement before any protected health information is handled.
No real patients in test
Development and test environments use synthetic records, never real patient data.
Your IP stays yours
Your code and your data remain yours under an NDA signed before work begins.
HIPAA compliant software is built and operated, not bought. Compliance depends on how the software is configured, hosted and supervised, so we document the safeguards for your privacy officer instead of asking for trust, and your organization remains the covered entity. Read about our compliance practice and our work on SMART on FHIR applications .
Why healthcare leaders choose Cabot to run transformation programs
Healthcare is the practice, not a page
Healthcare software since 2010, with 700+ projects and 140+ clients behind it. The team that scopes your program ships provider software every week.
Interoperability depth
The interface engineers work in HL7 and FHIR every week rather than reading the specification for the first time on your program. When an exchange requirement changes, the people who read the specification are the people who hold the code, so the answer takes days rather than a vendor cycle.
Compliance designed in, not retrofitted
Who can see what, what gets recorded, and where patient data is allowed to sit are settled before the first sprint.
A delivery model that fits your clock
Offices in Cleveland, Ohio and Hamilton, Ontario, with engineering in Kochi, Kerala. Overlap hours with US time zones, and a named person accountable for each workstream.
Clinical judgment stays human
We automate the work that is rule bound and leave the work that needs judgment with the clinician. See our approach to AI agent development .
Design that survives a shift
Clinical interfaces are tested with the people who use them under time pressure, not in a conference room.
Not sure which system has to move first?
Most programs stall on sequence rather than technology. We map your current systems, the interfaces between them and the order the work has to happen in, and hand you the map whether or not you engage us to build.
Common questions about digital transformation in healthcare
Straight answers to what buyers ask before the first call.
What is healthcare digital transformation?
Healthcare digital transformation changes what the underlying systems do rather than what the screens look like. A program connects data that sits in separate systems today, removes administrative steps that do not need a person, and rebuilds the workflow around the result. The test of whether it happened is the number of hand-offs. If a paper form became a web form and everything downstream stayed the same, that is digitization.
Why do digital transformation projects fail in healthcare?
In our experience it is sequence rather than technology. Too many workstreams start at once, each waiting on another, and nothing finishes early enough to prove the program is working. The second most common cause is a dependency found late, usually an integration or a legacy system that has to move before anything else can. The third is clinician adoption treated as a training problem at the end rather than a design constraint at the start.
How long does a digital transformation program take in healthcare?
A systems and integration assessment takes two to four weeks. A first workflow in production, including the interface work behind it, typically runs eight to sixteen weeks, and the variable is almost always the record system: what it exposes, and how long the wait is for an interface slot. Full programs run in stages across quarters, and we scope stage by stage so you approve a number you can evaluate rather than a multi-year figure.
How much does digital transformation cost in healthcare?
Most of the cost sits in the systems underneath rather than the layer on top, which is why estimates that ignore the existing systems are usually wrong by a wide margin. We price each stage against an agreed scope, and the assessment stage is the one that makes every later number reliable. For an indicative figure on a first build, try our Cost Calculator.
Can you integrate with our existing EHR?
Yes. Most of our work involves an existing record system rather than replacing one. The practical questions are which interfaces your system already exposes, whether a FHIR endpoint is available or an HL7 v2 feed is the realistic path, and how long the interface queue is on your side. We answer all three during the assessment before committing to an approach.
Which interoperability standards do you support?
HL7 v2 for the messaging most systems still run on, FHIR R4 for modern APIs, SMART on FHIR for applications launched inside the record system, CDS Hooks where guidance has to reach a clinician in the workflow, and DICOM for imaging. Read more about how we approach healthcare interoperability.
How do you handle HIPAA compliance and patient data security?
The controls are design inputs on day one rather than findings from a review at the end. Access control, audit logging, encryption and separation of patient data are specified before the first sprint, and the evidence a reviewer needs is produced as the build progresses, so you get a record rather than a reconstruction. We confirm which frameworks apply to your market during the assessment. See our compliance practices.
Do you work with providers, payers or health technology companies?
All three, and the work differs by more than vocabulary. Provider work is dominated by the record system and by clinical workflow. Payer work is dominated by claims, eligibility and utilization data. Health technology companies usually need a product built to pass a health system's security and integration review. Our healthcare software development practice covers all three.
