Cloud, data and AI delivery for healthcare and life sciences
Clinical, lab and trial data is the most governed data your organisation holds and the least joined up. We build the platforms that make it usable, from the clinic to the research bench, without loosening a single control.
- AWS Premier Tier Services Partner, the top tier of the AWS network
- Generative AI competency The only GenAI and MSP partner in Canada
- Agentic AI Specialization Selected Canadian partner
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SOC 2 Type 2 + ISO 27001
Independently audited
What is changing in healthcare
- 81% of physicians now use health AI professionally, more than double the 2023 rate American Medical Association, March 2026
- 49% of healthcare organisations are still only experimenting with generative and agentic AI Deloitte, December 2025
- 1 billion health records exchanged over TEFCA, up from 10 million in under a year ASTP/ONC, June 2026
Who we work with in healthcare
The healthcare and life science organisations we build for, and the problem each brings us.
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Providers
Clinicians who need the record to be complete before the appointment, not after it.
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Payers
Claims, prior authorisation and the evidence that both were handled correctly.
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Health tech
Product teams shipping into a regulated environment on someone else’s timeline.
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Pharma and biotech
Research data that has to be reproducible years after the study closes.
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Medical devices
Fleets in the field reporting back under quality and safety obligations.
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Clinical networks
Many sites, one view, and interoperability that has to hold across all of them.
From encounter to evidence in five stages
One chain from the moment data is created to the moment it is defensible. Each stage names the services that serve it, so the page routes into the work rather than describing it.
What happens here
Notes, forms and device output arrive structured, with the standard they came in on recorded rather than assumed.
What you get
An intake pipeline and the mapping that keeps it standards-clean.
The failure it prevents
A record that is complete only after someone retypes it.
Services behind this stage Generative AI for healthcare Engineering
What happens here
Systems that were never designed to talk share a record, through interfaces that survive an upgrade at either end.
What you get
Working interfaces, with the tests that prove they still work.
The failure it prevents
A referral that arrives as a fax because the interface broke.
Services behind this stage Data architecture Cloud data migration
What happens here
Access is granted by role and purpose, and every read and write leaves a trail that an auditor can follow.
What you get
Controls as code, with the evidence collected as they run.
The failure it prevents
Discovering during the audit that nobody can say who saw what.
Services behind this stage Security Managed services
What happens here
Documentation, coding and prior authorisation are drafted by models and approved by staff, with the human in the loop where regulation puts them.
What you get
An assistant in your workflow, with its accuracy measured.
The failure it prevents
Automation that a clinician cannot override and will not trust.
Services behind this stage Generative AI Agentic AI
What happens here
Quality, cost and outcome measures come off governed data with lineage, so a number can be traced back to its source.
What you get
A governed model and the reporting your quality team signs.
The failure it prevents
A quarter spent reconstructing how a reported figure was produced.
Services behind this stage Data architecture Security
Our Focus Area
Intelligent Medical Mobility
Intelligent Medical Mobility
Routing and asset tracking for transfers, home care and deliveries, connected to hospital and EMS systems. Vehicle position, job status and clinical schedules run in one stream, so dispatch works from the same picture as the ward. Transfers stop being coordinated by phone call and the fleet stops idling between jobs.
Benefits
- Routes optimised in real time
- Transfers and fleets coordinated
- Connected to hospital records
AI-Driven Medical Equipment Uptime
AI-Driven Medical Equipment Uptime
Monitoring and anomaly detection on clinical equipment, so maintenance is planned before a diagnosis is delayed. Device telemetry and service history are joined per asset, and every alert names the signal behind it. Biomedical teams work from a ranked list instead of a queue of faults already affecting patients.
Benefits
- Failures predicted before they delay care
- Maintenance planned, not reactive
- Longer asset life
Smart Medical Manufacturing
Smart Medical Manufacturing
Real-time quality control, predictive maintenance and supply chain integration, with traceability from lab to shelf. Batch, equipment and environmental data are captured as they are produced, which makes an audit a query rather than a search. Deviations surface while the batch can still be corrected.
Benefits
- Traceability across production
- Quality issues caught early
- Supply chain visible end to end
Fragmented Patient Data & Lack of Interoperability
Fragmented Patient Data & Lack of Interoperability
Records joined across systems, labs and devices over HL7 and FHIR, into one reliable source. Most of the work is mapping and terminology: deciding what a field means in each system before deciding where it lands. Where a system predates FHIR we bridge it rather than replacing it, so the change stays reversible.
Benefits
- HL7 and FHIR pipelines
- One patient record across sources
- Less manual re-entry
Low Patient Engagement & Adherence
Low Patient Engagement & Adherence
Reminders, mobile journeys and assistants that keep contact between appointments rather than only at them. Messaging runs off the same record the clinic uses, so a cancelled appointment does not trigger a reminder for it. Teams can see which prompts actually change attendance instead of guessing.
Benefits
- Reminders for medication and follow-ups
- Assistants answering around the clock
- Fewer missed appointments
High R&D Costs
High R&D Costs
Platforms that speed discovery and trial design, from screening to prediction, with the analysis automated. Data from instruments, public sources and prior studies is prepared once and reused, which removes most of the manual assembly. Researchers spend their time on the question rather than on the spreadsheet.
Benefits
- Screening that narrows the field
- Predictive modelling before physical trials
- Analysis pipelines instead of spreadsheets
How we start
Three scoped entry points, each ending in something your team keeps.
Clinical data readiness
Two weeks, fixed scope
- Systems, standards and access paths mapped
- The gaps that block interoperability, ranked
- A costed plan your team keeps whether or not we build it
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Most popular
Documentation assistant pilot
Four to six weeks
- One workflow, your own documents
- Accuracy and handling time measured against today
- A production path if it lands
- Nothing to maintain if it does not
Managed clinical platform
Monthly
- Platform run, monitored and patched
- Evidence collected continuously for audit
- Named engineers and agreed response times
Questions we get
How do you handle protected health information?
It stays in your accounts, under your controls, with access granted by role and purpose and every read logged. Our own practice is SOC 2 Type 2 and ISO 27001 audited, which is relevant because your auditors will ask about the supplier as well as the system.
Can you work with our EHR?
Yes, through the interfaces it publishes. Where the EHR is the constraint we say so early rather than building around it and calling the result integration.
Does a clinician have to accept what the model drafts?
No, and that is the design. The assistant drafts, a person approves, and the approval is recorded. Where regulation requires a human in the loop, the workflow enforces it rather than assuming it.
What happens to the pilot if accuracy is not good enough?
You keep the measurement and we stop. Scoping it so the answer is useful either way is the point of a fixed-scope pilot.
Who owns the models and the code?
You do. Everything is built in your accounts, in your repositories, under your licences.
Cloud, data and AI for healthcare and life sciences
Healthcare data sits in electronic health records, laboratory systems, imaging archives and devices in the field. Most of it was never designed to be read together. That is the work: joining those sources over HL7 and FHIR, governing who can see what, and putting the result somewhere clinical and research teams can query.
Dedicatted has delivered cloud, data and AI work since 2016. We are an AWS Premier Tier Services Partner with the Generative AI and Machine Learning competencies, and we operate under SOC 2 Type 2 and ISO 27001. Engineering, data and security sit in one team, so a pipeline ships with its evidence rather than after it.
What we build for healthcare organisations
- Interoperability pipelines over HL7 v2 and FHIR, including the mapping and terminology work that decides whether records actually join.
- Governed clinical and research data platforms, with access, lineage and retention set per data class rather than per request.
- Clinical and back office AI, from documentation assistants to prior authorisation triage, measured against how the work is done today.
How the work starts
Most engagements open with a two week readiness assessment. We map the systems, the standards in use and the access paths, rank the gaps that block interoperability, and hand back a costed plan your team keeps whether or not we build it. A pilot follows on one workflow, with accuracy and handling time measured against your current baseline.
- Compliance handled as engineering: audit evidence collected continuously, not assembled the week before a review.
- Named engineers and agreed response times where we run the platform after go-live.
- DevOps and platform work included, because the release process is usually what limits how fast clinical software can change.
Where a system predates FHIR, we bridge it with an integration layer rather than replacing it. That keeps the change reversible and the clinical risk contained.
Get started with a healthcare technology consultant
Outline your clinical, data or compliance challenge. Our team responds within one business day with relevant experience and initial technical insights.
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Our team replies within one business day, with relevant experience and a first read on your problem.