Clinicians need to review AI suggestions
AI that surfaces evidence and options with sources, with the clinician in charge.
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MedTech
Software for clinicians, with the evidence trail they expect
From an AI platform helping doctors turn data into decisions to medical-education tutoring: we build MedTech where every answer has a source, every action has an audit trail and every integration respects patient data.
- 130+People, remote across Poland
- 6 wksTo a working product, factory model
- 5.0Clutch rating from clients
This is for you if you build for clinicians, patients or payers
Patient data is regulated
Data minimisation, roles, encryption, audit trails and residency designed in.
Validation is part of the product
Evaluation sets, traceability and documentation ready for regulatory review.
You need engineers who ask clinical questions
A team that works with your medical advisors, not around them.
What MedTech gets from us. Safety as an engineering practice
How we work in MedTech
AI with provenance
Retrieval over approved sources, citations in every answer, evaluation against clinician-reviewed sets before release.
Privacy by design
Roles, consent, audit logs, encryption at rest and in transit, vendor review for every AI call.
Integrations and interoperability
HL7 FHIR, device data and EHR integrations scoped with the system owners.
Where MedTech products get stuck
Three risks we address in discovery.
The confident wrong answer
An LLM without retrieval and evaluation is a liability in a clinical setting. We measure before we ship.
Integration without owners
Every hospital system has an owner and a change window; we find both before the sprint that depends on them.
Documentation after the fact
Traceability from requirement to test is cheaper when written as you go — our factory produces it alongside the code.
An AI platform helping doctors decide
Our MedTech portfolio includes an AI platform intended to help doctors use clinical data.
The client is under NDA. The public preview describes an AI platform helping doctors turn data into decisions. It does not document clinical validation or a compliance review.
The public description is limited to the project preview.
You’re not getting a classic developer who simply does and then you have to fix the thinking yourself. If I had another AI idea and wanted to pursue it, I would just use Pirxey. It wouldn’t be a question.
What you get. Six ways we build MedTech
Clinical decision support
Evidence-based AI with citations and clinician control.
Privacy & compliance engineering
Roles, audit trails, encryption, residency, vendor review.
Integrations
FHIR, EHR, device and lab data with the system owners.
Patient and clinician apps
Web and mobile interfaces tested with real users.
Validation & documentation
Evaluation sets and traceability for regulatory review.
Product and AI audit
A ranked review of safety, data handling and model quality.
How we work
Evidence first
We set deadlines once the design is final, counted in working days, not as dates promised in a sales call. You hear about a problem from us, with options, while there is still time to choose.
You’re not getting a classic developer who simply does and then you have to fix the thinking yourself. If I had another AI idea and wanted to pursue it, I would just use Pirxey. It wouldn’t be a question.
How it works. From clinical need to a validated product
Scoping call
What you want to achieve, by when, with what budget. We say on the call whether we are the right team, and what the smallest useful first step is.
Workshop & plan
A short workshop with your stakeholders: outcome, hard and soft deadlines, integrations, risks. You get a written scope, a price range and the split between what AI accelerates and what needs a senior engineer.
Build in increments
We build in deployable increments with code review and automated tests. You get a status daily at first, then weekly once trust is there. Scope lives in Linear; conversations happen in Slack.
Launch & grow
Monitoring, documentation and runbooks handed over, or a squad that stays. Either way the product can be operated without us.
Proof, not promises
EdTech · AI
AI-powered medical tutoring for Elite Medical Prep
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Financial-crime investigation software for Poland's authorities
FinTech · Government
AML-grade oversight for U.S. political ad spend, built from scratch
What clients say
"Pirxey gave us the full package - frontend, backend, AI, and data - all under one roof, which meant we never had to coordinate multiple vendors. They thought like product owners, not contractors."
"What stayed with me was the communication. Fast, clear, and always with something concrete - a proposal, an update, a solution. We never had to wonder what was happening."
"Their ability to quickly deliver high-quality solutions while maintaining transparency in communication is rare."
"When you propose something to them, they don't simply say yes - they come back with a pro and con. You're not getting a classic developer who simply does and then you have to fix the thinking yourself. If I had another AI idea and wanted to pursue it, I would just use Pirxey."
"Well… didn't know what to expect but honestly, now I'm learning much from you guys. Had no idea an external tech partner can be so pro and organized."
"Their ability to quickly deliver high-quality solutions while maintaining transparency in communication is rare."
The people who build for clinicians
In MedTech the question is never whether the model can answer. It is whether we can show where the answer came from and who checked it.
Piotr
AI research and adoption
In MedTech the question is never whether the model can answer. It is whether we can show where the answer came from and who checked it.
Piotr
Delivery and squads
In MedTech the question is never whether the model can answer. It is whether we can show where the answer came from and who checked it.
Krzysztof
Architecture and APIs
In MedTech the question is never whether the model can answer. It is whether we can show where the answer came from and who checked it.
Grzegorz
Cloud and CI/CD
Questions MedTech teams ask us
- We scope the intended use with your medical advisors and define what needs to be tested. The public project preview does not establish clinical validation; suitability for a clinical setting needs to be assessed for the specific product.
- Data minimisation, roles, consent, encryption, audit trails and residency chosen for your jurisdiction; every AI vendor is reviewed for what it sees and retains.
- FHIR and HL7 integrations are scoped in discovery with the owners of each system and their change windows.
- Traceability from requirements to tests is produced alongside the code; we work with your regulatory consultant on the format.
- Our portfolio includes an AI platform for doctors under NDA and an AI tutoring product for Elite Medical Prep. The latter supports medical education. The public descriptions differ in how much detail they provide.
- We work remotely from Poland. We review the data access and agreement requirements for your project before confirming the engagement.
- A scoping call, then a discovery that ends with a written scope, a price range and the compliance work identified up front.
Discuss your MedTech product
Discuss your project with our AI Architects. No commitment, just clear answers and a roadmap.
Direct contact
Mike KacprowiczBook a callChief Growth Officer