You are building the model.
Clinical speech collection, medical imaging annotation, EHR and clinical text structuring, evaluation and red-teaming. Bought per engagement, delivered with provenance.
Healthcare & Life Sciences
AI can give care its time back.We build what makes it real.
Clinical speech and imaging data, expert annotation and evaluation, and AI systems built for defined healthcare workflows. From one Norwegian team, under GDPR, in the languages your patients speak.
What AI gives back
Care is losing hours it can get back. Three questions decide who gets them.
Documentation that writes itself. Findings flagged while they still matter. Tools that speak the patient's language. Whether that arrives in your clinic comes down to what the model learned from, and how it was proven.
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Where do our clinical hours go?
Into documentation. Ambient clinical AI returns those hours to the encounter, when the model has heard real consultations: interruptions, dialect, drug names spoken aloud, the way clinicians actually talk. That is trained, not assumed.
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Has it seen findings like ours?
A diagnostic model is only as good as its labels. Radiology, cardiology and pathology annotation with credential-verified reviewers, task protocols and QA records is what separates a model that assists from one that guesses.
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Does it speak our patients' language?
Danish, Norwegian, Swedish and Finnish clinical speech cannot be scraped at volume. Collection from native-speaker contributors, with documented consent, is the only source. If your tools should work here, the data has to be made here.
Two ways in
Building clinical AI? Or buying it? Both doors are ours.
System Data
You have the use case.
A defined clinical workflow turned into an operational AI system: assistants over your documentation, document flows, review queues. Built, integrated and proven before it touches care.
- 210,000+ contributors
- 50+ countries
150+ languages, including all Nordic. Operated from Norway.
What you can buy
The clinical data work, opened item by item.
Five engagements we run for healthcare AI teams. Each is independently purchasable, scoped per engagement, and delivered with the records that let you defend it.
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Clinical speech and ambient corpora
The consultations, dictations and commands an ambient documentation model must have heard.
- Data
- Contributor-sourced clinical speech: consultation-style dialogue, structured note material and clinician-spoken commands, captured with consent and rights controls configured for the engagement.
- System
- Speaker-diarized, verbatim or clean-read transcription with clinical terminology, dialect coverage and QA on every batch.
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Medical imaging annotation
Expert-reviewed labels for the findings your model must not miss.
- Data
- Radiology, cardiology and pathology annotation with credential-verified reviewers, a task protocol agreed up front, and QA records in the delivery package.
- System
- Reviewer qualifications, consensus stages and acceptance criteria set per engagement, for regulated model programs.
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Clinical text and EHR structuring
Notes and records turned into training data your lawyers can live with.
- Data
- Clinical text extraction, classification and structuring against an agreed delivery schema, exceptions and hard cases included.
- System
- De-identification scoped honestly: methods, limits and re-identification risk stated per engagement, never waved through.
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Clinical model evaluation and red-teaming
Proof that the model holds up on clinical language before a clinician relies on it.
- Data
- Native-speaker evaluation of clinical speech and medical language models, with safety-critical test material and edge cases that matter in care.
- System
- Human review of model output by evaluators calibrated on the actual clinical domain, reported per batch.
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Dataset licensing
Rights-cleared clinical corpora where collection is unnecessary.
- Data
- Ownership, consent and commercial rights verified at scoping. Where the rights setup does not hold, we say so and collect instead.
- System
- Licensed delivery with the consent and rights documentation in the package.
Nordic clinical speech · collect to evaluate
Nordic clinical language cannot be scraped. So we make it, word by consented word.
Danish, Norwegian, Swedish and Finnish clinical encounters: consultation transcription, structured note material and clinician commands. Every stage in the chain turns green only when a person has confirmed it.
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A native speaker, consented
Contributor-sourced clinical speech in Danish, Norwegian, Swedish and Finnish, with GDPR Article 7 consent and Article 9 biometric handling documented per contributor.
CONSENT · ON RECORD -
A clinical ear on every batch
Diarization and transcription with clinical terminology and dialect coverage, QA on every batch, de-identification with its limits stated.
QA · PASSED -
A native speaker rules on the model
Evaluation of clinical speech and language models against Nordic clinical language and the edge cases that matter in care, reported per batch.
RULED · NATIVE SPEAKER
Chain stages are the engagement's structure, not a live record. Scope, languages and QA stages are set per engagement.
AI Implementation for health
When the deliverable is the working system, not the dataset.
A defined clinical use case, turned into a system that runs inside your workflow and stops where your clinicians rule. Built, integrated, evaluated and monitored by the team that stays accountable for it.
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Clinical documentation workflows
Ambient and dictation-fed documentation flows that draft the note and leave the clinician the verdict.
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Assistants over medical documentation
Retrieval-grounded assistants that answer from your approved documentation, with source traceability and human handoff.
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Document and records flows
Extraction, classification and routing for clinical documents, with review queues where judgment belongs.
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Human-in-the-loop review
Review stations for model output in care settings: queues, escalation and an audit trail on every ruling.
Delivered with acceptance testing, monitoring and rollback, and with the technical documentation your GDPR and EU AI Act obligations ask about: what it learned from, how it was evaluated, where the human oversight sits.
Where patient words live
Words spoken in a clinic deserve the strictest room in the house.
A Norwegian company under GDPR. Clinical project data is stored in Europe by default and processed in the EEA where required, with the paperwork to prove both. US healthcare work is handled HIPAA-compliant.
- Jurisdiction
- Norway · GDPR-native
- Storage
- European by default
- Processing
- EEA where required
- Consent
- Documented per contributor
- US engagements
- HIPAA-compliant handling
- Contracts
- Standard DPA terms · SCCs available
- Erasure
- 30-day end-of-contract SLA
- Withdrawal
- Workflow with audit trail
Safeguards for US healthcare speech work Data residency in the EEA
Specialist routes
Four documents. Pick who is asking.
Every healthcare engagement gets inspected: by privacy, by procurement, by the clinician who has to trust it, by the team that has to train on it. These pages are written for that inspection.
Who is asking
- Healthcare data collection How PHI is de-identified and audited before it trains anything. What a strategic assessment scopes before the engagement starts. Which specialists label clinical data, and to what standard. DICOM, EHR and multimodal sourcing for a clinical model program. Inside GDPR Article 9 data controlsDe-identification pipelines and audit trailsStrategic assessment before an engagement Open the page
- Medical imaging annotation What governance evidence ships with every labelled study. The delivery gate and the quality metric you can hold us to. Who reviews the labels, under which review model. Quality metrics and decision evidence per batch, radiology to pathology. Inside Quality metric and delivery gateReview model with credentialed specialistsGovernance and decision evidence per label Open the page
- De-identifying clinical audio The 18 identifiers, the two lawful methods, and the residual risk. What documentation and audit trail the method leaves behind. What stays in the recording once identifiers are removed. Automated PHI detection and redaction, and where it needs a person. Inside The 18 HIPAA identifiers, in audioSafe harbor or expert determinationRe-identification risk factors Open the page
- Speech data for ambient clinical AI Every clinical claim mapped to a statute and a structural commitment. Where clinical AI procurement breaks, and the FAQ written for it. What high-fidelity ambient clinical speech has to capture. The methodology from consent-gated capture to delivery, step by step. Inside Regulatory posture under GDPR and the EU AI ActConsent-gated capture to contract-governed deliveryClinical procurement FAQ Open the page
Scope a project
Start with one workflow, one clinic, one language.
We scope against your workflow, write the specification with you and prove the work on a pilot batch before anything reaches care.
- Scope
- Specification
- Pilot batch
- Acceptance
- Production
A bounded pilot carries its own acceptance criteria. You judge the output against your clinic, not against a slide.
Briefs are treated as confidential. We are used to data that cannot leave the EEA and projects that cannot be named.
Image 10 · the bench edge, the channel as a floor line
The brief Tell us the workflow, the languages, and the data or system you need. We reply with a feasibility read.