Clinical data intelligence

The right data starts with the right question.

Tysena helps AI, life sciences, and healthcare teams define, source, and create the clinical data required to move ambitious work forward.

Your research defines the data. We find the way to deliver it.

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Finding what others miss.
The problem

Data is abundant.
The right data is not.

AI and healthcare development increasingly depend on highly specific clinical information — particular populations, modalities, histories, outcomes, annotations, or combinations that do not exist neatly inside conventional datasets.

The challenge is rarely acquiring more data. It is finding or creating the data that answers the actual question.

How Tysena works

Start with the research question. Not the inventory.

We begin with the cohort, modalities, longitudinal depth, intended use, geography, annotation, and consent requirements — then design the data path around them.

01 / Define
Research questionCohort, modalities, depth, geography, annotation and intended use.
Tysena
Existing dataLocate and structure what already exists.
Custom collectionRetrospective or prospective, built to protocol.
Hybrid datasetCombine existing and newly collected data.
04 / Deliver
Research-ready datasetCurated to the agreed specification and use case.
Clinical accessData engineeringGovernanceQuality assurance
Built for difficult cohorts

The company you call when the data problem is difficult.

Specific is where the model becomes valuable — especially when real inclusion criteria, modalities, and longitudinal detail are applied.

01 / Cohort

“Can you find patients with this diagnosis and this treatment history?”

Define the clinical logic first, then identify the feasible path to the cohort.

02 / Multimodal

“Can imaging be paired with pathology and longitudinal outcomes?”

Connect clinically meaningful modalities around the same patient journey.

03 / Create

“What if part of the dataset simply doesn’t exist?”

Where appropriate, design a targeted collection pathway rather than lowering the research requirement.

What makes Tysena different

Complex data. Clearer possibilities.

Rich clinical context

Notes, diagnostics, outcomes, imaging, pathology, laboratory data, waveforms, and other modalities can be connected into deeper patient-level context.

Multimodal by design

Healthcare does not exist in one format. Neither should the dataset.

Built around the use case

Instead of forcing the work into an available dataset, sourcing and collection can be shaped around the problem being solved.

Access beyond conventional datasets

Healthcare relationships create pathways to cohorts and data combinations that may never appear in a commercial catalog.

Modalities

Clinical reality is multimodal.

The value is not in collecting formats independently. It is in connecting them around the same patient, event, and clinical journey.

One patient.
Connected clinical context.
Clinical notes
Imaging / DICOM
Pathology
Laboratory data
ECG & waveforms
Wearables
Pharmacy
Outcomes
Patient-reported data
Different signals become more useful when they resolve into one coherent clinical picture.
Custom collection

When the dataset doesn’t exist, create the pathway.

Tysena can design retrospective or prospective clinical data collection around a specific research protocol, cohort, modality, or AI-development requirement.

Through healthcare-provider relationships and purpose-built workflows, collection can begin from the question rather than from an existing database.

Define the cohort.Define the modalities.Define the protocol.Build the dataset.
Who we work with

Built for teams advancing healthcare.

AI Research Labs

Training, evaluation, multimodal model development and clinical reasoning.

Life Sciences

Research, evidence generation, biomarker development and clinical programs.

Medical Technology

Algorithm development, validation and product development.

Healthcare Innovators

Clinical research and next-generation healthcare products.

Trust by design

Data usability begins with provenance and trust.

Clinical data requires more than technical access. Every program should be designed around intended use, source provenance, patient rights, privacy requirements, and delivery controls.

Purpose before access. Permission before use.
Patient rights & consentUse-appropriate consent and rights management where required.
Data provenanceSource, collection context, and transformation history understood.
Privacy controlsProject-specific de-identification and access requirements.
Quality assuranceValidation against the agreed specification and clinical logic.
Tysena

Tell us what you’re trying to solve.

If the right clinical data already exists, we’ll help find it. If it doesn’t, we’ll explore how to create it.

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