Science & Health
Evidence, protocols and clinical documentation.
Health and research data is structured in the middle and unstructured at the edges: encounters, results and measurements on one side, notes, protocols and images on the other. Neither half is much use without the other.
Evidence, protocols and clinical documentation.
Where this industry runs.
The environments in this industry, where a structured record and a document are almost always asked for in the same request and governed by the same access rules.
- Healthcare Clinical records, encounters, observations, orders and results.
- Life Sciences Experiment records, instrument data, sample lineage and publications.
- Pharmaceuticals Trial data, batch records, regulatory submissions and pharmacovigilance.
- Scientific Research Instrument output, simulation results, reference material and datasets.
- Engineering Drawings, models, bills of materials, test results and project records.
From the measurement to the evidence around it.
Evidence, protocols and clinical documentation held with the measurements they qualify. Four readings of the same system: the environments that measure, the shapes the data takes, the layer that holds evidence with its measurements, and the questions answered from it.
The contexts this industry runs in.
- Healthcare Clinical records, encounters, observations, orders and results.
- Life Sciences Experiment records, instrument data, sample lineage and publications.
- Pharmaceuticals Trial data, batch records, regulatory submissions and pharmacovigilance.
- Scientific Research Instrument output, simulation results, reference material and datasets.
- Engineering Drawings, models, bills of materials, test results and project records.
The shapes the data takes across them.
- SQL Records, keys and joins
- JSON / documents Documents and nested objects
- Time series Measurements and events in time order
- Objects Large assets with queryable metadata
- Events Operational events as they happen
Where the shapes stop being separate systems.
- One plan per request
- Snapshot reads under continuous writes
- One storage contract
The questions asked across the industry.
- Patient timeline
- Results with context
- Documentation stays findable
- Equipment and operations
One layer holds these shapes at once, which is what removes the copy between them: an event, the record it belongs to and the document around it are read from the same place, whichever environment is asking.
How evidence is reached, model by model.
The work, the shapes it names, and the path a request takes to reach them — documents and measurements first, retrieval surfaces where the roadmap carries them.
What runs against this data.
- Encounters and observations
- Clinical documentation
- Orders and results
- Patient and organisation records
- Instrument measurements
The shapes those workloads read and write.
- SQL
- JSON / documents
- Time series
- Objects
- Events
- Vector
One path from a request to the data it names.
- Planning Predicates narrow the work before it runs
- Execution Records, fields and windows answered together
- Transactions Readers and writers do not block each other
How the work reaches the layer.
- SQL surface The query language the layer is documented in
- Applications Services and jobs writing and reading as they run
- Analytics & AI clients The same layer, the same access path
What runs once the evidence is held.
The work comes after the evidence: protocols, trials and revisions drawn from every environment here. Choose one to see the shapes it moves and where it lands.
Visits, measurements, vitals and administered care. — Healthcare
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Notes, reports, referrals and correspondence. — Healthcare
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Requests, specimens, results and acknowledgements. — Healthcare
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Patients, practitioners, departments and their relationships. — Healthcare
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Readouts from sequencers, plate readers and imaging instruments. — Life Sciences
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Samples, aliquots, protocols, versions and operators. — Life Sciences
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Notes, annotations, images and derived results. — Life Sciences
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Publications, citations and internal reference material. — Life Sciences
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
The parts of the layer this industry leans on.
Counted across the environments above rather than chosen for this page: the properties every environment in this industry depends on, and the workload answers they keep returning to.
- Documents beside rows Fields that keep changing shape stay queryable instead of being exported into a separate document store.
- One data layer Rows, documents and time-ordered events live in one system, so a question is asked once instead of once per store.
- Retrieval as an access path Similarity search arrives as another way into the same data rather than a second copy to keep in step.
- Objects with queryable metadata Large assets are found by a query against their metadata rather than by a naming convention.
- Deployment is a decision Self-hosted, edge and managed topologies are design destinations of the deployment fabric, and the fabric is specified as its own part of the platform.
- Snapshot reads under continuous writes Readers and writers do not block each other, which is what makes a telemetry feed and an application share one system.
Solutions this industry keeps returning to.
Derived from the industry's own environments: the solutions referenced by the most of them, each one a page of its own.
- Document Intelligence → Documents, their fields and their attachments treated as queryable data. Referenced by 5 of 5 environments.
- Knowledge Systems → Entities and relationships made queryable rather than reconstructed at read time. Referenced by 4 of 5 environments.
- AI Retrieval → Similarity search and context assembly over documents, records and events. Referenced by 4 of 5 environments.
- Operational Analytics → Reporting that reads the operational source instead of a copy of it. Referenced by 4 of 5 environments.
- Data Infrastructure → One layer for records, documents and time-ordered data, instead of one system per shape. Referenced by 4 of 5 environments.
- Enterprise Search → One search surface over records, documents, events and their metadata. Referenced by 1 of 5 environments.
- HealthcareClinical records, encounters, observations, orders and results.
- Life SciencesExperiment records, instrument data, sample lineage and publications.
- PharmaceuticalsTrial data, batch records, regulatory submissions and pharmacovigilance.
- Scientific ResearchInstrument output, simulation results, reference material and datasets.
- EngineeringDrawings, models, bills of materials, test results and project records.
Evidence stays with its measurements.
Tell us which labs, trials and registries you run and who has to trust the record later. We will map them to the workloads, the shapes and the parts of the layer that carry them.