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Test curves
Raw signals, extracted values, preprocessing versions, and interactive plots.
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Data security
PolyCore is built in the EU and runs where your data policy wants it: in an EU cloud, in a private environment, or on your own premises.
FROM UPLOAD TO KNOWLEDGE BASE
PolyCore is designed to move beyond file storage. Mixed uploads can be classified into test data, material datasheets, standards, equipment documents, and reports, so raw files become reusable records instead of passive attachments.
Status labels separate what is already demonstrated from pilot and roadmap capabilities.
Instrument exports, PDFs, Excel files, standards, brochures, reports, and material sheets arrive together.
Raw signals, extracted values, preprocessing versions, and interactive plots.
Uploaded sheets become material context instead of scattered reference PDFs.
Methods and requirements can be stored next to the data they govern.
Machine brochures and device context support traceability and lab setup.
Client-specific questions over uploaded standards, reports, and procedures.
Raw file, curve, metadata, method context, criteria, and export paths stay connected.
PLATFORM POSITIONING
This is the deeper comparison that does not belong on the first landing-page scroll. A LIMS can be excellent for samples, workflow, and audit trails. PolyCore focuses on the raw-signal layer: curves, method context, preprocessing, quality criteria, and reusable material records.
Read the matrix as
Human-readable files and spreadsheets, but weak reuse and repeated reconstruction.
Better traceability and sample workflow, but raw curves often remain attachments.
Raw data becomes a computable material record that can sit above LIMS or act as the platform.
| Question | Manual workflow | Classical LIMS | PolyCore |
|---|---|---|---|
| Where does raw data live? | PDFs, spreadsheets, vendor exports, folders, email, lab PCs, and shared drives. | Often stored as attachments or SDMS objects next to a sample record. | Raw files, curves, metadata, equipment, and standards become one queryable test-data record. |
| What happens to curves? | Viewed once in vendor software, then reduced to a few copied values. | Stored and traceable, but often not analyzable across methods without extra tooling. | Full curves stay central: interactive, comparable, and ready for preprocessing versions. |
| How is context found? | Material sheets, standards, machine brochures, and test files must be matched by hand. | Some metadata is structured; many supporting documents still remain attached or separate. | Classifier-oriented ingestion routes test files, datasheets, standards, and equipment documents into the right places. |
| How do QC and outliers work? | Excel checks, manual thresholds, screenshots, and after-the-fact review. | Workflow gates and audit trails, but method-specific curve logic is usually external or custom. | Method-aware checks can operate on raw curves, scalar values, standards, and customer-specific criteria. |
| Is the data future-ready? | Hard to prove, hard to audit, hard to reuse for ML, FAIR, or Digital Product Passport work. | Audit trails are strong, but FAIR/DPP semantics often require extra modelling. | FAIR-aligned metadata and DPP-ready provenance are part of the record shape from the start. |
| What is the business effect? | Scientists spend paid time moving, naming, checking, copying, and re-explaining files. | Less folder chaos, but raw-signal intelligence still needs extra work. | Repeated data wrangling turns into reusable infrastructure for reporting, ML, audit, and regulation-facing data. |
Manual workflow
PDFs, spreadsheets, vendor exports, folders, email, lab PCs, and shared drives.
Classical LIMS
Often stored as attachments or SDMS objects next to a sample record.
PolyCore
Raw files, curves, metadata, equipment, and standards become one queryable test-data record.
Manual workflow
Viewed once in vendor software, then reduced to a few copied values.
Classical LIMS
Stored and traceable, but often not analyzable across methods without extra tooling.
PolyCore
Full curves stay central: interactive, comparable, and ready for preprocessing versions.
Manual workflow
Material sheets, standards, machine brochures, and test files must be matched by hand.
Classical LIMS
Some metadata is structured; many supporting documents still remain attached or separate.
PolyCore
Classifier-oriented ingestion routes test files, datasheets, standards, and equipment documents into the right places.
Manual workflow
Excel checks, manual thresholds, screenshots, and after-the-fact review.
Classical LIMS
Workflow gates and audit trails, but method-specific curve logic is usually external or custom.
PolyCore
Method-aware checks can operate on raw curves, scalar values, standards, and customer-specific criteria.
Manual workflow
Hard to prove, hard to audit, hard to reuse for ML, FAIR, or Digital Product Passport work.
Classical LIMS
Audit trails are strong, but FAIR/DPP semantics often require extra modelling.
PolyCore
FAIR-aligned metadata and DPP-ready provenance are part of the record shape from the start.
Manual workflow
Scientists spend paid time moving, naming, checking, copying, and re-explaining files.
Classical LIMS
Less folder chaos, but raw-signal intelligence still needs extra work.
PolyCore
Repeated data wrangling turns into reusable infrastructure for reporting, ML, audit, and regulation-facing data.
Positioning note: this does not claim every enterprise LIMS feature is replaced. PolyCore is the raw-data intelligence layer and, where needed, can integrate with existing LIMS infrastructure.
Model workflow impactIMPLEMENTATION ROUTES
Some labs already have a LIMS. Others need the material-data foundation itself. PolyCore supports both routes: an intelligent layer above established systems, or the platform that turns raw curves, standards, documents, and exports into reusable material records.
"I already have a LIMS."
Your LIMS keeps the system of record. PolyCore handles the raw-signal layer above it — full curves, standards-aware analysis, FAIR-aligned records, DPP-ready export. Integrates via REST API.
"I don't have a LIMS yet."
Samples, equipment, standards, documents, and workflows — plus the raw-signal layer, built in. One stack for the full material data foundation, with enterprise integrations added where needed.
ONE RECORD · THREE LANGUAGES
Once the curve is structured, the same record can serve audit, machine learning, and Digital Product Passport preparation without a second data project.
The technical detail moves to the platform page; the homepage only needs the direction of travel.
FAIR-aligned metadata makes test records findable, controlled, and reusable instead of buried in PDF archaeology.
Curves and metadata stay together, so cross-method correlations become queries instead of data engineering projects.
DPP-ready structure keeps material identity, provenance, and exportability in the record as EU requirements evolve.
PolyCore sits above instruments, folders, and LIMS exports. It reads raw outputs, preserves source and method context, applies standards-aware preprocessing, and turns each result into a record your team can compare, audit, reuse, or model.
CSV, Excel, PDF, vendor export, instrument file, or LIMS attachment.
Curve, source file, method, equipment, notes, and version history stay connected.
Normalized records feed QC, comparison, FAIR/DPP export, reporting, and DataFusion.
Raw outputs become usable records, then decision-ready intelligence.
DEPLOYMENT & DATA SECURITY
PolyCore can be operated as a secure European cloud service, as a dedicated environment, or inside customer infrastructure. The deployment model is selected around data residency, access control, backup policy, and integration needs.
European hosting, protected access, managed backups.
Run behind your firewall or on dedicated infrastructure.
EU-first cloud option; on-premise data remains in the customer environment.
No direct server access; authenticated admin routes and role-based use.
Encrypted snapshots and redundant backup paths according to the chosen deployment.
Final validation, contractual security controls, and compliance scope are defined with the customer environment.
One record, ready for audit, Digital Product Passport, and machine learning. Proven at the curve level, not at the sample level.
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