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Provenance & defensibility

Every number says what produced it

Content-addressed results, manifests that record the kernel, inputs, parameters, actor and toolchain, and structured refusals instead of plausible-looking answers — so a technical review can verify rather than trust.

The review dossier: what ran, with what and by whom — and the decisions it was bound to.

Target audience

Competent Persons, technical reviewers, auditors, due-diligence teams, QA/QC leads, and regulators.

Platform capabilities

Content-addressed artifacts — the same job returns the same result identity
Manifests recording kernel digest, input identities, parameter hash, randomness root, and actor
Lineage graphs walked from manifests alone
Units, support, and epistemic class declared per attribute
Source database, tables, analyte, and drilling recorded at capture
Structured refusals with code, category, and stage — never prose to parse
Stored results re-verified on every read

Business benefits

Shorten technical review by making claims checkable
Survive due diligence with evidence rather than recollection
Catch invalid work at submission instead of in the report
Keep interpretation, computation, and classification clearly separated

Screenshot gallery

The screens that support this workflow, shown in the working application.

Mapping profiles are approved once by a reviewer; only an approved profile can load data.
Collars staged and validated row by row — nothing touches the domain until the file is committed.
Groundrush, a public open-file gold project: 113 drillholes in 3D around the vein shell solved from their logged contacts.

Compare this workflow with the full platform

Explore adjacent capabilities in AI agents, data management, remote sensing, 3D visualization, and enterprise GIS.

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Reproducible Geoscience, Provenance & Technical Audit | SpatialTechSolutions