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The Data Layer

EOSYN Fabric™

Cleans, calibrates, harmonizes, and structures raw inputs into model-ready geospatial intelligence assets.

Overview

What It Does

Raw satellite and sensor data is noisy. Atmospheric interference, sensor calibration drift, geometric misalignment, and format inconsistency make raw data unsuitable for direct use in AI models or institutional decision-making. EOSYN Fabric is the data layer that transforms raw inputs into model-ready geospatial intelligence assets.

Fabric applies atmospheric correction (removing haze, aerosol, and water vapor interference), geometric alignment (ensuring pixel-level spatial accuracy across sources and time), format harmonization (converting heterogeneous data formats into a unified structure), and resolution standardization (normalizing data to consistent spatial and temporal resolutions). Every transformation is logged in a provenance record — an immutable audit trail showing exactly what data was used, what corrections were applied, and when.

The output of Fabric is a harmonized data cube — a multi-dimensional array of geospatial data that is spatially aligned, temporally consistent, and quality-scored. This data cube is the input to EOSYN Core's GeoAI models. The provenance records attached to every data cube mean that any EOSYN output can be traced back to its source data — a requirement for institutional auditability and regulatory compliance.

Capabilities

Key Capabilities

  • Atmospheric Correction

    Haze, aerosol, and water vapor interference removal

  • Geometric Alignment

    Pixel-level spatial accuracy across sources and time

  • Format Harmonization

    Unified structure from heterogeneous data formats

  • Resolution Standardization

    Consistent spatial and temporal resolutions

  • Provenance Tracking

    Immutable audit trail of all transformations

  • Quality Scoring

    Automated quality assessment of every data cube

Deliverables

Example Deliverables

Example deliverables for EOSYN Fabric™
DeliverableDescription
Harmonized Data CubesMulti-dimensional, spatially-aligned, quality-scored data arrays
Calibration LogsDetailed records of all corrections applied
Provenance RecordsImmutable audit trail from source to output
Quality ReportsAutomated quality assessment documentation
Metadata CatalogSearchable metadata for all processed data

The Stack

How It Connects

Data flows upward through the stack: Orbit sources raw signals, Fabric harmonises them into measurement-grade data cubes, Core generates confidence-scored intelligence, and Atlas delivers decisions into client systems.

Ready to explore EOSYN Fabric™?