The data acquisition
pipeline for multimodal
representation learning.

Seam collects, processes, and stores multimodal training data for the Alloy unified representation model. It handles 1D time-series signals, 2D imagery, and 3D spatial data — feeding a unified representation that enables cross-modal reasoning.

Seam orchestrates the full data lifecycle: ingestion from diverse sources, storage tiering across hot, warm, and cold layers, and preprocessing pipelines that prepare raw signals for Alloy's coordinate-value tokenization. The architecture is designed for scale — new modalities plug in without restructuring the pipeline.

Relationship to the stack: Seam provides the data that Alloy learns from, and Alloy's representations inform the intelligence substrate that Stratum's architecture operates on.