STRATA 2.0: Distributed Intelligence Architecture

@techreport{cnl2026strata, author = {}, title = {STRATA 2.0: Distributed Intelligence Architecture}, institution = {Canemah Nature Laboratory}, year = {2026}, number = {CNL-TN-2026-043}, month = {april}, url = {https://canemah.org/archive/document.php?id=CNL-TN-2026-043}, abstract = {STRATA 2.0 evolves the existing STRATA intelligence engine into a distributed research service spanning the Canemah Nature Laboratory's Tailscale mesh network. The current STRATA system on Galatea (Mac Mini M4 Pro) provides 13 temporal micro-agents, 7 context builders, 25 tool-calling endpoints, a 4-domain privacy model, and a personality system for narrative interpretation of Macroscope sensor streams. Analysis of this codebase reveals a clean four-layer architecture with minimal coupling to the web application, making extraction into a standalone service architecturally straightforward. The distributed architecture uses a hybrid approach: a shared PHP library on Galatea for co-located projects (MNG, production services), wrapped in a thin HTTP API for remote access by Data and other nodes over Tailscale. A plugin dispatch layer extends this across the mesh network, routing intelligence requests to specialized nodes: Galatea for data authority and cloud AI, Data for development and local inference via Ollama, Sauron for GPU compute (3DGS, ML training), and Hogwarts for vision processing (YOLO, camera services). STRATA\_Bench, the structured investigation lab bench built on a 14-table strata\_db schema with a seven-phase scientific workflow, becomes the primary consumer of this distributed service. The lab notebook captures every operation as a publishable primary dataset, with investigations flowing to Science with Claude (SWC) for public presentation. Together, these components form a complete observation-to-publication pipeline operating across federated databases and distributed compute nodes.} }