Atlas — DaedArch operational

The data layer behind every venture decision

136 datasets · 2 million+ records · 41 live query tools. NAICS, SOC, CIP, FIPS, LEI — search, classify, route. The same instrument that powers DaedArch's per-venture pipelines.

136

collections

2.0M

records

82.5K

SOC × NAICS rows (OEWS)

993K

World Bank indicator-rows

394K

open data catalog entries

Operational surfaces

Role finder (SOC)

Title → SOC code → wage, employment, transformation profile.

Industry browser (NAICS)

Code → workforce composition → automation roadmap.

Workflow

Industry × Occupation transform

NAICS + SOC → before/after scenarios + intervention plan.

Workbench

Task automation workbench

Drill into a single task: clearance type, automation feasibility, dependency chain.

Modeling

Butterfly Effect engine

Investment → county-level employment, wage, outcome propagation.

Methodology

Anthropic-vs-Atlas contrast

Per-NAICS run of daedarch.business.atlas_intelligence_v1.

Workforce

Education hub (CIP)

Program → completion → earnings → workforce alignment.

Reference

Data catalog (147 sources)

Every collection, every license, every ingestion timestamp.

How DaedArch uses this

Every venture pipeline that touches industry classification, occupation, or workforce composition reads from Atlas. Tool calls land at /api/v4/execute. Live tools include daedarch.business.atlas_classify_v1 (NAICS backfill), atlas.coverage_dashboard, atlas.data_catalog_dashboard, system.atlas_consolidator (135-collection consolidation into unified_atlas_data), and system.atlas_ground_truth_refresh.

Research narrative for these capabilities lives at trellison.com/atlas. The split: Trellison shows what we found; DaedArch is where you actually do something with it.