Build a BODS State-Owned Enterprise Control Chain Visualizer

Parse corporate registry declarations against BODS v0.4 data standards to identify state-owned enterprise structures. Extract government control thresholds and map indirect state ownership paths.

Enhanced due diligence investigator

Ingest BODS v0.4 statement packages containing entity ownership and directorship declarations.

Apply BODS modeling requirements to detect state-owned enterprise markers and government identifiers.

Calculate cumulative indirect ownership percentages to determine absolute state control thresholds.

Render an SOE control chain dossier detailing government influence across corporate hierarchies.

Network visualization showing shared directorships and registered agent clusters with an evidence drill-down panel.

Generate 45 synthetic BODS records showing varying degrees of direct and indirect government ownership. Starter examples below are synthetic. They are not downloaded records.

Beneficial ownership modelling Adheres to BODS v0.4 specific modeling guidance for 'Representing state-owned enterprises' cited in source excerpt 4.

langgraph, networkx, pydantic. LangGraph choreographs multi-step node traversal to evaluate interconnected directorship networks. Local or hosted LLM for drafting investigative findings from raw cluster metrics.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Correctly identifies entities designated as state-owned enterprises via BODS schema.

Calculates cumulative ownership chains to verify absolute government control thresholds.

Generates a structured JSON dossier outlining the state ownership path.

```json [ { "input": { "entity_id": "ENT-990", "name": "National Telecom LLC", "ownership_statements": [ { "interested_party": "GOV-01", "type": "state_body", "shares_exact": 60 } ] }, "expected_output": { "is_soe": true, "controlling_state_body": "GOV-01", "cumulative_state_ownership": 60, "chain_depth": 1 } }, { "input": { "entity_id": "ENT-991", "name": "Local Retail Corp", "ownership_statements": [ { "interested_party": "PER-05", "type": "person", "shares_exact": 100 } ] }, "expected_output": { "is_soe": false, "controlling_state_body": null, "cumulative_state_ownership": 0, "chain_depth": 0 } } ] ```

Assesses structural pattern risks; does not accuse individuals or make automated corporate governance judgments. Use mock external writes. Require human review before any real deployment.