{
  "id": "okf_vamsiramakrishnan_ge_agent_factory_okf_s_6555aa68",
  "kind": "okf",
  "category": "dados",
  "name": "Supplier Risk Scoring Engine",
  "tagline": "Multi-factor ML model integrates financial (RapidRatings), cyber (BitSight), operational (Resilinc), and credit (Moody's) data. LLM synthesi",
  "body": "# Supplier Risk Scoring Engine\n\n> A-1601 • Supplier Risk\n\n## Overview\n\n- **Persona:** Supplier Risk Analyst\n- **Department:** procurement\n- **Objective:** Multi-factor ML model integrates financial (RapidRatings), cyber (BitSight), operational (Resilinc), and credit (Moody's) data. LLM synthesizes individually minor signals — small D&B downgrade + executive departure + declining OTIF — into distress pattern narratives. so the Supplier Risk Analyst can move the Risk signal sources KPI.\n\n## KPI summary\n\n- **Risk signal sources**: 2-3 manual checks → 7 automated feeds\n- **Score refresh cycle**: Quarterly → Continuous\n- **Early distress detection**: After disruption → 3-6 months advance\n\n## Contents\n\n- [Playbook — role, scope, guardrails](/playbook.md)\n- [Source Systems](/systems/index.md)\n- [Data Entities](/tables/index.md)\n- [Agent Tools](/tools/index.md)\n- [Workflow Stages](/workflow/index.md)\n- [Query Capabilities](/queries/index.md)\n- [Eval Scenarios](/tests/index.md)\n- [Source Docume",
  "url": "https://github.com/vamsiramakrishnan/ge-agent-factory/blob/HEAD/okf/supplier-risk-scoring-engine/index.md",
  "status": "live",
  "origin": "okf_github",
  "origin_id": "vamsiramakrishnan/ge-agent-factory:okf/supplier-risk-scoring-engine/index.md",
  "install": "https://raw.githubusercontent.com/vamsiramakrishnan/ge-agent-factory/HEAD/okf/supplier-risk-scoring-engine/index.md",
  "source": "https://github.com/vamsiramakrishnan/ge-agent-factory",
  "transporte": "",
  "ns": "vamsiramakrishnan",
  "versao": "0.1",
  "oficial_status": "",
  "repo_host": "github.com",
  "topico": "gov",
  "linguagem": "TypeScript",
  "licenca": "",
  "repo_topics": "",
  "repo_slug": "vamsiramakrishnan/ge-agent-factory",
  "stars": 3,
  "forks": 0,
  "prs_abertos": 0,
  "pushed_at": "2026-09-06T09:45:38Z",
  "repo_estado": "ativo",
  "likes": 0,
  "comments": 0,
  "visits": 0,
  "readme_bytes": 8390,
  "readme_api": "https://agentalog.com/api/listings/okf_vamsiramakrishnan_ge_agent_factory_okf_s_6555aa68/readme",
  "readme_fonte": "repo",
  "created_at": "2026-09-09 05:06:57",
  "updated_at": "2026-09-09 05:06:57",
  "mine": false,
  "api": "https://agentalog.com/api/listings/okf_vamsiramakrishnan_ge_agent_factory_okf_s_6555aa68",
  "go": "https://agentalog.com/api/go/okf_vamsiramakrishnan_ge_agent_factory_okf_s_6555aa68",
  "comments_api": "https://agentalog.com/api/listings/okf_vamsiramakrishnan_ge_agent_factory_okf_s_6555aa68/comments",
  "readme_sha": "7fbaefc209df1acdec2972843a4123881c439b171522868ec725583bda311744",
  "readme_em": "2026-09-14 00:35:17",
  "payload": {
    "name": "vamsiramakrishnan/ge-agent-factory:okf/supplier-risk-scoring-engine/index.md",
    "title": "Supplier Risk Scoring Engine",
    "version": "0.1",
    "okf_bundle_dir": "okf/supplier-risk-scoring-engine",
    "okf_index_path": "okf/supplier-risk-scoring-engine/index.md",
    "okf_conceitos": 13,
    "okf_ref": "HEAD",
    "okf_type": "Knowledge Bundle"
  },
  "volatil_em": "2026-09-14 04:11:41"
}