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Pipeline Builder for DD Data Ingestion: Connecting Bank-Internal Systems to the Ontology Layer

by Noah Green CPA CFE | May 15, 2026 | DD Tech Lab

Foundry Ontology Design for Counterparty Risk Investigations — Article 001 in this sub-series — established that the ontology layer is the abstraction that insulates the analytical workflow from upstream schema churn. The ingestion layer is where that insulation is...

Workshop Application Patterns for Counterparty Risk Investigators: Single-Pane-of-Glass Investigator Workflows

by Noah Green CPA CFE | May 15, 2026 | DD Tech Lab

What you’ll be able to do after reading this. Recognize the design principles that distinguish a regulator-defensible investigator workflow from a generic data-viewer. Read a Workshop module specification and understand what the analyst sees on screen. Identify...

AIP-Driven Adverse-Media Summarization for DD Engagements: Prompt Patterns, Grounding Strategy, Hallucination Controls

by Noah Green CPA CFE | May 15, 2026 | DD Tech Lab

What you’ll be able to do after reading this. Read an AIP prompt specification and understand what structured output it produces. Recognize the four-gate validation pattern (schema validate, citation substring, hallucination verifier-LLM, insufficient-corpus...

Foundry Actions Framework for Audit-Trail Discipline: Risk-Rating Changes, Regulatory Documentation, and the Examiner-Ready Audit Log

by Noah Green CPA CFE | May 15, 2026 | DD Tech Lab

What you’ll be able to do after reading this. Read an ActionType specification and understand what state change it captures. Recognize the bypass paths that exist in any platform deployment and the controls the institution must add separately. Read an AuditEntry...

Code Repositories in Foundry: When to Embed Python / PySpark in the Pipeline (and When to Stay in Pipeline Builder)

by Noah Green CPA CFE | May 15, 2026 | DD Tech Lab

What you’ll be able to do after reading this. Recognize the decision boundary between no-code Pipeline Builder and code-based Code Repositories. Read a @transform-decorated PySpark function and follow what it does. Identify the audit-metadata columns...

Quiver for Ad-Hoc Counterparty Queries: Lightweight Investigator Tooling Without a Full Workshop Build

by Noah Green CPA CFE | May 15, 2026 | DD Tech Lab

What you’ll be able to do after reading this. Recognize the situations where Quiver is the right tool and where Workshop is. Read a saved Quiver query specification and understand what it returns. Apply a seven-criterion graduation checklist to decide when a...
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