Past Performance

Our prior engagements concentrate in the disciplines that make agent delivery defensible in regulated industries: data quality, master data management, metadata governance, and compliance reporting. Each engagement below produced governed, auditable data systems — the same foundation that production agents depend on to operate safely.

MUFG Union Bank

Enterprise banking — data warehousing, operational and regulatory reporting.
Agent translation: The reporting cycles built on this warehouse are direct candidates for reconciliation and anomaly-detection agents that run continuously against governed data instead of monthly against stale extracts.

Bank of the West

Enterprise banking — regulatory data quality (CCAR).
Agent translation: CCAR-style rule evaluation is one of the strongest surfaces for agent work — explicit checks, regulator-defensible logs, and a clear escalation path when a rule fails. Agents extend the framework into adaptive, self-monitoring checks without losing traceability.

Toyota Financial Services

Automotive finance — metadata governance and data cataloging.
Agent translation: Metadata governance is the prerequisite for safe agent action on enterprise data. The Core Data Element discipline established here is exactly the input contract that lets agents read and write against production systems without breaking trust.

Sherwin-Williams

Manufacturing / consumer goods — data quality program.
Agent translation: Encoded Collibra rules become the specification for a remediation agent — the rule defines correctness, the agent performs the fix-on-failure step that previously consumed analyst hours.

McGrath RentCorp

Equipment rental and modular buildings — master data management.
Agent translation: Business glossary terms become the shared vocabulary multiple coordinating agents must agree on. The governance scaffolding built here is foundational to deploying an Agent Pod across more than one source system.

Academic Search

Higher-education non-profit — data quality.
Agent translation: Demonstrates we deliver enterprise-grade DQ tooling at smaller scope and budget — the same shape of work that now fits inside a single Agent Pod engagement rather than a multi-quarter program.

Abbott Laboratories (current)

Medical devices — Salesforce data deduplication and cross-system impact analysis.
Agent translation: Deduplication and cross-system impact analysis is the canonical Single Agent Build workflow — high-volume, rule-bounded, currently consuming senior analyst time, with a clear human-in-the-loop checkpoint before any destructive action.

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