Business impact / verified outcomes

Transformation that survives contact with operations.

The recurring pattern: identify the constraint, frame the systems opportunity, build or guide the intervention, bring people through adoption, and measure the operating result.

Start with the flagship case →View resume

Case ledger

Evidence, not AI theater.

Flagship case · Quality operations

QA review automation

Operating context: A live customer-support operation where quality review was necessary but time-intensive.
Intervention: Designed and deployed an automation pipeline, including implementation, rollout, frontline adoption, and measurement.

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~70%reduction in quality-review time

Service transformation · Google Fiber support

Multichannel response-time transformation

Operating context: A 30+ agent OneSupport operation serving Google Fiber across voice, email, and social channels.
Intervention: Worked with Google engineering stakeholders on automation and social-listening workflows that improved signal detection and response routing.

26+ hrs → <10 minmultichannel response time

Scale leadership · Disney+ launch

Operating discipline at launch scale

Operating context: A major launch requiring rapid scale, consistent execution, and clear management signals.
Intervention: Led 450 FTEs through 10 direct-reporting managers using data-driven coaching, QA dashboards, and operational reporting.

23%CSAT improvement; preferred-partner status earned

Decision support · Workforce planning

Forecasting tied to staffing decisions

Operating context: Demand across Google Fiber support channels required proactive capacity planning.
Intervention: Built workforce-forecasting models and incorporated their output into staffing and capacity decisions.

~92%forecast accuracy

AI enablement · Knowledge operations

A knowledge assistant grounded in frontline work

Operating context: OneSupport agents needed consistent access to structured, reviewable operational knowledge.
Intervention: Coordinated with IT and owned requirements, data curation, rollout, and frontline adoption for an RLHF-powered knowledge assistant.

2,100+curated Q&A pairs deployed; no downstream performance metric is claimed

Operator who builds

The business judgment is backed by direct technical execution.

Since February 2024, I have built multi-agent workflows, model-routing services, retrieval systems, governance tools, and human-in-the-loop controls through StackBilt. The work is public so engineering audiences can inspect the implementation.

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