Selected prior work

Proof from systems used inside real operations.

Anonymized examples from prior in-house enterprise roles across AI incident operations, workflow automation, decision intelligence, and data delivery.

Context

These were in-house enterprise initiatives, not independent consulting engagements. They demonstrate the kinds of problems I have helped own and solve, not guaranteed outcomes for future clients.

01AI incident operations

From failure notification to evidence-backed diagnosis

Challenge

When an enterprise reporting workflow failed, its maintainer had to locate the relevant logs, interpret platform and database errors, identify the root cause, and determine the next action. One analyst reported that this investigation could take hours.

Contribution

Designed and built an event-driven triage system in which deterministic automation captures incident metadata and retrieves the correct logs, then a specialized AI diagnostic agent identifies likely causes and cites supporting evidence. Maintainers receive the diagnosis and next action by email, and replies continue the same contextual troubleshooting session.

Result

Following rollout, incidents arrived with enough evidence and guidance that the team did not need to manually investigate failed-refresh logs and could move directly toward resolution without learning a new support process.

Hours → minutesautomated incident diagnosis

02Decision intelligence

An operational model that exposed six figures in avoidable cost

Challenge

Leaders lacked a clear view of a recurring field-operations cost and the levers available to reduce it.

Contribution

Built an explainable operational cost model that connected field behavior to financial impact and made the findings usable by decision-makers.

Result

The analysis identified an estimated $300,000–$500,000 in annual savings opportunity.

$300–500Kmodeled annual savings

03Workflow automation

A recurring reporting task reduced from minutes to seconds

Challenge

A manual report-export and formatting process consumed analyst time every time it ran and varied by operator.

Contribution

Automated the repetitive steps, standardized the output, and packaged the workflow so other teams could adopt it.

Result

Run time dropped from roughly 15 minutes to under one minute and the solution spread to five teams.

15 min → <1 minadopted across five teams

04Enterprise data enablement

A standardized data path made advanced analytics easier to use at scale

Challenge

Analysts needed a more consistent way to connect modern enterprise data infrastructure to the reporting tools already embedded in their work.

Contribution

Helped establish and validate a standardized direct data path, coordinating technical requirements, testing, and adoption across stakeholder groups.

Result

The approved connection pattern became available to more than 1,400 enterprise users.

1,400+users enabled by the standardized path

Figures are based on prior internal analyses and observed workflow results. Scope, inputs, adoption, and outcomes vary.

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