Proof

Real problems, genericized. Real outcomes.

Sector descriptors only — no company names.

Education

From 10,000 students to the 300 that matter

Problem — staff couldn't tell which students actually needed intervention inside a full enrollment of ~10,000.

Built — an attendance-triage system applying trend logic to compress the roster into a ranked, actionable case list.

10,000 → 300

prioritized cases, so limited staff time goes where it changes an outcome

Education

36 pages of regulation into a yes/no

Problem — a 36-page state regulation had to be applied by hand to determine reading-plan eligibility.

Built — an eligibility engine that turns the regulation into a structured decision matrix.

36 pages → 1 matrix

eligibility determinations become consistent and automatic

Business

Vendor data, reconciled overnight

Problem — several vendors delivered data in different spreadsheet shapes, normalized and reconciled into core systems by hand.

Built — a nightly pipeline: ingest, normalize, stage into the ERP with identity resolution, create records and POs, sync downstream to the CRM.

~2 months

the manual reconciliation-and-entry process now runs itself, nightly

Business

Profitability at a glance

Problem — profit and margin lived in manual spreadsheet assembly, always out of date.

Built — a reporting tool aggregating labor, cost, revenue, profit, and margin with configurable date ranges and drill-down.

On demand

margin visibility instead of a rebuilt spreadsheet every time someone asks