WAV Enterprise BOM Configurator interface
Live product

WAV Enterprise BOM Configurator

The problem

Quoting network gear across hundreds of SKUs from multiple vendors (Ubiquiti, Cambium, RUCKUS, TP-Link) ran through a manual, back-and-forth, spreadsheet-based process between sales reps and engineering.

What I built

A guided, 10-category JavaScript bill-of-materials configurator for WAV Online. Users browse access points and network gear across four hardware brands, build a full parts list with live quantities and pricing from hundreds of engineer-vetted SKUs, and walk away with a ready-to-quote configuration.

Outcome

Eliminated a 2–4 hour engineering research bottleneck per customer quote, replacing it with a self-serve flow a rep or customer completes in a few clicks. Live in production at wav.com.

JavaScriptNetSuite ERPMulti-vendor SKU data
GEO Visibility Analyzer scorecard interface
AI SEO

GEO Visibility Analyzer

The problem

Most SEO tooling still optimizes for classic ten-blue-links rankings. It has no answer for whether a brand actually gets found and cited inside AI-generated answers on Google SGE, Perplexity, SearchGPT, or Claude.

What I built

A tool that scores any page for AI-search visibility. It grounds the score in live citation checks, search indexation data, and Core Web Vitals, then returns a prioritized action plan for improving how AI engines discover and cite the content.

Under the hood

Built on the Anthropic API — Claude Sonnet for the analytical scoring, Claude Haiku for cost-sensitive demo runs. A separated system/user prompt architecture with a multi-layer fallback parser solved a recurring double-encoded JSON bug from the first version.

Status

Currently being rebuilt as a standalone PHP tool, independent of WordPress, so it runs the same way regardless of what the rest of the site is built on.

Anthropic APIClaude Sonnet + HaikuCore Web VitalsPHP (in progress)
Marketing Analytics — dashboard screenshot goes here
Campaign analytics

Marketing Analytics

The problem

Campaign performance data lived scattered across platforms, with no single view of what was actually working or what to do next.

What I built

A tool that turns raw campaign data into KPI insights and a prioritized next-best-action list, diagnosing performance instead of just reporting it.

Placeholder: this section needs the most detail added. What data sources feed it, what decisions has it actually driven, any before/after metric.

Campaign dataKPI diagnostics

Want the credentials behind this?

54 active certifications across Anthropic, Coursera, Google, HubSpot, LinkedIn/AMA, SEMRUSH, and Udacity.

See credentials