AI Tools + Automation.

Most marketing teams keep a list of things they would build if they had an engineer for a week: the tool the sales team keeps asking for, a microsite for one campaign, the report someone assembles by hand every Monday, a translation workflow that stalls at the vendor. I build those. The proof is this site. The Audience Finder searches 950,000 third-party audiences from 287 data providers. The Ad Mockup Generator renders one image into 39 placements. The reference library holds 501 defined terms and 22 platform profiles. The AI, crypto, digital privacy, and PFAS regulation registers track the law by jurisdiction, cited to primary sources. And the homepage, the service pages, and both tools exist in twelve languages, built by a translation pipeline with a style guide and a review pass for every language.

Some of it is visible: calculators, finders, configurators, campaign microsites, and internal utilities, built as plain web software your team can host anywhere. Some of it runs in the background. A script assembles the weekly report from the ad platforms and flags a broken pixel, a paused campaign, or a budget pacing off before a client notices. Content and translation pipelines draft, edit, and localize at volume, with a human editor in the loop and a validator that refuses to publish anything that breaks the rules. And for teams in health, finance, and public affairs that cannot put patient data, deal flow, or client positions into a public model, I set up private and local LLMs.

This is a separate practice from SEO + GEO. That page covers how your brand shows up inside AI answers. This one covers building and running things with AI inside your own operation. The two meet often: the structured data, the machine-readable editions, and the measurement of AI referrals that GEO calls for are usually built with the tooling described here.

The person who plans your media builds the tool. Most internal tool projects die at the specification, when a developer who has never run a campaign builds what the brief says and misses what the team meant. I have twenty years in the work these tools are for, so the first version is usually right about the workflow and the second is the finished one. The scope is marketing and communications: no core product engineering, no systems of record, nothing that belongs with your IT department.

An engagement starts with the workflow you want gone and ends with a working version in your hands, documented so your team owns it. If a tool only makes sense with your data inside a private model, the setup runs on your infrastructure or a dedicated instance, and nothing leaves it.