Systems that work in the real world.

A veteran-founded firm needs to earn trust and get found. Generic templates do not build trust, and the firm was invisible when a client asked an AI engine who to hire.

A heritage-driven brand in dark green and gold that honors the founder’s military and law-enforcement background, over a citation-ready architecture: a LegalService entity for the firm and its founder, FAQ answers that cite the actual Florida statutes (Fla. Stat. § 95.11, the 2023 HB 837 reforms), and Bar-compliant disclosures on every page.

A Bar-compliant site built to be cited: statute-cited FAQ, interlinked practice-area pages across probate, estate planning, personal injury, and contracts, and a consultation-driven contact form with click-to-call.

A beautiful Miami real estate site, built by another team, looked complete but was invisible to AI search. It was a browser-rendered single-page app that shipped an almost empty HTML shell to crawlers, and the forms collected leads that then went nowhere.

The design stayed; the foundation changed. We ported it to a static, server-rendered build so the full page and its structured data reach the crawler, added a RealEstateAgent, Person, and WebSite entity graph with answer-ready FAQ, and wired every form to automated nurture with an AI concierge on every page.

A site that reads and converts: server-rendered pages an AI engine can cite, three automated nurture workflows behind every form, branded lead-magnet guides, and live MLS search kept intact.

Product, fitment, and repair knowledge lived in a five-figure SKU catalog and thousands of manual pages that only a few veteran staff could navigate. Cloud AI was ruled out because the data could not leave the company.

A private assistant on a single GPU server they own: a local language model, a guardrailed chat application, and a vector index over ~44,000 manual passages, reading the live catalog through a read-only connection. Nothing leaves the network.

91% accuracy against an 80% target, fitment lookups in about 11 seconds instead of 3 to 8 minutes, zero business data leaving the perimeter, and approval to move into production.

The pilot was built for a few testers on a closed network. Customer Service and Sales needed company sign-on, answers for up to 30 people at once, and new kit-contents questions, without any data leaving the building.

HTTPS through a reverse proxy, single sign-on through the company’s Entra ID, a vLLM engine built for many users on the same GPU with the old engine kept as rollback, kit and bill-of-materials skills, their branding, and an IT handoff.

15 of 15 security checks and 19 of 19 accuracy checks on the production build. A 12.6-second median full answer with 30 users at once, against a 15-second target. No new hardware.