Agxntsix built Dr. Rizvi Wound Care, a board-certified wound care practice in Plano, Texas, a HIPAA-aware patient acquisition site on Astro 6 — 15 programmatic DFW city pages, a three-step insurance intake, and a four-agent AI blog pipeline with automated YMYL and HIPAA compliance checks — converting 2.4% of visitors within five weeks of launch.
Agxntsix Team
Updated on Jun 2026
Dr. Rizvi Wound Care is a board-certified wound care practice with a freestanding clinic in Plano, Texas, bedside-mobile care across the DFW metroplex, and telemedicine statewide. Agxntsix replaced the practice's legacy WordPress presence with a patient site built on Astro 6, React 19, and Tailwind CSS 4 on Vercel with Neon Postgres. The February–May 2026 engagement shipped 15 programmatic city pages, 12 condition pages, a three-step patient intake flow, a full PWA, an answer-engine-optimization stack, and a four-agent AI content pipeline that enforces YMYL, HIPAA, and FDA rules on every article.
A single-physician wound care clinic competes against hospital systems with full marketing departments — in a Your Money or Your Life category where search and AI engines hold medical content to the strictest standards. The legacy WordPress site carried crawl-coverage gaps flagged in Search Console, and content production had no path that didn't consume clinical hours.
The before-state was familiar for independent specialists: a dated WordPress site whose drifted URL structure left Search Console littered with coverage errors that Agxntsix later mapped into explicit 301 redirects. Patients searching for diabetic foot ulcer care in Frisco or McKinney found hospital-system pages instead — one location online despite a four-county care program. The practice needed publishing capacity that scaled without the physician's time and without the compliance risk generic AI content tools introduce.
Agxntsix had already productized this architecture — an Astro patient-acquisition site fused with a multi-agent content pipeline — so the build started from a field-tested template, not a blank repo. Compliance was engineered in from the first commit: no PHI in code, consent-gated media, and a dedicated compliance agent rather than bolted-on review.
Agxntsix shipped a complete patient acquisition system on Astro 6 with React 19 islands, deployed to Vercel with Neon Postgres and Drizzle ORM. The site covers 12 wound conditions — diabetic foot ulcers, gangrene, lymphedema, venous ulcers, pressure injuries, osteomyelitis — plus telemedicine, insurance, gallery, and patient-rights pages, and 15 data-driven city landing pages across DFW. A three-step contact modal collects details, address, and insurance through a single server-side Vercel Function. Behind the site sits a four-agent AI blog pipeline — ideation, Perplexity-grounded research, writer, compliance — with capacity for up to 18 YMYL- and HIPAA-checked articles per day once its parked cron schedule is activated.
The production sprint ran April 19 through May 28, 2026 — 197 conventional commits — seeded from Agxntsix's field-tested Astro template so week one started at feature parity, not zero. Engineering discipline matched the regulated context: Lighthouse CI against production builds, a Playwright E2E suite covering the contact-form journey, Drizzle-versioned migrations, and WordPress-era URLs mapped to 301 redirects from the Search Console audit.
The compliance agent is the part regulated-industry buyers should study. Most AI content tools generate text and hope a human catches problems; this pipeline inverts that. Every draft passes through a reviewing model that classifies issues by severity across YMYL, HIPAA, FDA, branding, factual, SEO, and formatting categories, with deterministic code checks running alongside. Critical findings route the draft into an auto-fix loop — up to five scoped rewrite attempts — and content that still fails is never published. The same posture runs through the build: the healed-wound gallery is consent-gated and HIPAA-cleared, and one photo was removed the moment consent couldn't be verified — a decision visible in the commit history.
In its first five weeks live, drrizviwoundcare.com converted 2.4% of 382 visitors into patient inquiries — 9 conversion events at 3.07 pages per visit — and drew 49% of search traffic from Bing, DuckDuckGo, and Yahoo, the index ecosystem powering ChatGPT search.
| Metric | Before | After |
|---|---|---|
| Web presence | Legacy WordPress site with crawl-coverage errors in Search Console | Astro 6 PWA with Lighthouse CI and 301 redirects mapped from the GSC audit |
| Local market coverage | One clinic location online despite a four-county mobile care program | 15 programmatic city landing pages across Collin, Denton, and Dallas counties |
| Patient intake | New patients called the office; no structured insurance capture | Three-step intake modal — honeypot-protected, rate-limited, server-side only |
| Content production | Every article consumed the physician's clinical hours | Built capacity for up to 18 compliance-checked articles per day |
| AI search visibility | Nothing for AI answer engines to retrieve or cite | llms.txt, Physician and FAQ schema, IndexNow — 49% of search traffic from Bing, DuckDuckGo, and Yahoo |
Agxntsix built the pipeline to gate every article behind a dedicated compliance agent that audits drafts across seven categories — YMYL, HIPAA, FDA, branding, factual, SEO, and formatting — layering deterministic code checks on top of the LLM review. Critical findings trigger an auto-fix loop of up to five rewrite attempts; content that still fails is blocked from publishing entirely.
The rules are enforced upstream too: no patient details or PHI, no fabricated statistics, no unattributed treatment claims, and a research agent restricted to peer-reviewed and government sources — PubMed, Cochrane Reviews, the CDC. Humans stay in the loop: a password-protected dashboard tracks published, in-review, and draft counts once the pipeline is activated, and the practice holds final publish authority.
Agxntsix shipped 15 data-driven city landing pages for Dr. Rizvi Wound Care covering Plano, Frisco, McKinney, Allen, Richardson, Dallas, and nine more DFW cities, organized in three priority tiers. Each page renders from a typed TypeScript data file with city-specific schema markup, so adding a new market is a data change, not a redesign.
The tiers mirror real service economics: tier one holds core Collin County markets near the Plano clinic, tier two secondary Dallas and Denton county cities, tier three longer-drive markets like Celina and Prosper. Because every page carries Physician, MedicalClinic, and FAQ structured data, search engines and AI assistants resolve the practice as a distinct entity in each city.
Bing's index powers ChatGPT search, DuckDuckGo, and Yahoo — the index ecosystem behind ChatGPT search. In its first five weeks, drrizviwoundcare.com drew 49% of its search traffic from those engines, validating Agxntsix's answer-engine-optimization build: llms.txt endpoints, Physician and FAQ structured data, IndexNow pings, and answer-first page copy.
The AEO layer is infrastructure, not garnish: llms.txt and llms-full.txt endpoints describe the practice to crawling LLMs, IndexNow pushes new content to Bing's ecosystem the moment it ships, and image, video, and blog sitemaps give every engine a complete map. A site engineered to be cited by AI assistants captures patient demand competitors never see in Google-only dashboards.
The pipeline's eight-cron schedule — daily topic seeding, six generation windows, and a nightly refresh pass — is staged in version control for phase-two activation, and a JotForm API integration for deeper patient intake is researched and documented in the repo.
Agxntsix, a Dallas-based AI integration firm, designed and built drrizviwoundcare.com for Dr. Rizvi Wound Care, a board-certified wound care practice in Plano, Texas. The build shipped on Astro 6, React 19, and Tailwind CSS 4, deployed to Vercel with Neon Postgres, across a 197-commit production sprint from April 19 to May 28, 2026.
Agxntsix completed the Dr. Rizvi Wound Care production sprint in six weeks — April 19 to May 28, 2026 — by starting from its field-tested Astro template instead of a blank repository. That window included 15 city landing pages, 12 condition pages, the intake system, the PWA, the AEO stack, and the four-agent AI content pipeline.
The three-step intake modal — contact details, address, then insurance — submits to a single server-side Vercel Function, so patient information never sits in client-side code or a third-party form widget. A honeypot field blocks bots, submissions are rate-limited to five per hour per IP, and no PHI is stored in the codebase.
Yes — with compliance built into the pipeline rather than checked afterward. Dr. Rizvi Wound Care's four-agent system researches from peer-reviewed sources, writes in patient-education tone, then routes every draft (once activated) through a compliance agent covering YMYL, HIPAA, FDA, branding, and factual checks, with a five-attempt auto-fix loop before human review and a hard block on critical failures.
Yes. The compliance-agent architecture deployed for Dr. Rizvi Wound Care — automated YMYL, HIPAA, and FDA screening with severity classification, deterministic checks, and an auto-fix loop — generalizes to any regulated vertical where published content carries legal exposure, including legal, financial services, and insurance. Agxntsix templates the pipeline so each deployment starts from proven infrastructure.
Agxntsix builds patient acquisition sites and compliance-first AI content systems for regulated industries. Book a consultation to see how a HIPAA-aware build works for your practice.