Detect → Fix → Deploy → Verify: The AppScan AI Closed Loop

Why measurement alone is not enough

AI visibility tools excel at answering “Are we being mentioned?” — but most stop when the dashboard turns red. Security scanners excel at “What is misconfigured?” — but rarely connect to your ship cadence or prove a fix worked.

AppScan AI is built around a closed loop: detect gaps across AI visibility, security, and uptime; export developer-ready fix packs; trigger checks when you deploy; and verify scores improved — with portfolio rollups and weekly reports for teams managing more than one site.

This guide walks through each step using AppScan AI product features. If you only need conceptual background on AI visibility or security audits, see our [AI visibility tracking guide](/resources/ai-visibility-tracking-guide) and [website security audit guide](/resources/website-security-audit-guide).

Step 1 — Detect (visibility, security, uptime)

When you add a site, AppScan queues your first security audit automatically and starts uptime monitoring. You do not need a separate “run first audit” step.

AI visibility checks run on your plan schedule (daily on Starter and above). Track mention rate, citation rate, and share of voice vs named competitors on buyer-intent prompts.

Weekly automatic security audits run every 7 days per site (opt-out via the site detail toggle). Audits respect your plan’s monthly audit limit and stagger across weekdays so every site is not scanned on the same day.

Uptime monitoring runs continuously with SSL expiry and incident alerts via email, Slack, Discord, or alert webhooks.

• Dashboard → add site → first audit + monitoring start automatically
• Site detail → enable or disable weekly automatic audits
• AI Visibility tab → prompt library, fan-out, on-demand checks
• Portfolio view → rollup health, SSL risk, visibility drops across all sites

Step 2 — Fix (Fix Pack export)

Every audit and AEO finding includes a Fix Pack Export panel. Choose a format tailored to how your team ships:

Cursor / Lovable — paste-ready instructions for AI coding tools. GitHub Issue — formatted ticket body (link a repo in site settings for one-click creation). PR description — summary block for your pull request template.

Fix packs include severity, affected URL, remediation steps, and enough context that an engineer or AI assistant can implement without re-reading the full audit report.

Step 3 — Deploy (CI/CD webhook)

Alert webhooks (Slack, Discord, custom URLs) notify your team when something breaks. Deploy webhooks are different: they tell AppScan a fix shipped so we can capture a post-deploy snapshot and queue verification.

On each site’s detail page, open Deploy Change Monitoring, generate a webhook secret, and POST from your pipeline after a successful deploy:

• URL: `POST https://www.appscanai.com/api/assets/{site-id}/deploy`
• Header: `X-Deploy-Secret: your-secret`
• Optional JSON body: `{ "source": "github-actions", "branch": "main", "commit_sha": "…" }`
• First deploy for a site captures a baseline; later deploys diff security headers, scores, and critical findings

Step 4 — Verify (remediation timeline)

The Fix & Verify Timeline on each site tracks findings from detection through fix deployed to verified. When you ship a fix and notify AppScan via deploy webhook or “Record Deploy”, verification audits can confirm scores and issue counts improved.

This is how you answer executive questions like “Did the last sprint actually make us safer?” — not just “Did we close tickets?”

Reports & portfolio for agencies

Weekly and monthly reports combine security audit summaries with uptime context (sites up, open incidents, avg uptime) and AI visibility activity when checks ran in the period. Even quiet weeks still show monitoring health.

The Portfolio dashboard rolls up every site in your org: sites down, SSL expiring soon, critical security issues, AI visibility drops, and AEO gaps — designed for agencies and teams managing multiple properties without logging into each site separately.

How AppScan AI compares to AI visibility-only tools

Pure AI visibility products often win on prompt volume, engine coverage, or sales-intent categorization. AppScan AI’s advantage is operational completeness: you measure visibility *and* fix the pages, headers, and performance issues that cause citations to drop — with proof after deploy.

You replace a stack of point tools (AI monitoring + uptime + security scanner + manual reporting) with one subscription that closes the loop.