Top SitesAidoc | Clinical AI Solutions for Healthcare Providers

Machine Readiness

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55

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unknown

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Readable docs

robots, llms

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Document

robots.txt

Open robots.txt
User-agent: *
Disallow: /wp-admin/
Allow: /wp-admin/admin-ajax.php

Allow: /llms.txt

Disallow: /internal-docs/

Document

llms.txt

Open llms.txt
aidoc.com | llms.txt

# Overview
Aidoc provides AI-powered radiology and clinical workflow solutions. Its portfolio of FDA-cleared modules is designed to support clinicians in detecting acute findings and orchestrating workflow across service lines. Site content must emphasize compliance, safety, and clinical utility while scaling organic visibility.

# Audience & Personas
- Radiologists & ED physicians: accuracy, speed, clinical confidence.
- Hospital executives & operations: ROI, throughput, length of stay.
- IT/Clinical ops: integration, reliability, security, governance.

# Differentiation (Context)
Aidoc’s positioning emphasizes: breadth of radiology AI modules, hospital-scale workflow orchestration, deep PACS/EHR integration, and demonstrated adoption. (Comparable market players include Viz.ai, Arterys, RapidAI, Corti; messaging should focus on Aidoc’s multi-specialty coverage and orchestration rather than one-condition point solutions.)

# SEO Strategy
- Target high-intent queries:
  - "FDA-cleared radiology AI", "AI stroke detection", "AI pulmonary embolism triage", "clinical workflow orchestration", "AI for ED imaging"
- Build clusters:
  - /solutions/ (each module), /workflows/ (ED, neuro, cardiothoracic, trauma), /customers/ (case studies), /insights/ (thought leadership)
- Comparison & late-funnel:
  - /compare/ pages with neutral FAQs (e.g., Aidoc vs <competitor>) plus schema.

# Technical SEO
- Core Web Vitals: LCP ≤2.5s; INP ≤200ms; CLS ≤0.1 (desktop & mobile).
- Crawl depth ≤3 for solution clusters; eliminate orphan pages.
- Canonical & hreflang self-referencing; consistent international signals.
- Sitemaps: split by type; refresh <24h on content updates.
- Robots: block parameters/test beds; allow CSS/JS.
- Priority schema:
  - Organization, MedicalDevice, MedicalEntity, Article, FAQPage, BreadcrumbList.

# On-Page Standards
- Titles (≤60 chars): {Entity/Use Case} | {Hook} | Aidoc
- Metas (≤160 chars): 1 benefit + qualifier + CTA.
- H1 = primary intent; H2 = use cases, integration, evidence, safety.
- Internal links: Radiology AI hub → modules → case studies → contact/demo.
- Image alts: "{Module/condition} AI - {purpose/outcome}".
- Accessibility: transcripts for videos; descriptive link text.

# Content Priorities
1) Solution pages (each module): indication/scope, workflow fit, integration, evidence, FAQs, safety notes, CTA.
2) ROI assets: calculators, outcome dashboards, exec one-pagers.
3) Case studies: adoption at scale; balanced outcomes and limitations.
4) Insights hub: regulatory updates, integration deep dives, hospital operations.
5) Comparison pages: neutral positioning; address "how it differs" and integration.

# AEO / LLM Readiness
- 40-word top answer on key pages:
  - "Aidoc is an FDA-cleared AI platform that supports radiologists and emergency teams by surfacing acute findings and orchestrating workflow within PACS/EHR."
- FAQ blocks that answer: What is it? Is it FDA-cleared? How does it integrate? Which conditions? Who benefits?
- Entity map: Aidoc → Radiology AI → {Modules} → Workflow Orchestration → Hospital Adoption.
- Plain-language definitions; avoid marketing hyperbole.

# Analytics & Measurement
- KPIs: organic demo requests, hospital conversions, qualified sessions by persona, doc downloads, comparison-page engagement.
- Tools: GA4, GSC, log sampling, Looker Studio dashboards.
- Track per-module conversion events; attribute by persona (clinician/executive/IT).
- Quarterly schema validation + CWV audits.

# Compliance & Risk
- Avoid "best/cure" language. Prefer "FDA-cleared," "supports clinicians," "may improve workflow."
- Include fair balance, limitations, and region-specific availability disclaimers.
- All content subject to MLR review; cite authoritative sources (e.g., FDA, peer-reviewed literature) on evidence pages.
- No off-label or comparative superiority claims.

# Roadmap Priorities
1) Technical: CWV fixes, crawl/index cleanup, structured data validation.
2) On-page: titles/metas refresh for /solutions, /compare, /insights.
3) Content: new/updated module pages, ROI calculators, integration guides, comparison FAQs.
4) Evidence: expand case studies with outcomes + limitations; link from relevant modules.
5) PR/Off-page: regulatory updates, hospital partnerships, clinical publications.

# Notes
- Regions: US + EU; ensure labeling/availability statements.
- IA: hub→spoke model; breadcrumbs; clear CTAs (demo/contact).
- Cadence: monthly technical audits; quarterly content/positioning review; ongoing MLR.

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llms-full.txt

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