01
Monitor AI answers at prompt level
Track recommendation share, sentiment direction, and answer quality across major AI providers from one workspace.
Prompt MonitoringVisibility TrendsSource-level tracking
Solutions
The complete AI visibility execution stack
Use one system for monitoring, competitor ranking, content gaps, autopilot blog and campaign generation, shopping intelligence, Data Copilot chat, secure MCP access, report generation, source audit, and finally hallucination control with LLM Council checks.
Operating model
Run one weekly loop instead of fragmented tools
02
Diagnose where visibility is leaking
Use competitor ranking and content gap intelligence to find exactly where your brand loses recommendation opportunities.
Tracked competitorsGap analysisModel-by-model comparison
03
Deploy content and prove impact
Generate blogs and campaign ideas, run validation with council/hallucination checks, and distribute executive-ready reports.
Autopilot contentLLM CouncilAutomated reporting
Prompt playbooks
Use these prompt pages to operationalize solution insights
Unaided Brand Recall
Unaided brand recall is the most honest measure of brand strength: does your name come up when no one is prompted to think about you? In an AI-mediated world, this...
Competitor Preference Analysis
Losing to a competitor isn't just a product problem — it's a brand and perception problem. At the moment of decision, something in the buyer's mind tips toward the...
Positioning for AI Retrieval
Positioning has always been written for humans — for the homepage visitor, the prospect on a sales call, the buyer reading a proposal. But increasingly, a layer...
Content Gap for AI Mentions
AI systems recommend brands based on signals accumulated from everything published about them. If the right signals don't exist, the recommendation doesn't happen —...
Category education
Understand the systems behind the solution stack
These foundation pages explain how AI recommendation share, citations, retrieval signals, and trust mechanics actually work before you operationalize them in the platform.
What Is Generative Engine Optimization (GEO)?
Generative engine optimization (GEO) makes your brand the answer AI models give. Learn how it works, the five levers and how to start.
GEO vs SEO: What Changes When AI Becomes the Discovery Layer?
GEO and SEO optimize for different things: SEO for a ranked page, GEO for a brand AI models recommend. See where they overlap and where budget shifts.
What Is Answer Engine Optimization (AEO)?
Answer engine optimization (AEO) structures content so AI answer engines can extract, synthesize and cite it. Learn the four pillars and what to measure.
What Is AI Share of Voice?
AI share of voice is the share of tracked prompts where your brand appears versus competitors. Learn how it differs from classic SOV.
Modules
Solution modules teams activate first
Prompt Monitoring
Track prompts that decide if your brand is recommended, then monitor response shifts over time.
- Recommendation share
- Prompt trend history
- Daily execution
Competitor Ranking
Compare your position against saved competitors and identify where they outperform your brand.
- Tracked competitor list
- Rank movement
- Share-of-voice context
Content Gaps Engine
Identify missing pages, intents, and angles that prevent AI systems from recommending your brand.
- Gap prioritization
- Query intent clusters
- Action-ready backlog
Blog Generation Autopilot
Turn detected gaps into publication-ready blog topics and drafts aligned to AI recommendation patterns.
- SEO + GEO aligned outlines
- Category-level coverage
- Execution velocity
UGC Campaign Suggestions
Generate campaign suggestions inspired by user-generated-content angles that reinforce trust signals.
- Campaign direction prompts
- Messaging variants
- Platform-ready angles
Shopping Intelligence
Analyze recommendation behavior and product visibility in AI-assisted shopping journeys.
- Product-level monitoring
- Retailer/source analysis
- Price narrative checks
Data Copilot Chat
Ask natural-language questions on your AI visibility data and get structured, actionable answers fast.
- Conversational analytics
- Cross-widget reasoning
- Ops-friendly summaries
MCP Server
Connect Claude, ChatGPT, and other compatible assistants to your saved Brand Armor AI data through secure read-only access.
- OAuth-based connection
- Read-only dashboard tools
- Company-scoped access
Automated Report Generation
Deliver recurring AI visibility reports with trend narratives and execution recommendations.
- Scheduled delivery
- Executive summaries
- Operational follow-ups
Brand Source Audit
Map the sources, authority pages, and citation gaps that shape how AI systems describe your brand.
- Citation coverage
- Authority source mapping
- Trust signal gaps
Live AI Crawler Monitoring
See recognized AI crawlers request your website in real time and identify the pages, providers, and purposes behind that activity.
- Live request stream
- Page-provider coverage
- Crawler health
Hallucination + LLM Council
Validate claims across models, flag risky responses, and compare consistency before taking action.
- Hallucination detection
- Cross-model consensus
- Risk reduction
Browse by industry
AI visibility solutions by industry
The same monitoring, competitor-ranking, and content-gap workflow, tuned to what buyers in your category actually ask AI platforms.
- AI Visibility for Adtech Platforms
- AI Visibility for Automotive Brands
- AI Visibility for Banking Institutions
- AI Visibility for Beauty Brands
- AI Visibility for Biotech Companies
- AI Visibility for Cloud Infrastructure Providers
- AI Visibility for Construction Brands
- AI Visibility for Consulting Firms
- AI Visibility for Consumer Brands
- AI Visibility for Crypto Brands
- AI Visibility for Data Platform Companies
- AI Visibility for Developer Tool Companies
- AI Visibility for Ecommerce Brands
- AI Visibility for Edtech Companies
- AI Visibility for Energy Companies
- AI Visibility for Fashion Brands
- AI Visibility for Fintech Companies
- AI Visibility for Government Agencies
- AI Visibility for Healthcare Brands
- AI Visibility for Home Service Brands
- AI Visibility for Hospitality Brands
- AI Visibility for HR Tech Platforms
- AI Visibility for Insurance Brands
- AI Visibility for Legal Tech Companies
- AI Visibility for Logistics Companies
- AI Visibility for Manufacturing Brands
- AI Visibility for Marketing Agencies
- AI Visibility for Marketplaces
- AI Visibility for Martech Brands
- AI Visibility for Media Publishers
- AI Visibility for Medical Device Brands
- AI Visibility for Newsrooms
- AI Visibility for Nonprofit Organizations
- AI Visibility for Open Source Projects
- AI Visibility for Payment Platforms
- AI Visibility for Proptech Platforms
- AI Visibility for Real Estate Brands
- AI Visibility for Recruiting Platforms
- AI Visibility for Restaurant Brands
- AI Visibility for Retail Brands
- AI Visibility for SaaS Companies
- AI Visibility for Supply Chain Platforms
- AI Visibility for Telecom Providers
- AI Visibility for Travel Brands
Why teams choose this setup
Built for operational consistency, not one-off snapshots
One operating view
Monitoring, analysis, optimization, and reporting stay in one flow so teams move faster with less context switching.
Execution-first outputs
The platform focuses on what to change next: which page, which prompt cluster, which competitor gap, and why.
Built for recurring runs
Daily schedules and report loops keep recommendations stable and reduce blind spots across models.
Start with one module or roll out the full stack
Choose the workflow that matches your current stage, then expand coverage across monitoring, analysis, generation, and reporting as your team scales.
Explore With AI
