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, report generation, crawler monitoring, 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
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
Automated Report Generation
Deliver recurring AI visibility reports with trend narratives and execution recommendations.
- Scheduled delivery
- Executive summaries
- Operational follow-ups
Crawler Monitoring
Understand AI crawler activity and detect how model-facing crawlers access your content.
- Crawler signals
- Indexing behavior
- Technical opportunity map
Hallucination + LLM Council
Validate claims across models, flag risky responses, and compare consistency before taking action.
- Hallucination detection
- Cross-model consensus
- Risk reduction
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.