# What Is RAIVE?

RAIVE (Rankfender AI Visibility Engine) is the technology that monitors, scores, and helps optimize your brand's presence across 7 major AI systems in real time.

## Definition

RAIVE (Rankfender AI Visibility Engine) is the core technology that systematically queries 7 major AI systems — ChatGPT, Gemini, Perplexity, Claude, DeepSeek, Grok, and Llama — on a continuous basis to monitor how each platform mentions, recommends, and positions your brand. RAIVE runs structured test queries 4 times per day, simulating the full range of user intent: informational, comparative, recommendation-seeking, and transactional.

Each scan scores your brand across four dimensions: mention frequency (how often your brand appears), recommendation rank (first, second, or third position), sentiment (how the AI characterizes your brand), and citation accuracy (whether factual claims about your brand are correct). These four dimensions combine into a composite RAIVE score on a 0-100 scale, with individual breakdowns per platform.

RAIVE feeds three core Rankfender modules: the Observer (real-time alerts when your visibility changes significantly), the Strategist (AI-generated recommendations for improving your score based on competitive gaps), and the Chat interface (natural language analysis of your visibility data). Every chart, alert, and recommendation in Rankfender is powered by RAIVE data.

The technology handles both branded queries — where your brand name is in the prompt — and category queries, where a user is looking for a solution and your brand may or may not be recommended. Category queries are typically where the most competitive intelligence lives.

## Why It Matters

Without RAIVE, monitoring your AI visibility across 7 platforms would require manually querying each system hundreds of times, reading every response, recording brand appearances, and tracking changes over time — a process taking dozens of hours per week and still producing inconsistent, non-reproducible data. RAIVE automates this at scale with a consistent methodology, delivering comparable scores that teams can trend, benchmark, and act on.

Automated multi-platform monitoring matters because AI systems do not behave consistently. A model update on ChatGPT, a training data refresh on Gemini, or a new competitor article indexed by Perplexity can shift your visibility scores meaningfully within days. RAIVE's continuous scanning catches these shifts in near-real-time, so your team always has current data rather than a monthly snapshot that is already outdated.

### Related Concepts

- [AI Citation Score](/content/en/learn/ai-citation-score/index.html)
- [AI Visibility](/content/en/learn/ai-visibility/index.html)
- [AI Share of Voice](/content/en/learn/share-of-voice/index.html)
- [AI Brand Mentions](/content/en/learn/brand-mentions-ai/index.html)

## Key Things to Know

Essential aspects of RAIVE that every marketer should understand.

1. **Automated Multi-System Scanning**  
RAIVE queries all 7 major AI systems simultaneously, simulating real user prompts across informational, comparative, and recommendation query types. Running 4 scans per day, it captures how each platform responds about your brand and tracks changes as models update their knowledge and retrieval behavior.

2. **Visibility Scoring (0-100)**  
Each AI system produces a 0-100 score built from four dimensions: mention frequency, recommendation rank, sentiment quality, and citation accuracy. Scores are tracked over time, enabling week-over-week trend analysis and platform-level competitive benchmarking in a single dashboard.

3. **Competitive Intelligence**  
RAIVE monitors competitors in the same query set as your brand, generating head-to-head comparison data across all 7 AI platforms. See exactly which competitors are displacing you on which platforms — and identify the content gaps driving their advantage.

4. **Trend Tracking**  
Historical RAIVE data shows how your AI visibility evolves over time, correlating score changes with specific events: content updates, competitor moves, AI model refreshes, and PR campaigns. Trend data transforms raw scores into an actionable strategic record.

5. **Alert System**  
Get notified when your visibility score changes significantly, when a competitor gains or loses position, or when AI systems update their responses about your brand. Alerts are configurable by platform, threshold, and change type.

6. **SWOT Analysis**  
RAIVE generates AI visibility SWOT analyses showing your strengths, weaknesses, opportunities, and threats across the AI landscape — automatically updated as competitive positions shift and new platforms gain adoption.

## How to Measure

- **Overall RAIVE Score**: Aggregate visibility score across all 7 AI systems
- **Per-Platform Scores**: Individual scores for ChatGPT, Gemini, Perplexity, Claude, DeepSeek, Grok, and Llama
- **Score Trends**: Weekly and monthly visibility score changes
- **Competitive Gap**: Score difference between your brand and top competitors
- **Alert Frequency**: How often significant visibility changes occur

## Action Steps

1. Connect your brand to RAIVE by adding your domain and keywords
2. Run initial scan to establish baseline visibility scores
3. Review per-platform scores to identify strengths and gaps
4. Set up alerts for significant visibility changes
5. Use RAIVE data to guide content creation priorities
6. Track competitor scores alongside your own
7. Review RAIVE SWOT analysis for strategic planning

## Start Measuring RAIVE

Rankfender makes it easy to track RAIVE across 7 major AI systems. Get your scores, track trends, and compare against competitors.