Ninar AI: AI Visibility Platform Built for the AI Search Era

Some tools started as traditional rank trackers and added AI monitoring as a feature. That works fine if all you need is basic mention tracking. But if you need to actually improve your AI visibility, a bolt-on feature doesn't cut it.

Ninar AI was built from the ground up for AI visibility. Every feature, every scan mode, every integration is designed for how AI search works, not how Google worked in 2019.

Purpose-Built Architecture

Ninar AI doesn't repurpose SERP tracking infrastructure for AI monitoring. It uses native API integrations with each engine, dual-mode probing (memory + web-grounded), multi-layer brand detection (exact match, fuzzy match, LLM adjudication), and intent-weighted scoring that reflects how real users query AI engines.

9 AI Engines

AI Overviews, AI Mode, ChatGPT, Claude, Perplexity, DeepSeek, Le Chat/Mistral, Meta AI, Meta Llama. Each scanned with engine-specific methodology because ChatGPT's web search behavior is fundamentally different from Perplexity's citation model or Claude's training-data recall.

Content Generation + Publishing

When Ninar AI finds a visibility gap, it generates content designed to close it. Schema markup, entity-dense copy, FAQ structures, answer-first formatting. Then publishes via WordPress plugin or REST API. No handoff, no waiting.

MCP Server for Developer Workflows

Ninar AI ships an MCP server (ninar.ai/mcp) so developers using Claude Desktop, Cursor, or Cline can query AI visibility data from their IDE. No other visibility tool integrates into the developer workflow like this.

Comparison

Free Scan

Check your AI visibility at ninar.ai. No credit card, no account needed. 9 engines, 60 seconds.