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GetIntel

Free
★ 35 • Updated Jul 19, 2026, 09:03 PM

GetIntel is an AI search visibility platform designed for founders and agencies to monitor and improve how their brand appears in AI-generated recommendations.

Use Cases ▼
01

Track AI search visibility across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews

02

Monitor competitor mentions and citations in AI answers

03

Identify content gaps and draft fixes (e.g., llms.txt, schema) to improve AI recommendations

04

Watch Reddit and X signals to catch buying intent early

05

Integrate with coding agents via MCP to ship approved fixes automatically

06

Benchmark Findability Score against competitors to measure brand presence in AI

What Problem It Solves ▼

Many brands are invisible in AI-powered search results because they lack visibility into the prompts buyers use and the sources AI engines rely on. GetIntel solves this by providing a single dashboard that tracks, scores, and improves brand recommendations across multiple AI engines, turning blind spots into actionable insights so businesses can proactively influence what AI says about them.

Key Features ▼
✓

Provides a unified Findability Score across multiple AI engines

✓

Captures real AI interface answers, not just API responses

✓

Daily refresh ensures timeliness and momentum tracking

✓

Actionable fix recommendations with agent-based deployment

✓

Competitor benchmarking for strategic context

Overview

GetIntel is an AI search visibility platform designed for founders and agencies to monitor and improve how their brand appears in AI-generated recommendations. It tracks real answers from AI engines like ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews by capturing the interface rather than relying on sanitized APIs. The tool provides a daily-updated Findability Score that quantifies brand visibility across these engines, alongside competitor benchmarking. It monitors the exact buyer prompts that matter—such as pricing, alternatives, and ‘best of’ queries—so users can prioritize high-impact conversations. GetIntel also surfaces the underlying sources AI uses, including mentions and citations from Reddit, X, G2, Wikipedia, and Product Hunt, to reveal buying signals before they affect the score. Beyond tracking, it identifies content gaps and drafts actionable fixes (e.g., llms.txt updates, schema improvements, counter-articles) which can be reviewed and shipped via integration with coding agents through MCP, ensuring nothing goes live without user approval.

Pros & Cons

Pros

+

Provides a unified Findability Score across multiple AI engines

+

Captures real AI interface answers, not just API responses

+

Daily refresh ensures timeliness and momentum tracking

+

Actionable fix recommendations with agent-based deployment

+

Competitor benchmarking for strategic context

Cons

−

Limited to the specific AI engines currently supported

−

May not capture all niche or long-tail buyer prompts

−

Free tier likely imposes usage or feature restrictions

−

Relies on scraping live interfaces, which could break with UI changes

−

Focuses only on text-based AI search, not multimodal or voice

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