HQAIM Labs

Live Experiments

Gemini Content Optimizer

Convert fluffy or vague brand copy into structured, entity-dense content ideal for LLM citation.

Tech Stack

Gemini 2.5 + HQAIM Prompt Protocol

Output

Structured Markdown + Entity Analysis

Pro Tip

"Focus on semantic triplets (Subject-Verb-Object). AI models prefer atomic facts over flowery prose."

Input: Standard Brand Pitch Token Limit: 500

LLM Retrieval Simulation

LLM Retrieval Simulator

Test how generative engines like ChatGPT or Gemini would synthesize and cite your brand content based on structure, entity density, and factual integrity.

Test Content

Entity Visibility Scanner

See what the machines see. Discover how visible your brand truly is to language models and knowledge graphs.

Enter Your Brand or URL

Visibility Grade: B+

Your brand is recognized in multiple LLM datasets but lacks structured context.

Schema Score: 76 / 100

Most schema elements found, some missing SameAs validation.

Entity Graph Visualization

Check	Status	Fix Recommendation
Organization Schema Found	Yes	None
SameAs Links Valid	Partial	Link missing to LinkedIn
Entity in LLM Embeddings	Yes	None
Third-party Mentions	No	Publish profile on 2+ trusted directories

GEO Optimization Tips

Add FAQPage schema with top 5 product questions.
Embed structured triplets on your homepage (Subject-Predicate-Object).
Secure citations on G2, Crunchbase, or Trustpilot.
Ensure all social profiles are linked via SameAs in Organization schema.

RAG Pipeline Analysis

Real-Time RAG Auditor

Live monitoring of Retrieval-Augmented Generation pipelines. See which specific content fragments are retrieved during inference by enterprise AI agents.

Upload Content Corpus or Paste Snippet

Chunks Retrieved

92%

Avg Relevance

0.4s

Latency

Retrieved Chunks

Retrieval Heatmap

Visualizing vector density...

Structuring Audit

Ensure high-value answers use definition lists.
Add schema to reinforce factual anchors.
Chunk consistently: 200–400 words per unit.