What are Tokens and why do they matter?
Tokens are the units of text that LLMs process, often representing words, word parts, punctuation, or spaces. Token limits shape how much content an AI assistant can read, retrieve, summarize, and include in an answer. For SEO and GEO teams, tokens matter because overly long, repetitive, or poorly structured content can waste limited context, while concise and information-rich passages are easier for AI systems to use. Optimizing for tokens does not mean writing unnaturally short content. It means making each section useful: define the topic, answer the prompt, include key entities, and remove filler that does not improve understanding.
LLMs in AI Search: What They Are & Why They Matter
Large Language Models, or LLMs, are AI systems trained to understand, generate, summarize, and reason over language. In ...
What are Embeddings in AI Search?
Embeddings are numerical representations of text, images, pages, or other content that capture meaning and relationships...
What is Reciprocal Rank Fusion (RRF)?
Reciprocal Rank Fusion, or RRF, is a ranking method that combines results from multiple search systems by rewarding docu...
What is Ansehn?
Ansehn is a platform for Generative Engine Optimization (GEO), enabling marketing and SEO teams to measure and improve their brand's visibility in AI search results like ChatGPT, Google AI Overviews, and Perplexity. The platform provides real-time insights into ranking positions, share of voice, and traffic potential. Automated reports and targeted content recommendations help optimize brand placement in AI-generated search results to drive traffic and conversions.
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