Context Window
A context window is the amount of text, data, or tokens an LLM can consider at one time when generating an answer. Larger context windows allow AI assistants to process more information, but they do not guarantee that every detail will be used accurately. For AI search, context windows affect how much retrieved content, prompt history, citations, and instructions can shape the final answer. Content teams should not rely on long pages alone. The best approach is to make important answers easy to retrieve, summarize, and cite in compact sections. Clear headings, concise definitions, and well-structured evidence help AI systems use context more effectively.
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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