We believe brands deserve to know what AI is saying about them.

AnswerLens was founded in 2025 out of a fundamental shift in search behavior: consumers stopped scrolling through 10 blue links on Google and started asking LLMs like ChatGPT, Perplexity, Claude, and Gemini direct buying questions — "Does this brand ship to Europe?", "What is their return policy?", "Is X or Y more durable?"

Traditional SEO analytics could report that a visitor clicked through from an AI referral. But nothing could tell marketing or communications teams what the model told that buyer before they clicked, whether the pricing was obsolete, or whether the model incorrectly claimed the company was out of business.

Our Core Engineering Principles

• Factual accuracy is a critical business metric: An AI model hallucinating your return window from 30 days down to 14 days directly depresses checkout conversion.
• No black-box scores without citation proof: If a monitoring platform flags an error, it must quote the verbatim sentence, the prompt that produced it, and the source URL the model misattributed.
• Actionable engineering briefs, not vague SEO platitudes: Telling a marketing team to "optimize for GEO" is useless. AnswerLens provides the exact Schema.org microdata and canonical copy diffs to deploy.
• Frontier multi-model neutrality: We do not accept sponsored placements or manipulate model outputs. We provide an independent, objective audit across all major frontier foundation models.

Engineering & Team

AnswerLens is built by a distributed team of engineers and researchers specializing in Information Retrieval (IR), Knowledge Graph verification, and Natural Language Processing. Our systems currently monitor over 1.2 million simulated buyer prompts weekly across North America, Europe, and Asia.