Unusual helps B2B brands and SaaS providers shape how large language model agents perceive them. Its platform probes multiple AI models to map current brand perception, then creates SEO‑aligned, citation‑friendly content that improves AI‑driven recommendations and drives qualified traffic.
Funding
Funding not disclosed
Founders
Product
Problem
AI models increasingly act as brand audiences, forming opinions that influence buyer decisions across all marketing channels. When these models hold outdated or inaccurate beliefs about a company, the brand loses recommendations and sales without any visibility into the loss.
Solution
Unusual provides a systematic approach to diagnose and reshape how AI agents perceive a brand. By launching thousands of targeted “probe” prompts, the platform uncovers the specific attributes, categorizations, and trust signals that AI models associate with a company. It then generates AI‑optimized content—technical articles, use‑case pages, and citation‑rich resources—structured for easy crawling and citation by large language models. The resulting shift in model perception improves AI‑driven recommendations, increases citation share, and ultimately drives more qualified traffic and enterprise deals for the brand.
Target Audience
Primary customers are B2B brands, SaaS providers, and marketing teams that rely on AI‑driven recommendation engines and need to control how their company is represented to autonomous AI shoppers.
Features
- Automated probing engine that queries multiple LLMs (e.g., ChatGPT, Claude) to map current brand perception across dimensions such as enterprise readiness, security, and industry fit
- AI‑generated, SEO‑aligned content libraries hosted on dedicated subdomains to ensure consistent, citation‑friendly signals for LLMs
- Alignment dashboards that track perception scores, citation frequency, and bot traffic trends over time
- Integration guidelines for embedding perception‑optimized pages into existing web properties and knowledge bases
- Cross‑source verification that consolidates third‑party mentions, ensuring coherent signals across the web for LLM consumption