BrandSignal
AI Visibility Intelligence for Modern Brands
BrandSignal is an AI visibility and Answer Engine Optimization platform that helps brands understand, measure, and improve how they appear across AI search...
Why I Built It: As I increasingly relied on tools like ChatGPT, Grok, Gemini, and Perplexity to research products and compare brands before purchasing, I started thinking about the other side of that experience: how do brands know whether they are appearing in AI-generated answers, and why competitors may be recommended instead? BrandSignal explores that emerging visibility problem as a decision-support product, not a chatbot demo.
The Problem: Traditional SEO tools help brands understand how they rank in search engines, but consumer discovery is expanding beyond traditional search results. Brands now need visibility into whether AI platforms recognize and recommend them, how their positioning compares with competitors, which customer questions they are absent from, and what content and authority signals may improve their visibility.
The Solution: BrandSignal evaluates a brand's AI-search readiness and turns the findings into a prioritized optimization roadmap. Users enter brand and website information to receive insights across brand visibility and recognition, competitor positioning, prompt and intent coverage, citation readiness, content and entity gaps, and actionable AEO recommendations. The product is structured as analytics views rather than a chat interface, so teams can see where they are visible, where competitors are winning, why gaps may exist, and which actions to prioritize next.
Product Approach: I designed BrandSignal as a decision-support platform rather than a traditional audit report. Instead of only presenting a score, the experience helps users understand where their brand is visible, where competitors are winning, why those gaps may exist, and which actions should be prioritized next. A transparent BrandSignal Visibility Score (0–100) anchors the executive dashboard, with deeper prompt-level and competitor evidence underneath.
What the Platform Includes: An executive visibility dashboard with realistic Peacock OTT demo data; Prompt Explorer with multi-engine answers, citations, mentions, sentiment, and explanations; competitor and entity analysis; historical tracking, opportunities, optimizer, and reports; and extensible provider adapters for ChatGPT, Claude, Gemini, Grok, and Perplexity. The Scanner is demo-safe by default with mock data, and can run live or hybrid when session-only user API keys are supplied.
Built With: Built with Cursor and Grok 4.5 through modern AI-assisted product development workflows, using Next.js, TypeScript, and Tailwind CSS. The architecture separates product routes, reusable visualization components, pure domain scoring and explanation logic, provider adapters, and a Zod-validated scan API, with an optional Prisma Postgres path for persisted scan history.
What I Explored: Through this project I explored the emerging intersection of Answer Engine Optimization, Generative Engine Optimization, AI-driven consumer discovery, brand positioning, competitive intelligence, and AI-assisted product development. The core learning was that brands need operator tooling for AI answer visibility, not another SEO checklist or chat wrapper.
Demo-safe by default with mock scan data. Optional live or hybrid scans use session-only API keys entered in Settings and are not persisted by the demo. No advertising spend is incurred.