BrandGEO.app VS Codegres.org

BrandGEO.app's answer

Three reasons, and one honest reason not to.

1. Price floor. Profound starts at $99/mo and Otterly.AI at $29/mo. BrandGEO has a free audit with no signup, and paid plans start at $19/mo ($13/mo billed annually). If you are a founder still checking whether AI visibility is even a problem for you, you should not have to spend $99 to find out.

2. It ships artifacts, not just charts. Monitoring tools report that you are invisible. BrandGEO generates the llms.txt, JSON-LD and FAQ schema that close the gap, plus a prompt you can hand to Cursor or Claude Code so your coding agent applies the changes for you. Then a re-check confirms it landed.

3. Crawler-accurate by default. It fetches on the no-JavaScript path AI crawlers actually use and parses robots.txt per user-agent (GPTBot, ClaudeBot, PerplexityBot, Google-Extended). That is how accidental GPTBot blocks get caught — the single most common finding.

The reason not to choose it: if you need enterprise share-of-voice tracking across hundreds of prompts, multiple markets and a team seat model, the incumbents are more mature. BrandGEO is built for one person who needs the problem fixed this week.

BrandGEO.app's answer

Founders and small marketing teams — typically 1 to 10 people — at SaaS and ecommerce companies selling into English-speaking markets. The trigger moment is usually the same: they have a working website, Google traffic is fine, and then they notice that ChatGPT or Perplexity recommends a competitor when someone asks for a tool like theirs.

A second group: SEO consultants and small agencies who have picked up GEO/AEO work and need a repeatable audit plus deliverables they can actually hand to a client, not just a dashboard screenshot.

It is deliberately not built for enterprise brand teams that need share-of-voice tracking across hundreds of prompts and multiple markets, with seats and approvals. Those buyers are better served by Profound or Otterly.AI.

BrandGEO.app's answer

I spent seven years in brand consulting. The trigger was watching a client lose deals because ChatGPT kept recommending a competitor instead of them.

Their website was fine for Google. It was unreadable to AI crawlers — their robots.txt had been quietly blocking GPTBot for months, and not one of the tools they were paying for had ever mentioned it.

What bothered me was not that the problem existed. It was that every tool I could find would only score the problem. None of them would hand you the patch. So BrandGEO was built around one rule: if we can detect a gap, we should be able to emit the file that closes it — and then re-check that it actually landed.

The same rule is why every finding is labelled confirmed, AI-suggested, or unverifiable. A consultant learns quickly that a confident wrong answer costs the client more than an honest "I don't know yet".

BrandGEO.app's answer

• Next.js (App Router) + TypeScript for the web app. The marketing pages are server-rendered and readable with JavaScript disabled — which matters when your product is about crawler accessibility, so we hold ourselves to the same standard we audit others against.
• Node.js for the audit engine and the crawler, which fetches on the no-JavaScript path and parses robots.txt per user-agent (GPTBot, ClaudeBot, PerplexityBot, Google-Extended).
• Vercel for hosting and deployment.
• LLM APIs for the generation steps (fix packs, article drafts) and for probing live answer engines to check current citations.
• next-intl for full internationalisation — English and Chinese are both first-class locales, not machine-translated pages.