We're building for the recommendation economy.
OpenAEO comes out of hands-on search, growth and AI work with small businesses. It is open source, so the audit engine, the crawler and the commit history are all public and you can judge the work rather than the biography. We audit sites against 5 retrieval gates and 8 headline checks, every one computed live, free on 1 site. Helping businesses get found by the technology of the moment. We watched the ground shift under everyone's feet: customers stopped scrolling ten blue links and started asking an assistant, and overnight the rules of being discovered changed. The winners are no longer whoever ranks first; they are whoever the AI can read, trust, and recommend. We started OpenAEO because that shift is quietly leaving good businesses behind, not because their product is worse, but because their site is invisible to the assistants their customers now ask. Our mission is simple: a world where any business, not just the ones who can afford an agency, can succeed in this new recommendation economy. The free audit is where that starts.
- The code. github.com/charlacsina/openaeo-audit. Every check, every weight, and the crawler that fetches your site as each AI bot.
- The CLI. npx openaeo-audit yoursite.com. The same engine as the web audit. Add --json for CI.
- The MCP server. Listed in the official registry as dev.openaeo/audit, so your coding agent can run it. Setup and the tool reference.
- This site. Run the audit on openaeo.dev. We score ourselves with the same rubric and publish what it says.
The hosted service is not open source and we do not pretend otherwise: the audit history tracked over time, weekly citation testing and the crawler corpus run on our infrastructure. Where that line falls.
The team behind it
We are builders who have shipped in search and growth for years, and OpenAEO is the tool we wished existed the day AI search arrived. We helped businesses win in the era of Google, and we would rather help them win in the era of the assistant than watch a whole generation of good companies disappear from the answer. We keep the team small and the product opinionated: the same rubric for a solo photographer and a Fortune 500, a free tier that gives away the entire audit, and a flat refusal to sell vanity metrics. We are not here to gatekeep a dark art. We are here to make being recommended by AI as understandable as SEO became, and just as accessible. If you are reading this on launch day, this is day one of a long build: we would rather earn your trust with an honest score than a flashy promise. Come break it, tell us what is missing, and help us shape what the recommendation economy looks like.
What we believe
Three principles shape every audit. First, a score is only the input and a citation is the outcome, so OpenAEO never hands over a scorecard without a same-day citation baseline beside it, a number you can optimize is not the same as a customer who found you. Second, unverified facts get flagged, never guessed: anything we cannot confirm ships as a visible marker in your copy and schema, and unresolved markers cap your score so placeholder text can't ride a passing grade. Third, off-site consensus is measured, not sold, because assistants trust independent agreement between sources more than anything a site says about itself: community threads, third-party roundups, reviews, directory entries. That is 24 of the rubric's 100 points sitting on ground you do not own, and no file we generate can move them, so we score them, name the thin ones, and leave the earning to you. Those three rules are why the rubric is opinionated and why we would rather show you an honest 55 than a flattering 90.
How we work
The order is always the same: audit, fix, measure. First we crawl the site as each AI bot and score it, which surfaces the retrieval gate that is usually the real problem. Content that only renders after JavaScript, or a robots.txt line inherited from a relaunch that has quietly blocked GPTBot for months. Then we hand over the exact remediation: a generated robots.txt and llms.txt, JSON-LD that mirrors your visible numbers, and page copy rewritten to answer the buyer's question in the first hundred words with specifics instead of adjectives. Finally we measure, by segmenting AI-referral traffic and testing your target questions weekly across the four assistants, so you can see whether being cited turned into visits rather than guessing. Reach us any time at [email protected].
Questions
Who is behind OpenAEO?+
Why is the OpenAEO audit free and open source?+
Does OpenAEO sell off-site work like reviews and directory listings?+
How is this different from a traditional SEO tool?+
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