SEO research system
Rankr
An AI SEO agent for Singapore SMEs that finds demand and competitor gaps, drafts from real audience questions and helps businesses show up on Google.
A perfect on-page score produced no rankings, so I rebuilt the system around authority, demand and inspectable search evidence.
- Product demo: Rankr researches competitor gaps, drafts the useful page and waits for approval before publishing.
- ChatGPT citation: The low-authority Lullaflex testbed earned a real citation from ChatGPT.
- UCWS pitch: Rankr reached the Top 20 from more than 800 UCWS participants.
- UCWS finalist: Rankr reached the Top 20 from more than 800 UCWS participants.
- SME benchmark: The benchmark compares 42 responding sites by sector instead of hiding them behind one score.
- Live testbed tool: The live testbed included a real planner because useful tools earn links and citations that commodity articles do not.
What it does
Rankr combines market research, site diagnostics and content planning. Each recommendation links back to the evidence that produced it, and the public checker gives a small business a useful result without a sales call.
The result
Two Singapore SMEs signed letters of intent. Rankr also reached the Top 20 from more than 800 UCWS participants. Each finalist team received US$10,000 in OpenAI credits, and the project received S$2,000 from SUTD's Baby Shark Fund.
The experiment that changed the product
We pushed a fresh test site into the nineties on our own on-page checker. It still had almost no search authority and almost no traffic. The score looked good and explained very little.
That failure forced a rebuild. The next version separated technical hygiene from authority, demand and AI visibility. One page from the DR 2 Lullaflex testbed was later cited by ChatGPT, which gave us a much better piece of evidence than another internal score.
System design
I built the client pilot site, publishing layer and SEO/GEO plumbing. Differentiated titles pulled pages out of Google's "crawled, currently not indexed" state.
DataForSEO finds the gaps. Real Reddit threads ground each angle instead of producing another keyword list. Coverage memory stops the agent from pitching the same topic twice, and nothing reaches the client site without approval.
What I learned
An SEO score is only useful if it predicts something outside the tool. The testbed made it cheap to prove our own metric was weak before a client had to.