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ModularDot
Make your site clear to people and answer engines
ModularDot runs a free, deterministic 16-check answer-readiness scan on an authorized public website. It shows the exact evidence behind identity, access, proof, and decision-support results—without claiming AI rankings or citations. The $149 founding Fix Pack adds a prioritized page map, three publish-ready answer blocks, corrected JSON-LD, and before/after evidence. Two disclosed owned production references moved 62→98 and 49→98 under the same v2 method.
Hi Product Hunt — I’m Sarah, founder of ModularDot.
I built it because “AI visibility” is often sold through black-box scores and promises nobody can honestly guarantee. I wanted something smaller and inspectable: show exactly where a public website makes buyers or answer engines guess, then turn meaningful gaps into changes a real team can publish.
What you can try today:
- a free 16-check deterministic scan—no signup, no API keys, nothing stored;
- per-check evidence and a public scoring method;
- two owned production references: LossyInfo moved 62→98 and NostalgAI 49→98 under the same v2 method;
- a $149 founding Fix Pack with a page-gap map, three publish-ready answer blocks, corrected JSON-LD, and before/after evidence.
Important disclosure: LossyInfo, NostalgAI, and ModularDot are all operated by me. LossyInfo and NostalgAI are owned production reference implementations—not external customer results. The score measures observable public inputs—not rankings, citations, traffic, or revenue.
I’d especially value feedback on one question: after running the scan, is the evidence specific enough to tell whether your site is genuinely unclear—or whether the deterministic scanner simply missed valid wording?
About ModularDot on Product Hunt
“Make your site clear to people and answer engines”
ModularDot was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #114 on the daily leaderboard. ModularDot runs a free, deterministic 16-check answer-readiness scan on an authorized public website. It shows the exact evidence behind identity, access, proof, and decision-support results—without claiming AI rankings or citations. The $149 founding Fix Pack adds a prioritized page map, three publish-ready answer blocks, corrected JSON-LD, and before/after evidence. Two disclosed owned production references moved 62→98 and 49→98 under the same v2 method.
On the analytics side, ModularDot competes within Marketing, SEO and Artificial Intelligence — topics that collectively have 984.2k followers on Product Hunt. The dashboard above tracks how ModularDot performed against the three products that launched closest to it on the same day.
Who hunted ModularDot?
ModularDot was hunted by Sarah vanOorsouw. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of ModularDot including community comment highlights and product details, visit the product overview.
Sarah vanOorsouw
Hi Product Hunt — I’m Sarah, founder of ModularDot.
I built it because “AI visibility” is often sold through black-box scores and promises nobody can honestly guarantee. I wanted something smaller and inspectable: show exactly where a public website makes buyers or answer engines guess, then turn meaningful gaps into changes a real team can publish.
What you can try today:
- a free 16-check deterministic scan—no signup, no API keys, nothing stored;
- per-check evidence and a public scoring method;
- two owned production references: LossyInfo moved 62→98 and NostalgAI 49→98 under the same v2 method;
- a $149 founding Fix Pack with a page-gap map, three publish-ready answer blocks, corrected JSON-LD, and before/after evidence.
Important disclosure: LossyInfo, NostalgAI, and ModularDot are all operated by me. LossyInfo and NostalgAI are owned production reference implementations—not external customer results. The score measures observable public inputs—not rankings, citations, traffic, or revenue.
I’d especially value feedback on one question: after running the scan, is the evidence specific enough to tell whether your site is genuinely unclear—or whether the deterministic scanner simply missed valid wording?