SEORCE - See where your brand is discovered and fix what blocks it
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Your brand is being discovered in more places than search, but you cannot see where you are missing. Rankings, crawls, content, and links live in separate tools, leaving teams guessing what to fix first. SEORCE gives one clear view of discovery across search and AI, shows what is blocking visibility, who is winning instead, and what to fix first. One system to understand, prioritize, and act without scattered dashboards.



Replies
Congrats on the launch! I like how SEORCE reframes discovery as something broader than rankings, especially with AI answers and recommendations changing the game quietly. How teams typically uncover their biggest “blind spots” with SEORCE first?
SEORCE
@vik_sh
Thank you so much 🙏 Really glad that framing resonated.
What teams usually uncover first are the quiet blind spots that don’t show up in traditional SEO tools. A few common ones:
Missing entirely in AI answers for category-level questions, even though they rank well on Google
Being mentioned, but positioned weakly (for example, listed as an option, not a recommendation)
Competitors showing up for use cases or geographies they assumed they already owned
AI pulling from third-party pages instead of their own site, which signals gaps in content or clarity
SEORCE surfaces these by running consistent prompts across AI tools and comparing responses over time, so teams can see where they’re invisible, why that’s happening, and what to fix first.
Most teams start by fixing just one or two of these blind spots and see clarity very quickly.
SEORCE
@chris_wyatt2 The pricing is available on the website, unless you are an enterprise / large agency, the pricing is up on the website here:
https://www.seorce.com/pricing
Can SEORCE detect brand mentions inside LLM answers that don’t link back
SEORCE
@vipin_jain3
In AI answers, brands are often mentioned without any link at all, which makes classic tracking miss a huge part of discovery. SEORCE doesn’t rely on links to detect visibility.
Here’s how we handle it:
We scan LLM responses directly and identify brand mentions even when there’s no citation or URL
We capture the context of the mention ,whether you’re recommended, compared, or just referenced in passing
We track frequency and consistency of those mentions across repeat runs, so it’s not based on a single response
We compare those unlinked mentions against competitors to show who’s getting mindshare inside AI answers
This way, you can see where your brand is influencing AI-generated answers, even when there’s no click or backlink and spot opportunities to turn that visibility into clearer positioning or linked citations over time.
How do you measure “share of voice” in AI-driven discovery
SEORCE
@karan_baror
Here’s how we do it:
Prompt coverage: For a defined set of category and use-case prompts, we track which brands appear in AI responses and how often
Prominence: We look at how a brand appears — primary recommendation, secondary option, or passing mention
Context weighting: Mentions are weighted based on strength (recommended vs referenced) and sentiment
Competitive comparison: Your visibility is always measured relative to the same competitor set, so changes are meaningful
Trend over time: We track this consistently, letting you see gains or losses as AI answers evolve.
The result is an AI-specific share of voice score that shows who owns the narrative inside AI answers, not just who ranks on a page.
I like that this focuses on connecting signals instead of adding another dashboard. The fragmentation between SEO, content, and authority tools is honestly exhausting.
SEORCE
@xiangce_sun
Appreciate you calling that out 🙏 That fragmentation was exactly what pushed us to build SEORCE this way. Our goal is to connect the signals across SEO, content, and authority so teams spend less time jumping between tools and more time actually acting on insights. Really glad that approach resonates!
SEORCE
@xiangce_sun Totally agree, and that fragmentation is exactly the problem we’re trying to remove.
SEORCE isn’t meant to be another dashboard you check once a week. It’s a connective layer that ties together signals that already exist but live in silos today - content, technical SEO, authority, and now AI-driven discovery.
Instead of asking teams to interpret five tools and guess what matters, we focus on:
Connecting cause → effect (what changed in AI answers and why)
As discovery shifts from links to answers, the real advantage isn’t more data - it’s clarity and continuity across systems. That’s the layer we’re building.
Hi @kulraj I am interested in AI programming. A while ago, about two months ago, I developed a small game, and I was very happy—but this happiness didn’t last long, because I found my small game hard to discover, and I’m not very good at SEO. Can @seorce help people like me make their personally developed websites more discoverable or increase traffic?
Finally, an SEO tool that feels aligned with how discovery actually works today — beyond just Google rankings. One dashboard, real insights, clear actions. Great launch! ⚡️
SEORCE
@princeku945
Thank you so much 🙌 That means a lot. We’ve really tried to build SEORCE around how discovery actually works today, not just how it used to. Glad the clarity and actions are coming through , appreciate the support ⚡️
What kind of teams benefit the most right now, and who might find SEORCE too advanced at this stage?
How does SEORCE stay accurate as search and AI discovery systems keep changing so fast?
Do you have any early results or examples where teams uncovered visibility issues they did not know existed?