Bekon
Track and improve how AI assistants recommend your brand.
Tagline
Win the AI answers that matter
Search Console for AI visibility
See which prompts name your brand
Stop publishing blind. Fix AI visibility.
Bekon is the visibility layer for AI search, the way Search Console is for Google.
The product is fundamentally about measuring presence, share of voice, and rank across AI models, not just writing content. That makes a category-defining angle more credible than an 'AI SEO tool' label.
The best alternative to manual prompt testing and screenshot-driven AI brand tracking.
The Query Inspector, multi-model support, and prompt coverage analysis suggest it replaces a brittle manual workflow currently done in notebooks, spreadsheets, and repeated ChatGPT queries.
Stop publishing content blind: Bekon tells you which prompts, pages, and fixes actually move AI visibility.
The page repeatedly emphasizes actionable improvements like llms.txt, schema, internal linking, and deploy/re-scan loops, so the strongest pain-killer framing is precision and measurable lift.
Primary user
Head of SEO or Growth at a B2B SaaS company trying to win AI-referred discovery
ICP #1
Head of Growth at a B2B SaaS company with an established SEO program
Pain
They know traditional rankings are flattening, but they cannot tell why competitors are being named in AI answers while their brand is ignored.
Why this solves
Bekon gives them model-level visibility, competitor share-of-voice, and concrete fixes tied to prompts and content angles, so they can act instead of guessing.
ICP #2
SEO agency owner managing 5-20 client accounts
Pain
Clients are asking about ChatGPT and Gemini visibility, but standard SEO tools do not explain AI recommendations or provide a client-ready reporting layer.
Why this solves
Bekon produces downloadable visibility reports, ranked competitor benchmarks, and prioritized improvements that are easy to present in monthly retainers.
ICP #3
Solo founder or marketing generalist at a small SaaS with no SEO function
Pain
They need AI discovery traffic but do not have time to manually test prompts, create supporting content, or monitor changes after publishing.
Why this solves
Bekon's Autopilot workflow analyzes, diagnoses, deploys, and re-scans automatically, which directly matches a ship-and-forget operating style.
Strengths
- +The product is unusually concrete: it shows workflows, prompt lists, competitor leaderboards, model selection, reports, and deployment paths instead of vague promises.
- +The page nails the emerging category language with terms like AI search visibility, generative engine optimization, and answer engine optimization.
- +The workflow split into Watch, Maintain, and Autopilot is a strong way to segment users by maturity and operational style.
Weaknesses
- −The landing page is crowded and repetitive; the same navigation and CTA structure appears multiple times, which makes the message feel less crisp than the product itself.
- −The hero headline is decent, but it doesn't immediately state the core job: ranking in AI answers for commercial prompts. 'Turn AI search into your most reliable channel' is broad and slightly abstract.
- −It leans heavily on feature inventory without enough proof of impact, especially for a skeptical buyer who wants examples of lifted prompts, before/after visibility, or benchmark data.
- −The audience is still fuzzy. The page tries to speak to founders, agencies, SEO teams, and CMOs at once, which dilutes the strongest use case.
- −Several screenshots and examples are tied to Notion, Coda, ClickUp, and Confluence. That helps illustrate the product, but it risks making the brand feel like a workspace-app demo instead of a general AI visibility platform.
Fix these
- Tighten the hero around one clear use case: 'See and improve whether ChatGPT, Gemini, and Claude recommend your brand for high-intent buyer prompts.'
- Add a hard proof section with before/after examples: specific prompts, visibility score changes, and competitor swaps that happened after a fix.
- Create separate landing-page variants for three buyers: SaaS growth, SEO agencies, and founders without SEO resources.
- Reduce repeated UI and navigation duplication to make the page feel more premium and easier to scan.
- Replace some generic AI search language with explicit commercial outcomes like category consideration, comparison prompts, and alternative queries where AI influence actually affects pipeline.
Drop-in replacement copy
Headline
See if AI recommends your brand
Track mentions, compare competitors, and fix visibility across major answer engines.
Know where you show up
See whether your brand appears in ChatGPT, Gemini, Claude, Grok, DeepSeek, and Mistral for the prompts that matter. Get one visibility score instead of guessing from scattered screenshots.
See who beats you
Bekon compares you against named competitors by discoverability, share of voice, and average rank. That gives you a real benchmark, not an abstract SEO report.
Fix the right pages
Get specific recommendations for llms.txt, schema markup, internal links, and prompt coverage gaps. The goal is to move visibility, not just create more content.
Ship and rescan
Deploy fixes through Cloudflare, GitHub, or Vercel, then check whether the change moved your visibility. That closes the loop from diagnosis to action.
FAQ
How is this different from Semrush or Ahrefs?
Those tools are built around traditional search rankings. Bekon is built for AI answers, so it measures brand presence inside model responses and compares that against competitors.
Which AI models do you track?
Bekon currently tracks ChatGPT, Gemini, Claude, Grok, DeepSeek, and Mistral. You can run the same query across multiple models and compare the answers side by side.
Do I need a big SEO team to use this?
No. It works for in-house growth teams, agencies, and solo founders. If you can publish content or push a site change, you can use the recommendations.
What kind of fixes does Bekon suggest?
It highlights practical changes like llms.txt, schema markup, internal linking, and content angles that match the prompts where your brand is missing.
Can I share reports with clients or teammates?
Yes. Bekon includes extended visibility reports that are built to be downloadable and shareable, which makes it easier to present results in meetings or retainers.
ChatGPT already ranks your brand. The question is: does it recommend you? Bekon tracks how often you appear in answers across ChatGPT, Gemini, Claude, Grok, DeepSeek, and Mistral. Then it tells you what to fix.
Your SEO rank is not enough. If AI answers skip your brand, buyers never see you. Bekon shows your visibility score, competitor share of voice, and the prompts you’re missing. Build for the answer engine, not just the blue links.
We kept seeing the same problem: teams were publishing content, but had no idea if AI models were actually citing or recommending them. So we built Bekon to run the same prompt across 6 models, compare competitors, and point to the fix.
The part nobody else does: Bekon doesn’t just report visibility. It tells you what to ship next. llms.txt, schema, internal links, content angles, deploy via Cloudflare/GitHub/Vercel, then re-scan. Less guessing. More movement.
Manual prompt testing is broken. One query in ChatGPT. Another in Gemini. Screenshot. Spreadsheet. Repeat. Bekon runs the same question across 6 models in parallel and turns that mess into one visibility report.
Competitors show up. You don’t. That’s not a vibe issue. It’s a visibility issue. Bekon shows which brands AI answers prefer, where you’re missing, and which pages or prompts can change it.
Here’s the workflow in 15 seconds: 1. Pick your category 2. Bekon generates prompts 3. Scan ChatGPT, Gemini, Claude, Grok, DeepSeek, Mistral 4. See your rank vs competitors 5. Ship fixes 6. Re-scan That’s it.
One query. Six models. One report. That’s the whole point of Bekon’s Query Inspector. Instead of wondering why AI ignores your brand, you get a side-by-side answer view, competitor ranking, and the exact prompts worth targeting.
The fastest way to explain AI SEO: Show a founder where they appear in AI answers today. Then show the competitor who stole the slot. Then show the fix. That’s why Bekon is built like a visibility dashboard, not a content toy.
Teams do not need more AI fluff. They need a way to answer: - Are we mentioned? - Against whom? - On which prompts? - What should we change? Bekon is built for exactly that conversation.
Angle: Search Console for AI visibility
Most teams are still treating AI search like SEO from 2021. That’s the wrong mental model. If buyers ask ChatGPT, Gemini, Claude, or Grok who to consider, you need to know: • whether your brand appears • which competitors are being named instead • which prompts you’re missing • what content or schema change could move the needle That’s why we built Bekon. It’s the visibility layer for AI search. Not a content spinner. Not another “GEO” dashboard with vanity metrics. Bekon measures your presence across multiple models, compares you against competitors, and turns the result into actions you can actually ship: • llms.txt • schema markup • internal linking • prompt coverage fixes • deploy-and-rescan workflows The goal is simple: stop publishing blind. If AI answers are becoming the new discovery layer, you need a way to see whether your brand is showing up. That’s the product.
Angle: manual prompt testing replacement
There’s a weird amount of manual work happening in AI visibility today. People are: • asking the same question in 5 different models • screenshotting answers • pasting results into spreadsheets • arguing about whether a brand was “really” mentioned That workflow does not scale. Bekon replaces it. Run one query across ChatGPT, Gemini, Claude, Grok, DeepSeek, and Mistral in parallel. See the competitor leaderboard. Get a visibility score. Then get concrete recommendations for what to fix next. What I like about this problem is that it’s not abstract. A head of SEO, growth lead, or agency strategist can look at the report and immediately understand what changed and what to do next. No noise, no nudges. Just signal. We’re betting that the best products in this space won’t just answer “are we visible?” They’ll answer “what do we do now?” That’s the part nobody else does.
Angle: agency and operator use case
The strongest early buyer for AI search visibility might not be the founder. It might be the person who has to explain it every month. For SEO agencies and in-house growth teams, the problem is not just tracking AI answers. It’s making the data usable in a client review or an internal update. That’s what pushed us toward Bekon’s report-style workflow. You can show: • share of voice by model • competitor rank changes • prompt coverage gaps • quick wins like schema or llms.txt • progress after fixes are deployed That matters because clients do not want a theory. They want to know if their brand is getting named when people ask high-intent buyer questions. We’re still early, and I’m very interested in feedback from: • agency owners managing multiple accounts • heads of SEO with an existing content program • growth leads trying to win commercial prompts If that’s you, I’d love to know what you’d need in a report to make this part of your monthly workflow.
Tagline
Track your brand in AI answers
Description
Bekon shows whether ChatGPT, Gemini, Claude, Grok, and others recommend your brand, compares you to competitors, and tells you what to fix next.
Maker's first comment
We built Bekon because manual AI visibility checks were a mess. Teams were asking the same question in multiple models, screenshotting answers, and trying to turn that into a strategy. But if you’re a head of SEO, growth lead, or agency strategist, you need something cleaner: one place to see where your brand appears, who beats you, and what to change. Bekon started as a simple question: if AI answers are becoming a discovery channel, why is there no Search Console for them? So we made the product around that idea. It tracks visibility across models, compares competitors, suggests prompt coverage gaps, and points to fixes like llms.txt, schema, and internal links. The goal isn’t more dashboards. It’s fewer guesses. I’d love feedback on the report format, the clarity of the recommendations, and which buyer you think this should serve first: SaaS growth teams, agencies, or solo founders.
Pinned maker comment
Would love feedback on two things: the report format and whether the first-time user flow makes the next action obvious. Also curious which ICP feels strongest to you right now: SaaS growth, agency, or solo founder.
Meta
ChatGPT is already recommending competitors
Hypothesis: heads of SEO and growth at B2B SaaS want a faster way to see whether AI models mention their brand. Bekon tracks brand visibility across ChatGPT, Gemini, Claude, Grok, DeepSeek, and Mistral, compares competitors, and shows what to fix next.
Google Search
Track your brand in AI answers
Hypothesis: people searching for AI SEO tools want a direct way to measure brand presence in model answers, not another content tool. Bekon shows if ChatGPT, Gemini, Claude, Grok, DeepSeek, and Mistral recommend your brand, then turns that into actions.
Reddit Promoted
If AI ignores your brand, this helps
Hypothesis: SEO operators and founders in Reddit communities want less theory and more signal on whether AI models mention their brand. Bekon runs the same prompt across 6 models, compares competitor rank, and suggests fixes you can ship.
Subreddits
r/indiehackers
Build-in-public post about replacing manual prompt testing with multi-model visibility tracking
Rules: Share lessons and numbers; avoid pure promo; lead with the problem and what you learned
r/SideProject
Show the workflow: one query across 6 models, competitor comparison, and actionable fixes
Rules: Must show the build or demo; keep self-promo minimal and useful
r/microsaas
Explain the niche and the reporting workflow for SEO agencies and small SaaS teams
Rules: Focus on product lessons, pricing, and customer discovery; no spammy launch-only posts
r/EntrepreneurRideAlong
Diary-style post about building a category new tool for AI visibility
Rules: Transparent journey posts work better than polished marketing; share progress and challenges
r/SEO
Practical post on how AI answers are changing discovery and what metrics matter now
Rules: Be genuinely useful, avoid promotional language, and bring examples or screenshots
Communities
Post a build log, then reply fast to every comment with specifics, screenshots, and metrics.
Offer a free teardown of AI visibility for a few members and use that as a learning loop.
Cold outreach template
Hey {firstName} - noticed {context} and thought this might be relevant. We built Bekon to show whether ChatGPT, Gemini, and Claude actually recommend your brand versus competitors. If you want, I can run your category and send the visibility gaps back in one report.
Product Hunt timing
Launch on Tuesday at 12:01am Pacific Time. It fits B2B SaaS buyers in US time zones, gives you a full weekday for replies, and avoids the Monday inbox pileup and weekend dead zone.
Indie Hackers post ideas
- 01I built a Search Console for ChatGPT mentions
- 02How we replaced manual AI prompt testing with one dashboard
- 03What changed after we tracked competitor share of voice in AI answers
Competitor alternatives
Current tone of voice
Confident, product-led, and mildly technical. The copy is direct and outcome-focused, with lines like 'No noise, no nudges' and 'The part nobody else does,' which positions Bekon as a serious operator tool rather than a fluffy AI brand tracker.
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