This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Reach is the operating system to win AI search. Your marketing team and AI agents work in one place, doing the work that actually gets you recommended by ChatGPT, Perplexity and Google in the prompts that matter for your buyer journey. From finding the demand, to executing content, mentions and community, to measuring and attributing the revenue.
Hey Product Hunt 👋 Jose here, founder of Reach.
Right now, 41% of B2B buyers start vendor research in AI. When someone asks ChatGPT, Perplexity or Google's AI for the best tool in a category, there is basically one recommended answer. If it isn't you, it's your competitor, and you never even see the deal.
A year ago we put a team of the best SEO and data science experts on one question: how do these AI models actually decide which companies to recommend? We put the answers to work for companies like Carro, Indie Campers and Fraudio, drove millions in inbound revenue, and turned everything that worked into frameworks, then a platform.
Because here is how "winning AI search" has looked until now:
- buy a tool that just tracks how invisible you are
- fly blind on which prompts actually drive revenue
- get generic recs that don't know your product or your buyers
- let AI write the content, and ship slop that changes nothing
- do all the real work yourself, across five disconnected tools
We built the opposite. Reach is the operating system to win AI search: your marketing team and AI agents in one shared workspace, actually doing the work to change what AI recommends. It finds every question your buyers ask AI (ranked by revenue), reverse-engineers why the winners get cited, builds the roadmap, and puts agents to work on content, mentions and community, then measures and attributes the revenue across Search Console, Analytics, rankings and AI citations.
It's already working:
↳ Indie Campers grew revenue from AI search 14x in a year
↳ Carro went from a 0% to a 34.58% AI citation rate, now the #3 most-cited domain in its category, above Forbes and Shopify
↳ ColdIQ influenced $506K in signed pipeline in about 4 months
↳ Fraudio went from zero AI citations to recommended in 20.24% of the prompts that matter for their buyer journey, above unicorns like Feedzai
🎁 Launch gift for PH: comment your domain and I'll send back a free revenue-leak audit (the top 5 places AI is sending your buyers to competitors) plus the top 5 listicles in your category that could add $100k+/yr from AI recommendations. First launch signups also get a $300 credit toward Reach.
I'll be in the comments all day. Tell me the prompt you'd most want ChatGPT to recommend you for, and I'll show you what it takes to win it. 🙏
the part I'd want stress-tested before trusting a citation-rate number: these models are non-deterministic and increasingly personalized - memory, browsing mode, account history all shift what gets recommended, so the same prompt can genuinely return a different answer for two different real buyers. when you measure a domain's citation rate, is that sampled across enough variation to represent what buyers actually see, or is it closer to a single controlled probe that could look great on the dashboard while real users are still getting a different answer half the time?
@Jose Velez that clears it up, thanks. first touch plus last touch through the actual CTA gets you most of the way there without needing a full multi-touch model. does Reach expose that whole path (every touchpoint between first and last, not just the two ends) or is it deliberately kept to first/last to avoid overfitting a story onto noisy data?
the framing of "operating system" instead of another visibility tracker is the right call, most tools in this space stop at the dashboard. curious how the attribution actually works though - when a deal closes, how confident are you that the AI citation was the driver versus one touchpoint among five, especially for longer B2B cycles where someone sees a ChatGPT answer in January and buys in June?
As someone who now uses AI for everything I want to use or buy, this makes total sense!
I have worked with some of this team before and they are smart, high-energy and delivery-focused.
Bernardo Ferreira here, Founding AI Search Optimization Strategist at Reach 👋
We've waited for this moment for so long. And it's finally the day!
I feel so proud of our journey so far. It's even more special considering we're building something in a new ecosystem, among the pioneer companies defining the foundations of this industry.
We've been helping companies show up on AI search, with our experts' brains empowered by Reach's agents. And now it's time to share with everyone some of the tools that have been enabling our professional services team to scale.
Hope everyone tries what might become the best GEO software on the market.
How do your AI agents evaluate whether a third-party listicle or community thread is actually indexable by perplexity? congrats🙌 @jose_pedro_nunes
CTO at Reach here 👋
A few things I'm proud of from the engineering side: you drop in your domain and in minutes our agents map your competitive landscape, mine the actual prompts your buyers ask AI, and build a prioritized roadmap. All backed by live citation tracking across ChatGPT, Perplexity, Gemini and AI Overviews. Happy to answer any technical questions about how it works under the hood!
Hey Product Hunt 👋
I hunted this one. Full disclosure: I help run growth at Reach, so I'm biased. I wanted to be the one to show it to you because I've watched it work.
For the last year, the team ran SEO and AI search as a done-for-you service for companies like Carro, Indie Campers and Fraudio. It drove millions in inbound revenue. ReachOS is the system behind that work, and today it's open.
What won me over:
You drop in your domain, and a few minutes later you've got a brand profile, your keywords, the prompts your buyers actually type into AI, and your topic map. No blank screen, no week of setup.
One view shows where you stand on Google and inside ChatGPT, Perplexity and AI Overviews. Not five tabs. One screen.
Most tools stop at "you're invisible in AI" and leave you there. ReachOS gives you the next move, ranked, with a clear line to revenue.
Content Studio takes a keyword from research to brief to a draft you can publish. It writes from your own knowledge base, so it sounds like you and not generic AI filler.
It even shows you the exact pages and Reddit threads where AI is citing your competitors, then drafts your outreach and replies to get you in there too.
Reach was submitted on Product Hunt and earned 51 upvotes and 30 comments, placing #14 on the daily leaderboard. Reach is the operating system to win AI search. Your marketing team and AI agents work in one place, doing the work that actually gets you recommended by ChatGPT, Perplexity and Google in the prompts that matter for your buyer journey. From finding the demand, to executing content, mentions and community, to measuring and attributing the revenue.
Reach was featured in SEO (38k followers), Artificial Intelligence (475.9k followers) and Search (18.1k followers) on Product Hunt. Together, these topics include over 126.4k products, making this a competitive space to launch in.
Who hunted Reach?
Reach was hunted by Alexandru Muresan. 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.
Want to see how Reach stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Alexandru Muresan