Honestly launched this past Monday and we ended up Top 4 with 350+ upvotes and 40+ comments. It doesn t feel real, because:
1. The support we received from hundreds of strangers across the internet was incredible, and we are beyond grateful for it.
2. We didn t plan this launch. At all.
We ve been so deep in building the product that we kept pushing our launch back again and again and again. All of a sudden, on Monday we woke up to dozens of Congrats on the launch! messages. In our pre-coffee, foggy brained states we were really confused as to why. But then it hit us: we forgot to change our launch date.
To make matters worse, we didn t have any of the essentials: No hunter, no maker comment, no demo video (added in midday). There was just a placeholder of v0 materials we already iterated upon internally countless times. Our logo was even outdated, and the link to our product and website was nowhere to be found in the comments. Not one upvote or comment came from anyone we knew within the first hours of launching.
Because our day wasn t crazy enough, the website broke, so most businesses couldn t fill out our interest form properly, and our consumer facing Chrome extension encountered a huge bug where users couldn t use our product after installing it.
A situation like this usually means guaranteed failure, yet to our surprise, we climbed to a Top 5 position on the leaderboard and were swarmed with PH notifications all day. Even outside of Product Hunt we were being battered with notifications.
We re extremely thankful for the outcome, especially considering the circumstances. This is not a scenario that happens often, but it proved something vital to us:
Even with a shell of a launch, we re making something people want.
We always believed finding real, trustworthy reviews online mattered. But this experience made it clear it s not just important, it s necessary. As AI-generated content continues to blur the line between real and fake, the need for verified, authentic opinions is clear. That s the mission we re pursuing with Honestly.
Honestly
Hey Product Hunt 👋 I'm Scott, part of the founding team at Honestly.
Why we built it:
Bots and AI agents now generate more internet traffic than humans.
Your customers talk about your products every day across social media. But as AI-generated content, sponsored posts, and fake reviews become more common, finding authentic customer feedback is getting harder by the minute.
Today teams either spend hours scrolling social feeds themselves or rely on expensive tools that surface more noise than insight - but this felt wrong to us.
What Honestly is:
Honestly finds & verifies all customer conversations about your products, so you get honest insights built on data you can trust.
Simply enter a product by its name on our platform, and Honestly will help you:
Build better products by understanding exactly what customers love and dislike
Improve marketing by uncovering trends and high-performing content
Identify competitor weaknesses and market opportunities
Generate custom reports tailored to your business needs
What we believe:
As AI-generated content continues to flood the internet, authentic customer conversations will only become more valuable.
The companies that win will be the ones that can find real consumer data online, understand it quickly, and convert it into informed product and marketing decisions.
That's what we're building with Honestly.
Product Hunt offer (first 500 signups only!):
As a thank you to the Product Hunt community, we're offering a special deal to the first 500 signups that use code HonestlyPH26 when signing up for early access on our website:
🎉 7-day free trial
🎉 25% off for LIFE
We'd love to hear about:
How you currently gather customer feedback from social media
What’s most frustrating about finding real customer opinions today
How AI-generated content is impacting your customer research process
Thanks for checking out Honestly 🙏
@scott_davidson_jr Hey @byalexai, good hunt! Scott, congratulations on the launch! Honestly looks like a really interesting product. :)
I was wondering how you filter AI-generated content. Users might sometimes write their feedback and then rewrite it with AI into a polished version. Does your system detect whether a real opinion was AI-polished, or do you have a specific method for identifying and filtering AI content?
Also, is there a sample report available to view? When I visited the website, I only saw the waitlist and couldn’t find much beyond that. But I saw a glimpse of the report in the launch video.
Happy launch day! :)
Honestly
@byalexai @rohanrecommends Hi Rohan, great question! For detecting whether or not a post is AI generated, we have internal tooling combined with partnerships with leading AI detection models for image, video, audio, and text detection i.e. CheckReality.ai. This way we ensure with high confidence that the social media content we are providing our clients consists of authentic opinions.
As for the sample report, I believe you were referring to the customizable reports generated on a case-by-case basis. Because those are highly tailored, we'll provide a personalized report to everyone who books a demo for early access to the Honestly product by visiting our website :)
Appreciate the comment, questions, and support once again Rohan!
@scott_davidson_jr @byalexai @rohanrecommends I was going to ask the same question about identifying/filtering the AI content. With AI tools becoming more sophisticated by the minute, how can you stay ahead and verify authenticity?
Honestly
@byalexai @rohanrecommends @anna_ludwinowski Our partnerships with lead AI detection partners and internal tooling that ingest variables about social media posts like text type/structure, account history, and other factors ensure high confidence in classifying posts as authentic or not. Thanks for the question!
@scott_davidson_jr @byalexai @rohanrecommends Congrats on the launch! Very cool product and I can see it's usefulness across a variety of applications. My question was around filtering the content for authenticity and AI fingerprint but you've touched on that in some of the replies already.
Honestly
@scott_davidson_jr @byalexai @rohanrecommends @anna_ludwinowski Thanks for the kind words!!
Omnify, Inc
@scott_davidson_jr Looks great. Will try out today
Honestly
@kabandisaikia Thanks so much Kabandi! What do you think your biggest use case might be?
Honestly
@scott_davidson_jr @kabandisaikia Thanks Kabandi!
Honestly
@muhammad_azhar21 thanks so much! Would love to what specifically you like most (or maybe have most to say about) for Honestly?
@scott_davidson_jr Congrats! How does Honestly verify that a conversation is genuinely from a real customer, and can teams tune the confidence threshold or sources you check to match their product category?
Honestly
@scott_davidson_jr @swati_paliwal thanks! The organic vs sponsored vs AI scoring is universal using a set of custom algorithms on the sponsorship detection along with AI detection partnerships (I.e. checkreality.ai). We then tailor the filtering and data ingestion based off of your use case. (Affiliate detection, product development etc..)
As a founder, I care a lot about what people actually say when they are not filling out a feedback form or answering a survey. Reddit threads, TikToks, comments, and random posts often contain much more honest product feedback than the “official” channels.
The hard part is separating real signals from noise, especially now that so much of the internet is either AI-generated, sponsored, or just recycled takes. So I like the idea of focusing on verified conversations and turning them into something a team can actually use.
Curious how Honestly decides what counts as authentic or trustworthy feedback. Do you show the original source and context behind each insight, or mostly the summarized findings?
Also, how well does it work for early-stage products that don’t have a huge amount of mentions yet?
Honestly
@andrasczeizel Thank you for the detailed comment and questions Andras! Besides the partnerships with leading AI detection models mentioned in Rohan Chaubey's comment to detect AI content, we separate organic vs. sponsored posts by analyzing the account, tags, mentions, script, and video/image of the post itself. There are various signals that determine whether or not a post is an underlying advertisement across the aforementioned modalities, and we developed an algorithm internally to differentiate the two.
As for how Honestly works with early-stage products, many of our smaller teams have used competitive analysis of products with a more established social media presence to not only analyze competitors but better understand what content topics and formats attract engagement.
What sort of methods have you seen earlier-stage startups use to find these mentions so far? And where do you think the bottlenecks lie?
@scott_davidson_jr Thanks for the detailed answer, Scott, that makes sense! :)
From what I’ve seen, earlier-stage startups usually do this in a very manual way. They search Reddit, X, TikTok comments, YouTube comments, Google, sometimes even Discord communities, then try to save interesting mentions in Notion, Slack, or a spreadsheet. It works when there are only a few mentions, but it breaks pretty quickly.
For me, the bottleneck is not only finding mentions. It’s understanding which ones actually matter. A random comment, a repeated complaint, a competitor comparison, or a TikTok with strong engagement can all mean very different things.
For early-stage teams, I think competitive analysis is probably the strongest entry point. Even if people are not talking about your product yet, they are already talking about the problem, the category, and your competitors. Being able to turn that into product and marketing insights could be very useful.
@scott_davidson_jr @andrasczeizel The competitive analysis angle makes a lot of sense for early-stage. If nobody’s talking about your product yet, they’re already talking about the problem and competitors - still valuable signal. Do you see teams successfully converting that into insights early on?
Honestly
@andrasczeizel Love where your mind is at - focusing on understanding which ones matter rather than just finding mentions. This is the biggest challenge for most founders & earlier stage teams. I couldn't agree more with your approach and this focus on the problem, category, and competitors are the exact services many of our smaller teams request. Thank you for your detailed thoughts and engagement with our launch!
SlimSnap
Reddit is the hardest of these sources to pull from cleanly. It's hostile to automated access, and half of what reads like a "real opinion" there is planted marketing. How are you handling both sides: getting the data reliably without tripping Reddit's defenses, and separating the astroturfed stuff from the genuinely useful threads?
Honestly
@bickov You bring up some great points - these are both very valid concerns when trying to find the right data. For the hostility to automated access, we have been able to crack the code so to speak using some of our proprietary algorithms and reliably pull Reddit data about specific products over and over. As for the planted marketing, this occurs all the time. Some of the biggest indicators of if the post is marketing trying to disguise itself as authentic revolve around the text itself, the upvote count, subreddit it is posted in, and other details specific to the account. However, this is an issue we have been able to address well based on variables relevant to the post like the one I mentioned.
Sounds like you had experience with this problem firsthand - I'm curious to know what methods you tried and how successful they were?
SlimSnap
@scott_davidson_jr Honestly mine's the other side of your problem, the posting side, not scraping. I've done genuine community marketing on Reddit and what surprised me is how often authentic activity trips the same defenses as spam. Real participation gets flagged or removed even with zero automation behind it.
On telling planted from real, my best heuristic lines up with what you said: genuine opinions tend to show up buried, an offhand line in an unrelated thread or an old comment nobody upvoted. The marketing is the suspiciously clean, on-topic, top-level post. The more a "review" looks purpose-built to be found, the less I trust it. Does your scoring weight how buried a comment is? That's been my strongest signal as a reader.
@scott_davidson_jr @bickov The “buried comment” signal is super real. The more polished and on-topic a review looks, the less I trust it. Do you factor in thread depth or context in your scoring?
Honestly
@scott_davidson_jr @bickov @jared_salois For sure! We have that as a variable, and actually showcase the reviews as part of the thread if they are a reply. To verify a product, the three primary variables we focus on are pattern matching, context analysis, and AI detection software.
across TikTok, Reddit, and X specifically because those three have wildly different norms for what an authentic mention even looks like. a Reddit comment buried in a thread reads as more trustworthy by default than a TikTok video because TikTok incentivizes content creation in a way that distorts organic opinion. curious whether the verification weighting accounts for that platform difference or treats a mention the same regardless of where it came from
Honestly
@ansari_adin Yes! Each platform is analyzed for authenticity in its own way since each one has different algorithms, UIs, organization structures, and styles of how content is posted. This is an important question and one that should not be overlooked when reviewing tools like Honestly!
Interesting idea. How do you determine whether a comment is actually authentic versus just engagement bait or bot activity?
Honestly
@workout097_collab Great question! It is the core what makes our company - we not only partner with leading AI detection models such as CheckReality that specialize in imaging, video, & text modalities but our internal algorithms also ingest variables like text content, account history & activity, etc. to classify a post with high confidence. What do you think the biggest use for telling the difference between the two is for your company?
@scott_davidson_jr Probably product research. I'd rather build based on genuine user opinions than AI-generated comments that all sound convincing but don't represent real users.
Honestly
@scott_davidson_jr @workout097_collab 100%, just another reason why we're working hard to build out the world's largest authentic opinion dataset!
Honestly
@workout097_collab We have our own algorithms and models to determine whether posts are sponsored or organic, and we partner with leading AI detection models (such as checkreality.ai) for image, audio, and video authenticity. This way we ensure with high confidence that the social media content we're providing our clients consists of authentic opinions.
@honestly That's interesting. The sponsored vs. organic distinction is probably just as important as AI detection. I'd be curious to know how accurate those classifications are in practice.
Honestly
@honestly @workout097_collab In practice the classifications are done with very high accuracy. To determine that for yourself, I encourage you to test it out for yourself with our free demo offering!
Great work! Honestly seems like it is primarily geared towards larger companies since a demo is required to move forward with the platform. However, we are a small team. Do you have any self-service options for startups or small teams? The competitive analysis features seems compelling our this category of clients.
Honestly
@hoa_do_012 Thanks for your question! We serve both larger enterprises and early stage startups. We currently have a self-service option for startups/smaller teams on the roadmap, but for now are meeting with each customer to ensure we meet their needs since the insights businesses require varies based on the stage they are in as well as the industry. Competitive analysis has been one of the most popular services for our smaller team clients so far. Beyond competitive analysis, is there another type of insight you'd like to see in the self-serve version of Honestly?
Honestly
@hoa_do_012 Self service is coming real soon 👀
Finding out real customer opinion is really hard these days. By the time teams find these opinions customers already reach to it
Curious, can Honestly help me pick up on complaints across niche communities. for example developers flagging same issue across multiple forums. (something of that pattern). It would be a real game changer.
Honestly
@pradyumna6 Definitely agree! And 100% we can. We run sentiment analysis on all posts about the product or product keyword you're interested in. So anytime there is a specific issue that repeatedly pops up, our insights engine will let you know about it.
Are complaints the only area of interest or are you also curious about the product attributes customers enjoy the most/ are most popular?
Honestly
@pradyumna6 Definitely, customers that complain show the opportunities you can capitalize on. Product attributes are interesting as well since they are a form of playbook for growth - you see what already is popular, receive views/engagement, then capitalize on it.
Speaking of market gaps, how do you currently go about finding them & what challenges do you face when doing so?
@scott_davidson_jr Personally, I spend a lot of time in niche subreddits and on twitter looking for honest customer conversations.
The hard part is the scraping. Going thread by thread, trying to figure out whether a complaint you keep seeing is a widespread pain point or just one frustrated person having a bad day.
If its a common complain then i would do my research and find out if it is a gap that we could build on.
That distinction between opportunity and noise is everything.
Honestly
@pradyumna6 Scraping is much more difficult than most believe, and you're correct in saying that many of the real customer conversational gold lies in these niche forums/ communities. Cracking the code here is key and is why we have been able to get as far as we have! Thank you for your thoughtful comments and for engaging so much with our launch!