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p/intimid-ai-matchmaking
p/intimid-ai-matchmakingDating apps make you audition. Matchmakers cost thousands. We’re building a third option.
Andreas Jablonka:@alexander_friz first of all its exclusively for long term relationships. not hook-ups or casual anything. secondly introverts and re entry daters (divorced people, surviving-spouses, single parents) are underserved they have it harder in the dating world.often seen as less desirable and often value character over visuals. if you just want a hot girl/guy go on tinder. no judgement. but us more experienced humans learned compatibility is about learning what the other person is like, what drives them, their needs and wants. THAT is what we match on. not looks. the Avatars bridge the gap between no fotos and tough visual quo you will recognize the user when you see them on the video call or ultimately the first date.
in p/intimid-ai-matchmaking
p/intimid-ai-matchmakingDating apps make you audition. Matchmakers cost thousands. We’re building a third option.
Andreas Jablonka:@sseanyd we are definitely trying to bring dating back to the authentic human. not the performances chasing IG style dater who wants matches and collects likes. we include free audio and video chatting in the app so you get feeling for your match before you meet them.
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p/general
p/general83% of large enterprises have deployed AI. 18% of businesses under 50. Why is it going top-down?
Samuel Adedigba:I think part of the gap is that adopting AI isn't just “pay for a tool and start using it.” Larger companies usually already have structured data, documented workflows, APIs, approval processes, and people who can integrate AI into those systems. A small business may still be running important operations through WhatsApp, spreadsheets, email, and knowledge that exists only in the owner’s head. So even when the AI itself is cheap, making the business ready to use it safely can be expensive. That makes me wonder if the bigger opportunity isn’t cheaper AI, but products that meet small businesses where their workflows already are instead of asking them to become “AI-ready” first.
in p/general
p/general83% of large enterprises have deployed AI. 18% of businesses under 50. Why is it going top-down?
Gal Dayan:I don't think it's purely a capital problem, it's more that big companies already have a safety net for being wrong - compliance, legal, a QA layer - so an AI mistake gets caught before it reaches the customer or the auditor. a solo accountant or small law office doesn't have that layer, so an AI error becomes their personal error with their name on it. PCs and mobile never asked you to trust an output, they just gave you a tool to produce your own. AI is the first general purpose tech that asks the small operator to vouch for something they didn't fully create, and that's a much scarier ask when you have no one to catch it if it's wrong
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p/self-promotion
p/self-promotionWhat are you building? Drop your AI product below
Samuel Adedigba:What I’m building: Stepper an AI inference orchestrator for applications that need more reliable model execution instead of depending on a single provider call. Who it’s for: Developers building AI products that need retries, provider failover, queue-based execution, caching, circuit breakers, and better handling when models rate-limit or fail. Hardest part right now: making reliability feel simple for the developer using it. The interesting part of AI apps isn’t always getting a model to answer, it’s deciding what happens when that provider is slow, unavailable, rate-limited, or returns something unusable. I’ve been building around that layer with TypeScript, BullMQ and Redis, and I’m still refining how much complexity Stepper should hide vs. expose to developers. Curious how other AI builders here handle provider failures today, build the reliability layer yourselves, or depend mostly on one provider?
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p/introduce-yourself
p/introduce-yourselfHey Product Hunt 👋 I’m Samuel
Samuel Adedigba:Also curious to meet other builders from Africa here 👋 If you’re building from Nigeria or anywhere across the continent, drop what you’re working on. I’d genuinely like to discover more of what’s being built around here.
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p/life-lopp
p/life-loppLifeLoop is officially LIVE! 🚀
Sam Rizzi:Congrats!
in p/self-promotion
p/self-promotionCeptize, light version of Paysellable, knows what you should build next
Dinh Thoai Tran:Dear PH community, On 29 Aug 2026, I extracted 32 features from 3 products which are randomly picked out from 727 products launched on 28 Aug 2026, then picked out 5 features which passed uniqueness test. | Rank | Feature |Uniqueness | WTP | Combined Commercial Position | | 🥇 1 | Business Impact Intelligence for API Changes | ⭐⭐⭐¾ | ⭐⭐⭐⭐⭐ | Exceptional WTP + strong differentiation | | 🥈 2 | Production Behavioral Observability for Regexes | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | Highest uniqueness + strong WTP | | 🥉 3 | Autonomous Loading-Dose Optimization | ⭐⭐⭐¾ | ⭐⭐⭐⭐½ | Very high WTP + highly differentiated | | 4 | Autonomous Safety-Constrained Exercise Optimization | ⭐⭐⭐¾ | ⭐⭐⭐⭐ | Strong pain/WTP, but crowded | | 5 | Continuous Individualized Functional-Capability Optimization | ⭐⭐⭐¾ | ⭐⭐⭐⭐ | Good market, but least differentiated | Best regards, Dinh Thoai Tran
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p/ama
p/amaHi there 👋 I'm Elizabeth co-founder and General Partner at Hustle Fund. AMA
Konstantin Tikhaev:building with coding agents taught me trust breaks when you are told everything is fine while silent erors pile up. without pmf the polite nods are that exact false green light ) you have to hunt for the breaks, not the validation
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p/murmell
p/murmellDrop your startup below 👇
Moss’Ab Mirande-Ney:@kyle_peter1 Thanks man! And LUTRipper is actually a really cool idea, especially the camera-specific recipe part. 👀 For Murmell, not branches under the hood. All agents work in the same working directory / repo. The tricky part is preventing them from stepping on each other, so we built a file-level claim system: before an agent writes, it claims the paths it needs. If another agent is already working on one of them, it has to wait or work somewhere else. That way agents can actually see each other’s changes as they happen, instead of having 3 separate branches and merging everything at the end.