Genpire
Make Real Products with AI, literally.
730 followers
Make Real Products with AI, literally.
730 followers
Most AI stops at the idea. Genpire takes it to the factory. Think Lovable, but for consumer goods manufacturing - an agentic platform that turns prompts and sketches into products, collections, and factory-ready specs, then lets you work with your own factory or tap into a vetted network for instant quotation, sampling, and bulk production. One workflow, all the way from an idea to the factory floor. Genpire makes building physical products faster, simpler, and finally accessible to anyone.
Genpire
Hey Product Hunt 👋
Even with all the new AI tools out there, it’s still way harder to launch a physical product than to launch an AI-powered app. Creating something like a flip-flop brand or an accessories line, for example, still requires design skills, tech packs, sourcing, and navigating factory workflows - all slow, expensive, and deeply manual.
Genpire is here to change that.
We took the “vibe-coding” simplicity you see in tools like Lovable and applied it to real, physical product creation. Just describe your idea and Genpire generates your product visuals, technical drawings, multi-view renders, and a complete factory-ready tech pack in minutes - no design or manufacturing experience needed.
You can build handbags, sneakers, toys, beauty tools, lamps, apparel, gadgets - anything. Genpire supports eight major product categories, giving millions of people the ability to bring big ideas to life exactly as they envisioned them.
For Pro users, Brand DNA lets Genpire adopt your exact style and creative identity. And with our new Manufacturer Quotes, vetted factories can help you sample and produce your product faster than ever.
Would love your feedback - and if you drop an idea in the comments, I’ll generate a tech pack or full product concept for you. Let’s build your Genpire 👑
- Daniel Shoshani
PicWish
@daniel_shoshani1 def. a game changer for DTC brands. how does it handle technical accuracy for moving parts vs static objects?
Genpire
@mohsinproduct Well, moving parts are by nature more complex in terms of accuratly generating them from prompts using existing models. We're initially focus on what we call "Soft" categories - apparel, footwear, furniture, toys, accessories, bags, jewlery - a pretty wide range of consumer categories we're building in.
Thing is - we're aiming to make Genpire a cross-category, general-purpose platform - serving all consumers categories - as well as categories with so-called moving parts, which will require us to offer a deeper, more robust generative specs features.
We're on it! 🪄🏭
@mohsinproduct Great question, and honestly one of the more interesting engineering challenges we're working through.
For soft categories, which is our current focus, apparel, footwear, bags, accessories, furniture, the geometry is complex but the constraints are well-defined. We've built the generative pipeline to output structured specs with dimensions, tolerances, and materials that map to what factories actually need.
Moving parts are a different beast. The challenge isn't just visual accuracy, it's encoding mechanical constraints into the output, joints, pivot points, stress load areas. That requires a deeper spec layer that we're actively building toward. The architecture is designed to handle it, we're just being disciplined about not shipping it before it's reliable enough to trust.
Short answer: static and soft categories today, mechanical complexity on the roadmap. We're not cutting corners to get there faster.
Genpire
@daniel_shoshani1 Every shortcut on the surface only feels like magic because of the stack underneath holding it up. So proud to see this finally out in the world congrats on the launch, team!
Creatoor AI
@daniel_shoshani1 Make me a container for my backyard that is a coworking space with a desk and outlets for my laptop. Premium interior with standing desk that can be lowered height and chair with option for ergonomic chair.
Hey Product Hunt!
Esmat here — Co-Founder & CTO of Genpire.
I came up in enterprise security at Check Point, where the bar for "good enough" is set by the worst day a customer could have. That's the mindset I brought into building Genpire's technical foundation.
Genpire is an AI-native platform that takes any idea, sketch, or prompt and turns it into factory-ready files — design visuals, technical specs, materials, measurements, and manufacturer matching — all in one workflow. Under the hood, that's multi-agent systems working across design, technical, and sourcing layers, with structured data pipelines built to be reliable and compliance-ready from day one. SOC 2 Type II and ISO 27001 are in progress — because enterprise data handling should be designed in, not bolted on.
We built this to work for a solo designer with a big idea just as well as for a procurement team at a global retailer. That's the engineering challenge I wake up for every day.
Super excited to finally have this out in the world. Would love your feedback — drop your idea in the comments and I'll generate a tech pack for you right here!
— Esmat Nawahda
Genpire
@esmatnawahda that "worst day" framing is the exact mindset I steal every time I sit down to hammer out a new test. The real reason I'm stuck in the QA and marketing infra weeds is because we made a pact on day one: if it doesn't clear that bar, it doesn't ship. I’m incredibly proud of where we’ve finally landed. It’s a massive day for the whole crew
Creatoor AI
I've been waiting for this a very long time. If it works you have yourself a lifetime customer. Selfish ask, will you move to larger product sourcing, say container house? Asking for a friend 😂
Genpire
@olumidegbenro Thank you, Olumide!
Thing is - we're in the design-to-manufacturing business, interesting to see that more than 60% of our beta users already have their sourcing and supply chain all sorted out, while Genpire plays a role in their planning, design and specs workflows, in parallel with allowing them to manage the sampling process and sourcing through our agentic sourcing interface offered both for new comers who wants to use our built-in, vetted network of factories - or their own by inviting them to collabrate.
Container house are naturally on a later stage (and plenty of players in this space) - we might launch this on PH sometime during 2027 🏭🪄🍠
Interesting idea! Are you talking about manufacturing any product, or just clothing? We once built a system for one of the largest yogurt manufacturers in the world. In that system, we had to store formulas, ingredients, quality control, etc. In theory, AI can help with this, but it needs to be trained separately, and not the entire process can be automated with the current state of AI.
But even for clothing, I don’t fully understand how it can account for all sizes, materials, etc. You would need a very large vector database with information...
the factory-ready specs part is where i'd want to dig in. design to spec is a well-understood problem but 'factory-ready' means different things depending on material, category, and which country the factory is in. a spec that works for a Guangdong garment factory doesn't work for a Portuguese one. how is Genpire handling that variation or is it assuming a specific manufacturing context by default
The multi-agent pipeline across design, specs, and sourcing is the part that actually makes this more than a fancy Midjourney wrapper. What I'm curious about is where the handoff between agents happens? like does the design agent produce something and the spec agent independently interpret it, or is there a shared structured representation that gets passed through? Because that seam is usually where accuracy degrades.
Genpire
Hey Product Hunt :)
I’m Muharrem, part of the engineering crew over at Genpire. I spend most of my time head-down in our marketing platform and the QA backbone that makes everything tick basically, I’m the one ensuring the AI agents and brand tools actually hold up when we ship those tech packs. Genpire’s whole thing is flipping a simple description into a factory-ready product in literal minutes. Truth be told, even after watching this loop run through testing thousands of times, it still catches me off guard when a real, tangible RFQ pops out at the end. I’d love to hear your thoughts, so just toss an idea in the comments and let’s see what Genpire whips up for you.
Genpire
@myurtsever The backbone of the Genpire machine!