Launched this week
HugoGen
Hire one AI marketing team instead of five tools.
8 followers
Hire one AI marketing team instead of five tools.
8 followers
HugoGen is the AI marketing team for online sellers. It learns your brand once, runs your campaigns everywhere, and gets your products ready for every buyer, human or AI.
Hey Product Hunt 👋
We're two master's students at NUS, and we built HugoGen because every online seller we interviewed was drowning in the same problem.
To get one campaign out the door, you have to brief ChatGPT, design in Canva, plan in Notion, post manually on Instagram and TikTok, then update your product listings on Shopee, Tokopedia, TikTok Shop, and Shopify. Every tool needs a fresh re-explanation of your brand. By the time the campaign is live, you're exhausted and the next one is already due.
HugoGen is the AI marketing team that learns your brand once, then handles the rest.
Here's what your AI team does:
🎨 Designer designs images and videos in your brand style. Edit any element directly without breaking the rest.
✍️ Copywriter writes posts, captions, product descriptions, and campaign briefs that sound like you, not a generic AI.
💬 Strategist brainstorms with you, pulls from your brand library and past campaigns so the answers actually fit your business.
📁 Brand library holds your logos, products, voice, and past work in one place. Every tool above pulls from here, so you only explain your brand once.
🛒 Storefront lists your products in a structured way that AI agents can read. Today, humans buy. Tomorrow, when AI agents shop for people, your store is already there.
One brand context, five jobs, no more juggling tools.
Two bootstrapped master's students at NUS. Built this because we lived the problem.
Try it free at hugogen.com.
We'll be in the comments all day, honest about what works and what's still rough.
Thank you!
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@hesoyamcode Love that you're tackling the fragmentation problem—jumping between tools is genuinely exhausting. The context memory issue with AI chats is real too. One thing I'd be curious about: how are you handling the quality bar for generated images over time, especially as users iterate on designs. That's historically been the hardest part to solve well.
@osakasaul Hey Saul, thanks for asking. Two things help with this.
First, your brand library (logos, products, past designs, voice) stays the consistent input on every generation. So even when you iterate, the AI is pulling from the same brand context each time, which keeps outputs from drifting.
Second, we built element-level editing so when one part of an image is wrong, you can fix that part without re-rolling the whole thing. That "fix one thing, break four others" loop is what kills most AI design tools. Instead of regenerating until something works, you adjust directly.
Still early. Some generations miss today, and we have a roadmap to push the underlying design quality further over time. The editor is built around the reality of AI that isn't perfect yet.