HugoGen
AI-native product development workspace for any team
8 followers
AI-native product development workspace for any team
8 followers
Hugogen is an AI workspace for teams and AI agents. Build with Projects for tasks across list, board, calendar, and gantt; Documents with block-level AI; AI Chat for research and deep questions; Designer for product photos, social posts, ads, and short video. Used by 1,000+ businesses across US, India, Brazil, Singapore, Indonesia, Australia, Japan, and beyond.
Hey Product Hunt 👋
We're master's students at NUS, and we built HugoGen because every creator and business owner we interviewed was drowning in the same problem.
To make a single piece of social content, you have to brief ChatGPT for the caption, design in Canva, edit the video in CapCut, plan in Notion, files in Drive and re-explain your brand to every tool along the way. By the time the post is live, you've wasted 6 hours for one piece of content, and the next one is already due.
HugoGen is the AI designer team to make selling content in minutes.
Here's what's inside:
🎨 Designer generates social content of images and videos in your brand style. Edit any element directly without breaking the rest of the image.
✍️ Documents writes captions, product descriptions, and campaign briefs that sound like you, not a generic AI.
💬 Chat brainstorms with you and pulls from your brand library so the answers fit your business, not just any 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.
Vision
HugoGen will be the AI infrastructure for selling online, from content creation to agent-ready commerce.
One brand context, no more juggling apps, let AI do the rest.
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!
RiteKit Company Logo API
@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.