DeepFashion My Journey from Idea to Sale

Introduction

My entrepreneurial journey with DeepFashion, an AI-powered clothing design platform, was a rollercoaster of challenges, pivots, and triumphs. As the founder, I navigated the startup process from a spark of inspiration to a successful sale, learning invaluable lessons along the way. This story, drawn from my own reflections, offers a firsthand account of building DeepFashion, blending my background in fashion with cutting-edge AI technologies.

The Spark That Started It All

In April 2023, I was captivated by a new release from MidJourney, an AI tool that could generate images from text prompts. Paired with the power of ChatGPT, it ignited an idea for DeepFashion—a platform to revolutionize fashion design through AI. Growing up with family in Hangzhou’s fashion industry, I’d absorbed enough insights to know this was a field ripe for innovation. After running feasibility studies, I confirmed AI could transform tasks like creating product descriptions, social media content, video scripts, customer service chatbots, and even clothing designs.

What I Envisioned for DeepFashion

• Fashion Advice: AI-driven style recommendations.
• Product Descriptions: Compelling write-ups for e-commerce.
• Social Media Content: Engaging posts to draw in users.
• Short Video Scripts: Scripts for promotional videos.
• Customer Service: AI chatbots, including Retrieval-Augmented Generation (RAG) for after-sales support.
• Design Generation: Turning text into visual design drafts and clothing mockups.
• Diving into Development and Market Validation

I jumped in by testing MidJourney and ChatGPT, designing a prototype T-shirt by April 22, 2023. I crafted a PowerPoint pitch and shared it with designers and clothing company owners, who showed genuine interest. Their feedback validated my vision of an AI platform that could streamline fashion design and marketing.

To formalize the idea, I drafted a business plan (BP) under the name “Zero Fashion” with a friend from my first company, an AI expert with fashion-related startup experience. He’d seen my social media posts and reached out. We hashed out the BP at Tim’s Cafe, covering market opportunities, business models, core tech, and competitive strategies.

Building a Team—and Facing Tensions

Initially, it was just me and my AI-expert friend. Knowing a strong user interface (UI) and user experience (UX) were critical, I reached out to a former OmniEdge colleague, a Malaysian developer in Singapore who could handle design, front-end, and back-end work. He was excited, but when I suggested offering him equity to lock in his commitment, my friend pushed back hard. He believed we’d already secured investment and saw no need to give shares so early.

This disagreement fractured our partnership. My friend even suggested I step back to become a financial advisor (FA), taking a commission while he led the project independently. I was deeply frustrated but decided to be transparent, informing our clothing company partners about the split since we’d been discussing potential investment. Reflecting on this, I realized rushing into a co-founder relationship was a mistake. I learned to prioritize solo decision-making early on, bringing in team members only when absolutely necessary.

Going Solo and Embracing AI

After the split, I doubled down on my own. I dove into AI research, leveraging my IT background to rent A100 GPUs for training Stable Diffusion models. Using a mix of sourced and AI-generated images, I built a custom AI for fashion design. Remarkably, about 80% of DeepFashion’s code was AI-written—I just tested and deployed it. This approach let me develop and iterate quickly, adding features and rolling them out to users.

I recorded demo videos for each new feature, promoting them to fashion designers both in China and abroad. Their feedback helped refine the platform. To manage costs and protect intellectual property, I opted for foreign cloud vendors like AWS, Digital Ocean, Runpod, and Replicate, as domestic providers raised concerns about unencrypted Stable Diffusion models.

Scaling Up and Surprising Success

DeepFashion grew into a Software-as-a-Service (SaaS) platform with nearly 10,000 users, showcasing AI’s power to scale applications. Designers loved its ability to generate designs, descriptions, and marketing content. The high cost of computing power was a hurdle, but using trusted foreign cloud vendors kept my IP safe.

To my surprise, DeepFashion was eventually sold—a rewarding end to a journey that started with a simple idea. Navigating technical challenges, team conflicts, and market demands made the sale all the more gratifying.

Lessons I Learned

• Test Ideas Early: Engaging with industry players validated DeepFashion’s potential from the start.
• Pick Partners Carefully: My hasty partnership led to conflict; solo leadership early on would’ve been wiser.
• Use AI to Build: AI-generated code sped up development, proving it’s a game-changer for lean startups.
• Safeguard IP: Choosing reliable cloud vendors protected my technology.
• Iterate with Users: Rapid updates and designer feedback kept DeepFashion market-ready. Conclusion

My DeepFashion journey showed me how AI can transform industries like fashion while teaching me the grit needed to build a startup. From harnessing MidJourney and ChatGPT to selling a thriving SaaS platform, I learned to adapt, innovate, and stay focused. To fellow entrepreneurs, I say: test your ideas, choose your team wisely, and let AI amplify your vision. The road isn’t easy, but the rewards are worth it.