A Tool Solving the AI Problem by Using AI

Learn how Saquib used his knowledge in AI to create a tool which helps people in the creative industry stay consistent with their AI generated characters.

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Happy Sunday. This week weā€™re welcoming back Saquib, an entrepreneur in the AI space who has created a tool which earns him thousands of dollars per month.

In the interview, we can learn from him about:

  • The importance of creating something which fixes a problem for the customer.

  • Using a content driven approach to build a customer base.

  • How previous projects can help speed up your processes on future work.

Now, over to Saquib!

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The Flux Train

Please tell us about yourself and your business?

I am a robotics researcher turned entrepreneur, combining a background in deep tech with creative industry experience. During my undergraduate years, I founded an animation company, which sparked my interest in bridging technology with creativity. My current mission is to enhance the adoption of generative AI in the creative industry, particularly in video production.

A significant challenge in video production is maintaining consistent characters across multiple scenesā€”a limitation of current generative AI solutions. My platform, TheFluxTrain, addresses this by allowing users to train characters easily and create storyboards featuring them. These storyboards can then be transformed into videos using our image-to-video generation capabilities. This is just the first step in realising a broader vision for revolutionising video creation with AI.

Why did you decide to build this product?

Over the years, Iā€™ve been deeply involved in fine-tuning and training image models, a process that is notoriously time-consuming due to the need for captioning individual training images. To simplify this, I developed a straightforward UI (using Nuxt.js for the front end and Node.js with Python for OpenAI integration) to batch-caption images efficiently. When I released this tool, it resonated with users and gained significant traction.

This success inspired me to tackle a broader problem in the creative industry: enabling more intuitive, scalable solutions for character and video creation through generative AI.

How did the build process look like?

Thanks to base code Iā€™d built in prior projects, I was able to create the complete appā€”including authentication and payment integrationā€”within 4ā€“5 days. The rapid development process was a result of leveraging existing resources and focusing on the most critical features for an initial release.

What did you do differently this time around?

This time, I prioritised early user engagement and marketing. I launched with a minimal landing page and basic features, promoting the platform on Reddit to gather initial feedback.

I also adopted a content-driven approach to attract users. Instead of solely promoting my platform, I wrote tutorials and blogs on Medium addressing the broader problem my product solves. For instance, my guide on fine-tuning image models (Saquib Alam, MS: A Noobā€™s Guide to Flux LoRA Training) gained traction, indirectly driving interest to my platform. This focus on educating users and providing value proved instrumental in converting interest into paying customers.

How will you monetise this? What do you think you'll expect to earn from it?

My platform operates on a credit-based model with no free plan or subscriptions. Users purchase credits as needed, ensuring a straightforward and flexible payment system.

Since launching three months ago, our monthly revenue has grown as follows: $350, $1,900, and $1,540. Based on current trends and our growth strategies, I expect to reach $5,000 per month within the next two months.

Where can people find you?

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šŸ‘‡ļø Now itā€™s your turn to answer a question:

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If youā€™d like to read Saquibā€™s previous interview. Check it out here.

Thank you all,

See you next week! šŸ‘‹