AdVinci

AdVinci

Crafting Personalized Promotions with AI Precision

AdVinci

AdVinci

Crafting Personalized Promotions with AI Precision

Describe your project

AdVinci is an AI-powered solution for generating customized promotional content using the Flux model with product-specific LoRA fine-tuning.

  1. In-scope:
  • Flux model core with LoRA training for each product
  • Generation of banners and videos from text prompts
  • Incorporation of product images, offers, colors, and themes
  • Multi-format output for social media and websites
  • User-friendly interface for non-designers
  • Fast, scalable content generation
  1. Out of scope:
  • Original image creation or editing
  • Promotional copy generation
  • Automated social media posting
  • Performance analytics
  • Interactive or AR content creation
  1. Future opportunities:
  • E-commerce platform integration
  • Expanded output formats (GIFs, HTML5)
  • AI-driven A/B testing
  • Automated campaign generation
  • LoRA model marketplace
  • Personalized content based on customer data
  • Expansion to packaging and in-store display design
  • Cross-modal applications (audio to image)

Challenges we ran into

The biggest challenge we encountered was properly generating and managing text for our promotional content. Ensuring that the text was contextually appropriate, grammatically correct, and aligned with the visual elements proved to be more complex than anticipated. We addressed this by:

Implementing a robust natural language processing pipeline
Creating a curated database of promotional phrases and templates
Developing a feedback loop system to refine text generation based on user inputs

Integrating Flux and LoRA
Another significant hurdle was making the Flux model work seamlessly with LoRA fine-tuning for individual products. This integration was crucial for achieving the level of customization we desired for each of the product. We overcame this challenge by:

Experimenting with different integration architectures + lot of experimentation with prompt Engineering.
Fine-tuning our approach to balance general Flux capabilities with product-specific LoRA adaptations.

Tracks Applied (1)

9. Problem statement shared by BigBasket

How AdVinci solves these challenges: Text Generation: Implemented an NLP pipeline with feedback mechanisms for contextu...Read More

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