Kluster

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AI/ML

Conversing with an E-commerce Store Database

Summary

Transform how businesses interact with data by building a system where non-tech savvy users can query an e-commerce database using simple, everyday language. This challenge is all about bridging the gap between complex data management and intuitive user experience.

Requirements

Implement an AI agent to convert natural language queries into SQL.
Design a user-friendly chat interface.
Provide a demo e-commerce database.
Include a tutorial or help feature for new users to learn the system.

Submission Guidelines

Figma (Optional): Provide a link to your Figma design / prototype for your project.
GitHub Repository: Provide the link to your GitHub repository containing all the relevant source code and project files.
Deployed Link: Share the link to the deployed version of your project. For web applications, consider hosting on platforms like Netlify or Heroku. If it's a mobile app, upload the APK to Google Drive and provide a public link.
Walkthrough/Presentation: Create a concise 2 to 5-minute maximum screen recording. Walk through key features, functionalities, and any unique aspects of your project. Clearly articulate how users can interact with and benefit from your solution. Ensure your presentation covers essential details without exceeding the time limit.

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Limited OpenAI API keys available at no cost for your hackathon project. Reach out here with your use case, and get keys for Speech-to-Text, Chat Completions, Embeddings, and more. Keys deleted post-hackathon.

Explore Models

You have the freedom to explore a wide range of models for your project. Not limited to the following options:

Additional Resources

Take your project further with these valuable resources:

Suggested Approach

Day 1 - 2: Concept Development & Framework Establishment

Product Management & AI/ ML Specialists:

Define the project scope and the functionalities of the AI agent.
Begin exploring AI models for natural language processing (NLP) that can translate user queries into SQL commands.

Backend Development:

Set up a demo e-commerce database with a range of products and categories.
Begin integrating the AI model with the database.

Frontend Development & Product Design:

Design a chat interface that is user-friendly and intuitive.
Ensure the interface aligns with the non-tech savvy user base.

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Day 3 - 4: AI Integration and Interface Development

AI/ ML & Data Science Specialists:

Integrate and fine-tune the AI model for accurate query interpretation and SQL translation.
Implement logic for handling a variety of query types.

Frontend Development:

Develop the chat interface and connect it with the AI backend.
Implement real-time query responses and feedback loops.

Product Design & Management:

Conduct user testing with mockups or prototypes.
Gather feedback for interface and interaction flow improvements.

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Day 5: Refinement, User Education, & Presentation

All Team Members:

Finalize the AI agent and chat interface based on user feedback.
Create a tutorial or help feature to educate new users about the system.
Conduct thorough testing to ensure reliability and user-friendliness.
Prepare a presentation highlighting the system's capabilities, ease of use, and potential impact on e-commerce data management.

Transform how businesses interact with data by building a system where non-tech savvy users can query an e-commerce database using simple, everyday language. This challenge is all about bridging the gap between complex data management and intuitive user experience.

Access Free OpenAI API Keys!

Explore Models

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Additional Resources

Day 1 - 2: Concept Development & Framework Establishment

Product Management & AI/ ML Specialists:

Backend Development:

Frontend Development & Product Design:

Day 3 - 4: AI Integration and Interface Development

AI/ ML & Data Science Specialists:

Frontend Development:

Product Design & Management:

Day 5: Refinement, User Education, & Presentation

All Team Members:

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