The problem SynthQL solves

SynthQL addresses the challenge of efficiently generating SQL queries, especially for users lacking in-depth SQL expertise. By harnessing natural language processing (NLP) and AI algorithms, SynthQL interprets user input, comprehends data structures, and produces SQL queries, thus streamlining the process and enabling users to convert human language requirements into SQL queries effortlessly. Additionally, by hosting the language model locally, SynthQL ensures data privacy and security while providing seamless query generation functionality.

Challenges we ran into

1. Understanding Human Language: Making sure the AI understands what users want in simple words, even if they're not SQL experts.

2. Figuring Out Data Structures: Teaching the AI to recognize how data is organized in databases so it can write accurate SQL queries.

3. Setting Up Local Hosting: Getting the AI to run smoothly on users' computers while keeping their data safe.

4. Making It User-Friendly : Designing an interface that's easy to use, even for people who aren't tech-savvy.

5. Testing Everything: Checking that the AI works correctly across different situations and databases.