Text Recommendation

Inspiration

We've all experienced the struggle of finding the right words for a client email, starting a conversation with a colleague, or striking the perfect balance between formality and informality. Text Recommendation aims to alleviate this common communication challenge.

What it does

Our app analyzes the sentiment of incoming texts and provides tailored reply suggestions, offering options in various styles (business formal, casual, etc.) and tones translation features. Additionally, it allows users to learn from the recommendations, enhancing their communication skills.

How we built it

We combined a robust tech stack, including Ruby on Rails, TRON, TronWeb, Solidity, Bootstrap, StimulusJs, Gemini-AI, and render.com, to bring Text Recommendation to life.

Challenges we ran into

Maintaining consistency in AI-generated responses was a significant challenge. We plan to refine this through further model tuning.

Accomplishments that we're proud of

We successfully developed a working prototype and achieved seamless blockchain integration.

What we learned

Building Text Recommendation offered valuable insights into Blockchain, Frontend Development, and Smart Contracts.

What's next for Text Recommendation

• Expanding query parameters for more versatile text recommendations.
• Optimizing the AI model to deliver more consistent and reliable responses.

Built With

• bootstrap
• geminiai
• render.com
• ruby-on-rails
• solidity
• stimulusjs
• tron
• tronweb