Define the problem
- Identify the key issues or needs that Talkin' Text aims to address.
- Determine the target audience and specific use cases for the app.
Train the NLP Model
- Define the purpose and scope of the NLP capabilities.
- Choose an appropriate NLP model, such as the LLaMA 3 Transformer Model.
Build the app
- Develop the core functionality to accept and process PDF, DOCX, and TXT files.
- Implement the interface for users to upload documents and ask questions.
Launch the app
- Conduct thorough testing and quality assurance.
- Launch Talkin' Text to the public with initial marketing efforts.
Update the app
- Based on user feedback, plan and release updates to improve features and fix bugs.
- Introduce enhancements for better user experience and performance.
Train the NLP Model
- Regularly update and fine-tune the NLP model to improve accuracy and response quality.
- Incorporate new data and user interactions to make the model more robust.
Collect and Label Data
- Gather a diverse set of user inputs and interactions to continuously improve the chatbot's understanding and responses.
Add more features
Ongoing
- Enable the app to handle and respond to multimedia inputs, such as images, videos, or audio clips.
- Implement advanced features like multi-session management and history tracking.
Evaluate and Iterate
Ongoing
- Regularly evaluate the app's performance and user satisfaction.
- Plan and execute iterative improvements based on ongoing feedback and technological advancements.
Missing a feature?
Anything you're missing in our product? Drop
a message here to let us know!
Copyright © 2024 GradientArc