Through my work at STIGMA on their mental health app, I seamlessly navigated between front-end and back-end development, helping the team meet deadlines and exceed expectations. My journey began with developing an AI tool (Al-i), funded by an Amazon accelerator, to provide users with nearly immediate feedback using ChatGPT and user data. As a team, we trained our AI, refined the prompt, implemented the necessary UI, and deployed the feature. Post-accelerator, I spearheaded the development of an SMS posting feature, enabling users to more easily "ask for help," thus advancing STIGMA's goal of crowdsourcing hope to reach more people.

For the SMS feature, I independently developed a robust solution by migrating to AWS Lambda services, coding in JavaScript for Node.js instead of using Xano's built-in tools. Using SQL queries, I meticulously parsed the database to link messages with user accounts, creating new member IDs when necessary. Twilio streamlined the text message flow, collecting crucial data from users. This meticulous approach ensured that every message, whether from new or existing users, was properly associated with their accounts, enhancing accessibility and allowing more individuals to seek and receive support seamlessly.

Crowdsourcing Hope | A Mental Health App

STIGMA

Stigma Image
Project Timeline
SMS Deployment

Deploy SMS feature, collect user feedback, and iterate for continuous improvement of user experience and accessibility.

AWS Migration

Migrate to AWS Lambda, parse database, and integrate Twilio for comprehensive SMS feature functionality.

AI Development

Train AI using user messages, refine prompts, and integrate UI for seamless deployment and optimal performance.

Union 1
Lines

At STIGMA, I played a vital role in developing the AI tool, leveraging users' messages of hope to train our AI. Through iterative refinement and prompt engineering, we optimized the tool to generate postable messages effectively. We then seamlessly integrated it with the UI, prioritizing usability. Leveraging Xano for back-end support and Draftbit for front-end development, we ensured a smooth deployment. This comprehensive approach resulted in a feature capable of delivering personalized support and fostering a sense of community among users.

Stigma Team

STIGMA

Crowdsourcing Hope | A Mental Health App

Through my work at STIGMA on their mental health app, I seamlessly navigated between front-end and back-end development, helping the team meet deadlines and exceed expectations. My journey began with developing an AI tool (Al-i), funded by an Amazon accelerator, to provide users with nearly immediate feedback using ChatGPT and user data. As a team, we trained our AI, refined the prompt, implemented the necessary UI, and deployed the feature. Post-accelerator, I spearheaded the development of an SMS posting feature, enabling users to more easily "ask for help," thus advancing STIGMA's goal of crowdsourcing hope to reach more people.

For the SMS feature, I independently developed a robust solution by migrating to AWS Lambda services, coding in JavaScript for Node.js instead of using Xano's built-in tools. Using SQL queries, I meticulously parsed the database to link messages with user accounts, creating new member IDs when necessary. Twilio streamlined the text message flow, collecting crucial data from users. This meticulous approach ensured that every message, whether from new or existing users, was properly associated with their accounts, enhancing accessibility and allowing more individuals to seek and receive support seamlessly.

Lines
Project Timeline
SMS Deployment

Deploy SMS feature, collect user feedback, and iterate for continuous improvement of user experience and accessibility.

AWS Migration

Migrate to AWS Lambda, parse database, and integrate Twilio for comprehensive SMS feature functionality.

AI Development

Train AI using user messages, refine prompts, and integrate UI for seamless deployment and optimal performance.

Union 1
Stigma Image

At STIGMA, I played a vital role in developing the AI tool, leveraging users' messages of hope to train our AI. Through iterative refinement and prompt engineering, we optimized the tool to generate postable messages effectively. We then seamlessly integrated it with the UI, prioritizing usability. Leveraging Xano for back-end support and Draftbit for front-end development, we ensured a smooth deployment. This comprehensive approach resulted in a feature capable of delivering personalized support and fostering a sense of community among users.

Stigma Team
Project Timeline
SMS Deployment

Deploy SMS feature, collect user feedback, and iterate for continuous improvement of user experience and accessibility.

AWS Migration

Migrate to AWS Lambda, parse database, and integrate Twilio for comprehensive SMS feature functionality.

AI Development

Train AI using user messages, refine prompts, and integrate UI for seamless deployment and optimal performance.

Union 1
Stigma Image

Through my work at STIGMA on their mental health app, I seamlessly navigated between front-end and back-end development, helping the team meet deadlines and exceed expectations. My journey began with developing an AI tool (Al-i), funded by an Amazon accelerator, to provide users with nearly immediate feedback using ChatGPT and user data. As a team, we trained our AI, refined the prompt, implemented the necessary UI, and deployed the feature. Post-accelerator, I spearheaded the development of an SMS posting feature, enabling users to more easily "ask for help," thus advancing STIGMA's goal of crowdsourcing hope to reach more people.

For the SMS feature, I independently developed a robust solution by migrating to AWS Lambda services, coding in JavaScript for Node.js instead of using Xano's built-in tools. Using SQL queries, I meticulously parsed the database to link messages with user accounts, creating new member IDs when necessary. Twilio streamlined the text message flow, collecting crucial data from users. This meticulous approach ensured that every message, whether from new or existing users, was properly associated with their accounts, enhancing accessibility and allowing more individuals to seek and receive support seamlessly.

Crowdsourcing Hope | A Mental Health App

STIGMA

Lines

At STIGMA, I played a vital role in developing the AI tool, leveraging users' messages of hope to train our AI. Through iterative refinement and prompt engineering, we optimized the tool to generate postable messages effectively. We then seamlessly integrated it with the UI, prioritizing usability. Leveraging Xano for back-end support and Draftbit for front-end development, we ensured a smooth deployment. This comprehensive approach resulted in a feature capable of delivering personalized support and fostering a sense of community among users.

Stigma Team