Inspiration: Academic writing can be stressful. Being unable to express yourself clearly makes stress worse. Procrastinating makes writing worse. We want to make writing more pleasant, more engaging, more fluid, less overwhelming, and less stressful.

What it does

SynthesizOr is a writing tool that can be customized to prompt, guide, and coach through the writing process with structured assistance for optimizing productivity, focus, and given academic sources as inspiration to draw from as evidence for the argument, synthesize ideas and concepts for better results. It is ultimately the user who has the knowledge and ability to form an opinion and make arguments. Our goal is to facilitate the stream of consciousness and achieve a flow state.

How we built it

We looked at the design and functionality of the writing process with an attempt towards automation. We chose to think about graphics for UI and keep the web service simple and user-friendly for usability. We used Adobe Dimension and Photoshop, React.js, HTML, and CSS.

Challenges we ran into

Since it was only the two of us, we didn’t have a lot of help building, so we chose to keep the project simple. Team building and knowing how we would do things we wanted. Curtiss is a beginner and is low-to-no tech, but showing signs of improvement. Very rough around the edges. Suhit is the tech expert on the team, so without much help from Curtiss, Suhit is responsible for most of everything. Curtiss helps with documentation, design, pitch and presentation, and project management. Knowing what we wanted and how we thought everything would work still presented a lot of challenges. Our Tech Stack was a little flawed, working through the web deployment from the domain DNS, and then the cloud service we wanted was a little tough because neither of us ever used any cloud service. We had to get assistance from a mentor, but the instructions had to be looked up and worked out step-by-step. With two teammates, we may have benefited from sharing ideas, but construction and improvements were a challenge. We decided to reach simple, logical milestones and leverage the mentors as the most valuable resource in suggesting edits and critiquing our process. Because of our stack, we had a hard time deploying the website, which in turn, delayed us from a video demo to add to our pitch. We were confident that once we got the website up we could add the demo to the video and switch the video of just the presentation to a video of the presentation with the demo. We wanted to get the UI into the pitch but it was being developed so the best we could do was submit an example mockup in the pitch until the demo was ready.

Accomplishments that we're proud of

We focused on minimalism, and that gave us an advantage. We are most proud of being a two-person team and making something that we would use ourselves. We learned a lot!

What we learned

We learned the importance of teamwork and communication. We also learned new valuable skills and tools. Curtiss learned how to use Notion, Prezi, and how difficult programming and development can be, even with seemingly simple functionality. Suhit learned how to work with the MERN stack, this being his first application on it, he also learned how to work with Quill.js, which is a tool for creating a text editor.

What's next for Synthesizor

We would like to have built an API for language processing, AI/ML, to help assist with detecting user need for prompting and feedback during later stages of the writing process and comparisons and synthesis. With the number of publications and materials that could be accessed, especially with APIs that link publications and sources, citations and bibliographies could be linked to our service. A long stretch goal would be to have AI/ML for source materials, which could help point out accuracy/inaccuracy in reading comprehension and analysis. Having more users, we could also have teachers, instructors, and professors involved in the review process, or peer to peer as a give-one-review-one reciprocal exchange based on the level of difficulty or topic.

Google Cloud and/or AWS Alpha testing Debugging AI Debugging Beta testing Machine Learning Debugging Gamma testing

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