| OP here with additional details requested by several of the commenters. Thanks so much to everyone for your responses on this thread, as well as those who reached out via email with suggestions and opportunities for collaboration. Description of the stack: - The frontend is a TypeScript Next.js app, with Prisma and RDS Postgres for persistence, and S3 for storing files uploaded by users. - On the backend I have a BullMQ worker for handling asynchronous tasks such as audio/video transcription, backed by Redis. - A Telegram bot that allows quickly adding resources from a phone and for having practice conversations with AI. - Everything is deployed via a Github Actions pipeline, with images hosted on ECR and other AWS resources deployed using Terraform. Preferably the solution would allow me to reuse at least parts of the existing CI/CD pipeline and Terraform for managing resources. Some of the suggestions by commenters such as running this on a machine in my home, while may be optimal from a cost minimization perspective, compromise a bit too much on quality-of-life for me—not simply from a developer perspective, but I also live somewhat of a nomadic lifestyle and prefer to have few physical possessions. I already tried applying for AWS Activate but was rejected due to not meeting their criteria. I do not have a company or non-profit entity formally set up for this project. It initially started as a research project purely for personal interest, to explore how LLMs can be used for memory augmentation (in general, not just for language learning). I’ve been a user of conventional SRS tools such as Anki for many years, and have been frustrated by certain UX limitations that hindered consistent long-term use. Initially, I built it as a tool for myself, with me as the sole target audience. Onboarding foreign monks in Thailand was a fortuitous occurrence that I had not initially anticipated. |