Yumi
Founder & AI engineerMar 2026 - PresentAn AI assistant that turns conversation into actions in everyday apps. Ask it to remind you to buy milk, and it creates a task in Mugi. Ask about a new word, and it can make a study card in Memori. I built the assistant, app connections and supporting services.
Connect chat to real reminders, habits and study materials.
- Built tools to manage reminders, record habit check-ins, organise vocabulary and generate study cards. Changes appear in Mugi and Memori.
- Enforced the signed-in user’s identity on the server so the AI cannot select another account. Added Firebase sign-in, app permissions and configurable approval before tools run.
Bring chat, voice and app actions to mobile and web.
- Built a Flutter client for iOS, Android and web with replies appearing as they are generated, voice, action approvals, searchable history and ten interface languages.
- Preserved message drafts across navigation and window resizing. Tested streamed replies, sign-in and input method editors (IMEs); deployed the web client and a simulated demo.
Let developers give an AI assistant access to their app’s functions.
- Published yumi-agent on PyPI, with a setup command and developer libraries. Apps connect their functions over WebSocket, using Python, TypeScript, Dart or Swift.
- Supported Claude, Gemini, OpenAI and Ollama so the assistant can select and call connected app functions while streaming its response.
- Added SQLite/LanceDB memory, versioned prompts and automated tests using simulated AI responses. Automated package releases with GitHub Actions and OIDC.
Multi-user
platform
Closed source
Keep user data separate and give administrators control over costs and access.
- Extended the core through plugins. Separated customer data in PostgreSQL; added OAuth sign-in, hashed credentials and limits on login attempts.
- Built a React admin console with usage and cost limits, plus execution records to investigate which tools the assistant used.
- Enforced access levels in SQL. Administrative access to message content requires a saved audit record before viewing.
Deployment &
reliability
Docker · Terraform
Deploy the service and verify that saved data can be recovered.
- Deployed with Docker Compose, Caddy/TLS and health checks. Provisioned GCP with Terraform and GitHub OIDC; later moved the API to a self-hosted Mac mini.
- Implemented backups and release rollback. Validated recovery by restoring a backup in a separate environment and comparing database tables.