Rise
The AI layer for a mobile life-coaching app: eleven endpoints, five coaching personalities, and streamed responses.
Rise is a mobile life-coaching app. Its AI layer exposes 11 FastAPI endpoints built around a five-personality tone system, so coaching responses feel distinct depending on the personality selected. Responses stream to the client over server-sent events as structured JSON, rather than arriving as a single blocking reply.
Primary technologies
- Python
- FastAPI
- Server-Sent Events
- Structured JSON outputs
01 / Context
What this project is
Rise is a mobile life-coaching app. Its AI layer exposes 11 FastAPI endpoints built around a five-personality tone system, so coaching responses feel distinct depending on the personality selected. Responses stream to the client over server-sent events as structured JSON, rather than arriving as a single blocking reply.
Engineering problem
Coaching needed to feel personal and immediate in a mobile client — five distinct personalities, delivered as a smooth stream rather than a delayed wall of text.
Approach
Designed 11 endpoints around a five-personality tone system, with server-sent-event streaming and structured JSON outputs the mobile app could render as it arrived.
02 / Stack
What it's built with
Technologies
- Python
- FastAPI
- Server-Sent Events
- Structured JSON outputs
03 / Outcome
What shipped
Delivered as a standalone AI service layer, ready for the mobile app's backend team to integrate.
Next step
Have something like this
you need built properly?
I work on the AI layer — retrieval, reasoning, and the plumbing underneath — and hand it over ready to integrate.