Uplift - for Strava athletes

Sindhu15 — Wed, 18 Jun 2025 14:44:38 +0000

I’m a developer who’s into fitness and now slowly falling in love with running.

A few months ago, I joined a small running group guided by a coach. Initially, I couldn’t understand why people enjoyed running so much. I struggled, gasped for air, and mostly kept going because I needed a distraction.

When I hit my first non-stop 10k I couldn't stop comparing it with my very first run and appreciate how far I had come. That moment stuck with me.

The Why

A race was coming up for our group. I couldn’t participate due to an injury, but I knew many were giving it their all — their first 5K or 10K. I wanted to build something to celebrate their progress and efforts. And for myself, it was a chance to practice system design by building something end-to-end.

And so, Uplift was born — a quick weekend project built to celebrate each runner’s journey using their Strava data.

Project Goals

Appreciate the effort of runners in my group
Show them how far they've come using Strava stats
Generate a motivating, AI-powered message based on their data
Ship fast and keep it simple

Tech Stack

Backend: Node.js with Koa (my comfort zone)
Frontend: HTML, CSS, Vanilla JS (needed speed)
Integrations:
Strava API (OAuth + Activity fetch)
OpenAI (with fallback to Together AI)
QuickChart for journey graphs
Deployment: Render (simple and quick)
Logging: Google Sheets + Script

Feature Breakdown

Strava OAuth

Registered the app to get client_id and client_secret
Used OAuth flow to get access and refresh tokens
Set up a callback route /callback
Read user activities using /athlete/activities
Followed their guidelines on logo placements etc

Report Generation
Each report includes:

Total runs and distance
Longest run
Fastest run
Recent Run
First run (to see the contrast)
A chart showing their weekly run stats
A motivational AI insight

** AI Insight**
I crafted a detailed prompt asking the AI model to write a personalized, friendly uplifting message celebrating the user’s journey with the data provided to the LLM.

OpenAI GPT-3.5 Turbo as the default model
Together.ai Mistral-7B-Instruct as fallback
Plain text as fallback if both models fail (If we exceed the quota in both models)

Graphs
Used QuickChart to generate a visual summary of the user’s consistency
Simple, fast and suited for small-scale usage

Download the report as an image
Initially added a text asking the user to manually take a screenshot. After I was done with the design tweaks and data I wanted to show, I realised manual screenshot was not very efficient as the user had to scroll down and take 2 images if the report was slightly longer. So now had to support downloading as an image as that was more user friendly. Used html2Canvas to support this usecase.

Strava-hosted profile images didn’t render in the canvas export. I created a proxy route to handle image downloads properly.

Taking it a step further
I tested on my Strava account. With the race just a day away, I wanted to surprise the group. I enabled international transactions on my card and paid around $5 to enable better AI responses (hello, crazy mode 😄), and told the group something exciting was coming up.

Roadblock: Connected Athletes Limit

Everything was ready and I asked a friend to try it out, thats when I realized there was a limit on the number of users allowed to connect.

I panicked. I had already told my group there was a surprise waiting. I really wanted people to use it right after the race. I wrote an email to Strava with the screenshots of my app, my linkedIn profile etc. I activated my linkedIn premium and reached out to support people from Strava requesting if they could do anything to increase it.

Eventually, I calmed down, figured out the right process, and submitted the form. I was transparent and informed my group about it.

Polish & Improvements

With extra time while waiting for the increased limit, started fine tuning a few things.

Refined prompt

Logging
I wanted to understand the basic usage of my app. But I also wanted something very quick and didn't want to spend too much time on this. Google sheets with a script deployment was sufficient for this.
Used Google Sheets + Script deployment to log basic usage info: timestamp, model used, and origin. No user data was stored — just a hashed athlete ID. Privacy first!

Supported error states with friendly messages
Created *feedback form *(Google Form)
Added email contact for support
Replaced the “latest run” with more meaningful milestones

Caching
Added caching to handle Strava's 200-requests-per-15-min rate limit

Design Iterations:
I made n number of tweaks on:

Text placement
Font sizing
Chart layout

Logo:
Spent an unreasonable amount of time creating the logo and the name 😅

This is a privacy first app. No user data is stored.

End Result

Here goes my report :D

My takeaways:

OAuth
Got to explore Strava APIs
AI prompting and data feeding for AI insights
Starting with an idea, building and launching a product end-to-end
Feedback from real users
Always check rate limits and access caps
Ship fast, but communicate clearly when things go sideways
Tiny touches — profile pics, download buttons, fun copy — make a big difference
Excitement when users used my app

Try Uplift!

If you’re a runner on Strava, try it out and see your journey celebrated beautifully.
https://sindhus-stride.onrender.com

Pre-requisite: A Strava account with a few runs logged.

Uplift is simple. But it’s made with heart and all the tech I have mentioned in this blog :P A weekend well spent :)

Here's me: LinkedIn
Also published on medium - https://a-sindu15.medium.com/uplift-for-strava-athletes-1317ad5b9645

DEV Community: Sindhu15