Swift Sage

Inspiration

An average PM spends 10-20 hours a week planning features, user stories and tickets. This is a huge pain point that could easily be solved by collating internal and external data sources and harnessing modern AI tools.

What it does

Harnessing the power of AI and leveraging 6 internal and external data sources, Sprint Sage will collate data and create sophisticated feature reports

Challenges we ran into

We ran into many problems collating our many data sources together and connecting this to the frontend.

Accomplishments that we're proud of

We successfully collated all of these data sources together and created functions in the backend connected to Langchain agents and OpenAI's GPT4 model to create intelligent predictions for PMs.

What we learned

We learned a lot about PMs and management in general through user interviews and deepend our knowledge of technical concepts such as embeddings, cosine similarity, and clustering.