Case study

Transforming search with Machine Learning

Founded in Copenhagen in 2019, Podimo is a platform for podcast and audiobook lovers as well as audio content creators. Their app puts a world of podcasts and audiobooks at your fingertips. Their revenue-sharing model rewards creators for making content that people want to hear – whether they have an established following or a niche audience.

Client

Let's talk

Podimo

Founded in Copenhagen in 2019, Podimo is a platform for podcast and audiobook lovers as well as audio content creators. Their app puts a world of podcasts and audiobooks at your fingertips. Their revenue-sharing model rewards creators for making content that people want to hear – whether they have an established following or a niche audience.

Partnership

Ongoing since November 2022

1000+

Exclusive Shows

70.000+

Audiobooks

Industry

Country

Denmark

Project details

STX Next specialists were working together with Podimo onsite team to create an application that will allow users to listen and upload the podcasts and audiobooks. The app shares members’ subscription fees between the creators of the audio material so there would be a direct connection between a customer and a creator. Currently we are working on the bugfixing, feature updates and maintenance as the application is already live and working for the good of the customers.

STX Next team standing together behind large STX NEXT letters in the office

The challenge

Podimo's Elasticsearch system delivered search results that weren't always relevant. Despite possessing rich information about user preferences, they struggled to consistently prioritize the most popular shows in search responses.

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20+

years of software delivery

450+

specialists on board

1,000+

projects delivered

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The solution

STX Next first scrutinized and optimized Podimo's existing Elasticsearch settings, refining mappings and analyzers. We then implemented a Learning To Rank machine learning model to reposition search results, placing those with higher historical user preferences at the top. Additionally, semantic search capabilities using BERT were integrated, enabling users to search using natural language and get more pertinent results. We're now in the process of adding a conversational search feature, primarily leveraging OpenAI's ChatGPT, allowing users to interact with a chatbot for their queries.

STX Next delivered

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Tech stack

Vue.js
PyTorch
Sentence-Transformer
huggingface
Kibana
NumPy
LangChain
Google Cloud Platform
OpenAI
Seaborn
Matplotlib
XGBoost

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