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Neurofrog

Neurofrog developed a mobile app designed for pregnant women and new mothers, providing expert guidance on exercises, diets, and symptom management. The app also features distinct versions for different countries, such as New Zealand and Vietnam.

The Problem:

Neurofrog encountered significant challenges in mobile app development, including malfunctioning features, content generation issues, crawler errors, inaccurate data, authentication and login problems, security concerns, and UI design flaws.

The Solution:

See how Prixite fixed app issues, opptimized performance, and developed an Ai chatbot for Neurofrog. The case study details the technologies used, the methodology and the fial results that led to a satisfied client and a successful project.

Tech stack

The sheer scale and complexity of the project demanded a diverse tech stack. In order to achieve the best results, we divided the project into sub-domains. We ended up using express.js, MondoDB, Python, PGvector, PostgreSQL, Scrapy, Django, and Node.js along with openAI models and fast API.

Outcome

Streamlined user onboarding resulted in a drastically higher app success rate. Improved chatbot accuracy (thanks to our engineers putting in clever conditions on the chatbot) eliminated fabricated answers, leaving users more satisfied. This increased user engagement on the app. Check out the details in the complete case study document.

Download the full case study to learn more about how Prixite helped Neurofrog achieve these results.