Scaling Fitia: Engineering Nutrition with AI and JetBrains
How Fitia’s lean engineering team achieves monthly feature releases using integrated development tools.
1Fitia's Rapid Growth Trajectory
Founded in 2019 in Peru by Piero Linares and Ulises Olave, Fitia has scaled to over 10 million users. The Y Combinator-backed startup provides personalized meal planning and calorie tracking. As they expand from Latin America into the US market, the team maintains a lean structure while managing massive user data.
2Managing Massive Data Fragmentation
Fitia processes over 30 million food logs monthly, alongside weight, sleep, and activity data. This information was previously scattered across PostgreSQL, BigQuery, Azure, and Redis. The resulting fragmentation made maintaining data integrity and executing simple queries a significant operational headache for the small engineering team during their rapid scaling phase.
3Centralization Through DataGrip
To solve database fragmentation, the team centralized all sources into DataGrip. This transition eliminated the need to switch between different providers. By leveraging built-in AI features within the tool, the team successfully reduced complex query execution times from several hours down to mere seconds, significantly improving their daily backend development workflow efficiency.
4Doubling Development Velocity
Adopting GoLand for their Go microservices allowed Fitia to double their development speed. The IDE’s code suggestions and optimization tools provided a cleaner, more reliable backend architecture. This efficiency gain directly supports their mobile team, ensuring that backend services remain stable while enabling faster deployment cycles for new application features.
5Achieving Monthly Feature Releases
Fitia currently maintains a consistent pace of shipping one major feature every month. This represents a three-fold increase in productivity compared to their previous development speed. By focusing on developer efficiency and tool integration, the lean team successfully competes with larger organizations without needing to expand their headcount significantly this year.
6Leveraging AI in Development
The team integrated JetBrains tools to keep pace with the rapid advancement of AI models. Beyond just using IDEs for coding, they utilize context-aware chat features that reference their own codebase. This native integration allows developers to ask questions directly within the environment, fundamentally changing how they approach complex problem-solving tasks.
7Strategic AI Implementation
Fitia’s strategy focuses on building proprietary features atop existing large model providers. They train these models using their own community data to ensure recommendations remain relevant to user goals. This approach allows them to offer advanced capabilities like photo-based food identification while maintaining a unique value proposition in the nutrition market.
8Operational Efficiency as Strategy
Fitia’s success highlights the importance of developer tooling in scaling lean startups. By joining the JetBrains Startup Program, they gained access to professional-grade IDEs that streamlined their entire deployment path. Their ability to maintain high-velocity releases demonstrates how optimized engineering workflows act as a primary driver for sustainable product growth.
Original article: The JetBrains Blog — Scaling Fitia: Engineering Nutrition with AI and JetBrains