Building an Insights page for your SaaS: from idea to production

In the journey of embedding an Insights page into a SaaS application, particularly for an AI startup with a chat application, developers face the challenge of providing real-time analytics to meet user demands for features like token usage tracking and model usage distribution. Initially, PostgreSQL may seem suitable but falls short due to complex ETL requirements and latency issues. Instead, using Tinybird, developers can efficiently create a web dashboard with interactive charts, leveraging log data and user information to cater to specific user needs. The process involves creating data sources, building API endpoints, and prototyping dashboards, with a focus on schema optimization and intermediate tables for scalability. As the project progresses, monitoring and optimization are crucial for maintaining performance and quality in production. With user expectations evolving towards real-time, embedded analytics, the foundation laid by this process not only enhances user engagement and retention but also positions the application to integrate advanced AI-driven exploration features, allowing users to interactively query data in natural language.