Sacred Graph partnered with Cloudchart to overhaul and optimize their core application performance. We participated as a direct extension of their team to resolve bottlenecks in data retrieval and refine the interaction between their graph database and the user interface, resulting in a significantly faster and more responsive experience.

As Cloudchart’s data grew, their existing Neo4j queries began to struggle with latency, slowing down the entire application. The team needed more than just a quick fix; they required a deep architectural review to address inefficient API calls and frontend lag that were impacting the overall user experience and threatening future scalability.

Our primary goal was to modernize the database layer to handle larger datasets without compromising speed. We aimed to optimize complex graph traversals, streamline the API functionality to reduce overhead, and implement targeted frontend improvements to ensure the application felt fluid for the end user.

We performed a deep-dive audit of the existing Neo4j graph structure, rewriting inefficient queries to minimize execution time. To support these changes, we refined the API layer to ensure data was moving efficiently between the database and the frontend. Beyond the immediate code changes, we implemented targeted UI performance tweaks. This guidance focused on how Cloudchart could adapt their graph database to remain scalable as their business needs and data complexity continue to evolve.

The collaboration resulted in a noticeably more efficient and user-friendly application, with query response times significantly reduced. By addressing both the immediate performance hurdles and the long-term architectural strategy, we’ve empowered Cloudchart to scale their platform with confidence.