How We Built Real-Time Chart Visualization in Our Chat SDK
At Coherence, we're on a mission to make AI conversations not just intelligent, but visually rich. When we set out to build our chat SDK, we quickly realized that text-only responses were leaving value on the table. Modern AI agents analyze data, generate insights, and identify patterns - but forcing them to describe charts and graphs in words is like asking someone to explain a sunset over the phone.
The challenge? How do you seamlessly integrate interactive data visualizations into a streaming chat interface without compromising performance, breaking the conversation flow, or requiring developers to write complex visualization code?
Early in development, we faced a fundamental architectural choice that would define our entire approach. Should charts be generated server-side in a sandboxed environment, or should we push the rendering responsibility to the client?
We initially explored server-side chart generation using containerized rendering environments. The appeal was obvious: complete control over the rendering pipeline, consistent output across all clients, and the ability to leverage powerful server resources for complex visualizations. We prototyped solutions using headless browsers in Docker containers, generating static images and SVGs that could be embedded directly into chat responses.
