Making Data Visualization Accessible
We believe every developer, analyst, and storyteller should be able to create beautiful, meaningful charts without wrestling with complex libraries or design tools. ChartGen AI bridges natural language processing and data visualization, turning plain English into publication-ready charts.
Our Story
ChartGen AI started with a simple observation: creating a good chart takes too long. Between choosing the right library, formatting data, picking colors, and handling edge cases, what should be a 30-second task becomes a 30-minute ordeal.
We asked: what if you could just describe what you want? "Show me monthly revenue as a gradient bar chart" -- and get a production-ready SVG in milliseconds.
That question led us to build ChartGen AI: an API that understands natural language, infers the best chart type, applies intelligent styling, and renders beautiful visualizations at scale.
The Team
Sarah Chen
Former data scientist at Stripe. PhD in Computational Visualization.
Marcus Rivera
Ex-Google engineer. Built ML pipelines serving 1B+ requests/day.
Aisha Patel
NLP researcher. Published 20+ papers on language-to-visualization.
James Okonkwo
Led design systems at Figma. Passionate about accessible data viz.
Elena Volkov
Infrastructure architect. Previously scaled systems at Datadog.
David Kim
Open source advocate. Maintains several popular charting libraries.
Open Source
We are committed to giving back. These core tools are open source and community-maintained.
chartgen-core
Core rendering engine for SVG chart generation
chartgen-themes
Community-curated theme packs for data visualization
chartgen-cli
Command-line tool for batch chart generation
Join Our Mission
We are always looking for talented people who share our passion for data and design.
Get In Touch