RapidCanvas Secures $29M Series B to Automate Enterprise Data Science with AI Agents

The rush to integrate artificial intelligence into enterprise operations has exposed a critical bottleneck: a severe shortage of data scientists capable of building and maintaining custom models. To bridge this gap, Austin-based RapidCanvas has raised nearly $29 million in a Series B round led by Vertex Ventures and Hitachi Ventures. The funding signals a shift in enterprise AI from conversational chatbots to specialized agents capable of executing complex, multi-step technical workflows.

While general-purpose coding assistants like Devin or GitHub Copilot focus on software engineering, RapidCanvas targets the specific intricacies of data science. The platform combines autonomous AI agents with a no-code interface, allowing business teams to automate data preparation, model training, and deployment. Instead of requiring a team of engineers to manually clean datasets and tune algorithms, the system's agents handle the underlying infrastructure, effectively acting as an automated data science department.

This approach represents a significant evolution from the previous generation of AutoML tools, which still required substantial technical oversight. By enabling non-technical users to deploy custom AI applications, RapidCanvas is positioned to democratize machine learning across enterprise departments. As companies increasingly demand measurable ROI from their AI investments, platforms that can demonstrably reduce the time and cost of model deployment are capturing significant venture capital attention.