Highlights:
- RapidCanvas’ platform automates repetitive data science tasks with AI agents.
- RapidCanvas facilitates feature engineering, the process of structuring data to make it more interpretable for AI models.
Recently, data science startup RapidCanvas Inc. has secured USD 16 million in funding, with Peak XV leading the round.
Titanium Ventures, Accel, and Valley Capital Partners also participated in the investment, raising the company’s total funding since its inception to over USD 23.5 million. RapidCanvas, founded in 2021 by CEO Rahul Pangam and CTO Uttam Phalnikar, was previously behind Simility Inc., a fraud detection startup acquired by PayPal Holdings Inc. in 2018.
RapidCanvas’ eponymous software platform aims to automate repetitive data science tasks through the use of AI agents—large language models tailored to specific use cases. The company asserts that its agents can automate up to 75% of tasks in data science projects.
The initial phase of an analytics initiative centers on gathering the data users want to process. RapidCanvas offers over 500 integrations for retrieving records from cloud storage services, databases, and other data sources. If a connector is unavailable for a particular system, customers can create a new one using the prebuilt AI.
RapidCanvas features a drag-and-drop interface that enables users to prepare data for analysis without coding. The platform can standardize records from various sources into a unified file format, eliminate duplicates, and filter out errors. Users can also make additional modifications, such as replacing a list of product prices with an average price to simplify processing.
RapidCanvas also supports feature engineering, the process of structuring data in a way that makes it more comprehensible for AI models.
Once the preparatory work is complete, customers can generate multiple versions of the finalized dataset. One version might be used for training AI models, while another could serve as a benchmark for evaluating the models’ accuracy. A built-in chatbot streamlines the process by automating the coding typically required for these tasks.
In addition to AI models, RapidCanvas can generate data visualizations. It’s what-if analysis tool enables users to explore graphs for new patterns within the visualized data.
The platform’s core features are enhanced by administrative tools that simplify software deployment management. Access controls define feature availability based on employee roles, while an autoscaling capability optimizes infrastructure usage according to workload demands.
RapidCanvas asserts that its platform is suitable for a wide range of analytics projects. For instance, inventory planners can forecast demand for new products, while marketing teams can detect when customers might be at risk of churning. The platform also caters to industry-specific needs, such as identifying potential issues in factory equipment before they disrupt manufacturing processes.