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Turning AI Theory Into Enterprise Practice With RapidCanvas

Dec 11, 2024 - forbes.com
RapidCanvas, a Texas-based start-up founded by Rahul Pangam and Uttam Phalnikar, aims to address the skills shortage in AI by leveraging AI itself. The company has developed AI agents that help businesses identify and implement AI-driven solutions to enhance efficiency, productivity, and value. RapidCanvas recently announced a $16 million Series A funding round, bringing its total funding to over $23.5 million since its launch in December 2021. The company's hybrid approach combines AI agents with specialist advisers who provide domain expertise, allowing businesses to achieve AI integration with fewer human consultants. This method has led to rapid growth in customer numbers across various sectors, including manufacturing, retail, and financial services.

The new funding will support further technological development and recruitment, particularly of industry experts in key sectors. RapidCanvas plans to increase the workload handled by its AI agents to 90%. Investors, led by Peak XV and including Titanium Ventures, Accel, and Valley Capital Partners, are optimistic about the company's innovative approach. Harshjit Sethi of Peak XV Partners highlights the significant gap in data science expertise and praises RapidCanvas for its scalable and efficient solution that combines AI agents with subject matter experts to drive results.

Key takeaways:

  • RapidCanvas, founded by Rahul Pangam and Uttam Phalnikar, addresses AI deployment challenges by using AI agents to fill skills gaps in companies.
  • The company has raised a total of $23.5 million, including a recent $16 million Series A funding round led by Peak XV, with participation from Titanium Ventures and existing investors.
  • RapidCanvas employs a hybrid approach, combining AI agents with specialist advisers to solve business problems, aiming to replace the need for numerous expert consultants.
  • The company plans to use the new funds to enhance its technology and recruit industry experts, with a goal to increase the workload handled by AI agents to 90%.
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