Mage aims to be the “Stripe for AI”; raises $ 6.3 million for development tools to integrate AI into applications

mage, developing an artificial intelligence tool for product developers to build and integrate AI into applications, provided $ 6.3 million in seed funding led by Gradient Ventures.

Founder Tommy Dang launched the company in late 2020 after building low-code internal tools at Airbnb. Working with product developers, Dang found that while product developers wanted to use AI, they didn’t have the right tools to do so without relying on data scientists.

“We worked with hundreds of developers who had great machine learning tools and internal systems to run models, but there weren’t many who knew how to use the tools,” Dang told TechCrunch. . “They haven’t worked much with machine learning, so we decided to create tools for non-technical experts. We’re like Stripe for AI, which makes it easier for developers to integrate AI into apps.

The AI tools market is expected to reach $ 126 billion by 2025, but most of these continue to be geared towards those with AI experience. Mage’s technology is a low-code, cloud-based tool and user interface with a shared workspace similar to Figma. Users can add data by uploading a file, streaming data, or connecting to a data warehouse. From there, they can build models and choose from other use cases, such as unsubscribe prevention, ranking, and user matching. After creating the model, users can review the model, improve it, and then download it to a file, reconnect to the data warehouse, or deploy it to an API or application.

Mage product review

Mages dashboard. Image credits: mage

Neo, Designer Fund and a group of angel investors including Unity CEO John Riccitiello, Behance founder Scott Belsky, Lenny’s newsletter author Lenny Rachitsky and James Beshara, joined Gradient in the tour.

Darian Shirazi, general partner at Gradient Ventures, said via email that he found Mage while looking for an investment in the machine learning infrastructure space that did not require data engineering experience. . He saw that most of the recently funded companies were heavy infrastructure and facilitated big jobs for data scientists and machine learning engineers.

Shirazi has seen a market demand for technologies and systems that allow non-data scientists to take advantage of AI and machine learning. Shirazi found this in Mage. He had met Dang at UC Berkeley and then reconnected while Dang was at Airbnb. He believes that if “Mage succeeds in providing the simplest tools to take advantage of AI and machine learning, they will transform the way everyone does business.”

“There is a strong desire for businesses and individuals to take advantage of technologies and systems that are currently only available to domain experts such as data scientists, ML engineers and AI researchers,” he added. “The reality is that the number of applications for AI / ML is endless. There have to be simple tools for anyone to take advantage of machine learning, without requiring a deep understanding of math, computer science, or data science.

He considers Mage’s “superpower” to be “the link between data quality tools and the interoperability of ML models and functionalities”. Shirazi expects the company to eventually have a market for different models and tools for manipulating and combining data sets, such as for marketing, sales, products, and finance.

Mage is still in beta, but works with small businesses, and Dang said the company plans to launch its self-service feature in early 2022. Behind the scenes, the company is hiring for the design and engineering of products and intends to also use the new capital to build additional AI tools and expand internationally.

Dang said the company isn’t focused on revenue at the moment, but has built up a group of paying customers from the start. These early customers are helping Mage by trying out the features, he added.

“Our next steps are to launch general availability where you can get on board yourself,” Dang said. “The need for machine learning is a global need, and few others emphasize accessibility of tools. We have a community of developers who want to broaden their skills and develop their toolkits. “


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