Mage Raises $6.3M to Simplify AI Integration for Developers

Mage Secures $6.3 Million Seed Funding to Democratize AI Integration

Mage, a company focused on developing artificial intelligence solutions for product developers, has successfully raised $6.3 million in seed funding. The investment round was spearheaded by Gradient Ventures.

Origins and the Need for Accessible AI Tools

The company was founded by Tommy Dang in late 2020, stemming from his experience creating internal low-code tools while at Airbnb. Dang observed a significant gap in the market during his collaborations with product developers.

While developers expressed a strong desire to incorporate AI into their applications, a lack of appropriate tools hindered their progress. They frequently found themselves reliant on the expertise of data scientists, creating a bottleneck. As Dang explained to TechCrunch, many developers possessed machine learning tools and systems, but lacked the necessary knowledge to effectively utilize them.

“We identified a need to create tools specifically for technical professionals without extensive machine learning backgrounds,” Dang stated. “Our aim is to become the ‘Stripe for AI,’ simplifying the process of integrating AI capabilities into applications.”

A Growing Market and Mage’s Approach

The market for AI tools is projected to reach $126 billion by 2025. However, a substantial portion of these tools remain geared towards individuals with specialized AI expertise. Mage distinguishes itself through its low-code, cloud-based platform and intuitive user interface, reminiscent of Figma.

Users can seamlessly integrate data through file uploads, data streaming, or connections to existing data warehouses. The platform then facilitates model building and selection of various use cases, including customer churn prediction, user ranking, and personalized matching.

Following model creation, users have the ability to review, refine, and ultimately deploy their models. Deployment options include downloading the model as a file, reconnecting it to the data warehouse, or integrating it into an API or application.

Investors and Industry Validation

In addition to Gradient Ventures, the funding round included participation from Neo, Designer Fund, and a cohort of angel investors. Notable investors include John Riccitiello, CEO of Unity; Scott Belsky, founder of Behance; Lenny Rachitsky, author of Lenny’s Newsletter; and James Beshara.

Darian Shirazi, General Partner at Gradient Ventures, shared that he discovered Mage while actively seeking investments in the machine learning infrastructure sector that didn’t necessitate extensive data engineering skills. He noted that recent funding trends favored complex infrastructure solutions geared towards data scientists and machine learning engineers.

Addressing a Market Demand

Shirazi recognized a growing demand for technologies empowering non-data scientists to harness the power of AI and machine learning. He found that Mage directly addressed this need. Having previously connected with Dang at UC Berkeley and later at Airbnb, Shirazi believes that Mage’s success in providing accessible AI tools could fundamentally alter business operations.

“There’s a considerable demand from both companies and individuals to utilize technologies currently limited to specialists like data scientists, ML engineers, and AI researchers,” Shirazi explained. “The potential applications of AI/ML are limitless, and simple tools are crucial for enabling broader adoption without requiring advanced technical expertise.”

Mage’s Unique Capabilities and Future Plans

Shirazi highlighted Mage’s “superpower” as the convergence of robust data quality tools and the interoperability of machine learning models and features. He anticipates the company will eventually establish a marketplace offering diverse models and tools for data manipulation and combination, catering to various departments like marketing, sales, product, and finance.

Currently in beta, Mage is collaborating with small businesses. The company plans to launch its self-service feature in early 2022. The new capital will be allocated towards expanding the product design and engineering teams, as well as developing additional AI tools and pursuing international expansion.

While immediate revenue generation isn’t the primary focus, Dang confirmed that Mage has already secured a base of paying customers who are actively providing valuable feedback on the platform’s features.

“Our immediate priority is a general availability launch, allowing users to onboard themselves,” Dang stated. “The need for machine learning is universal, and we are committed to making these tools accessible. We have a thriving community of developers eager to enhance their skills and expand their toolsets.”