Companies that use SuperAGI

Source: Analysis of tech stacks from 60 companies that use SuperAGI

I noticed that SuperAGI users are predominantly B2B companies with sophisticated marketing operations and a strong focus on measuring and optimizing their entire funnel. The presence of LiveIntent and Apollo.io's visitor tracking tools tells me these companies are serious about identifying and engaging prospects at scale, while tools like Factors.ai suggest they're tracking multi-touch attribution across their customer journey.

The pairing of LiveIntent with Factors.ai is particularly revealing. These companies aren't just running email campaigns, they're using programmatic advertising to reach prospects across multiple channels and then measuring how those touchpoints contribute to conversions. Adding Apollo.io's visitor tracker into this mix shows they want to identify anonymous website visitors and pull them into nurture sequences. Meanwhile, Weights and Biases appearing in the stack suggests many of these companies are building or training AI models themselves, which makes perfect sense given SuperAGI's focus on autonomous agents. They're not just using AI tools, they're developing AI products.

The full stack reveals these are marketing-led B2B companies in growth stage, likely Series A through C. They've moved past basic marketing automation and are investing in sophisticated attribution and visitor identification technology. The presence of SonarQube Cloud indicates they have engineering teams focused on code quality, while Ahrefs shows they're thinking strategically about content and SEO as acquisition channels. These companies are data-driven and willing to invest in multiple tools to understand what's working.

Source: Analysis of Linkedin bios of 60 companies that use SuperAGI

I noticed that SuperAGI visitor identification attracts companies operating in highly technical, innovation-driven spaces. These aren't traditional service businesses. They're building AI platforms, developing blockchain infrastructure, creating VR training systems, automating marketing workflows, and solving complex security challenges. Many are software companies, but they're specifically focused on emerging tech: generative AI, automation, cybersecurity, and digital transformation. Even the non-tech companies like chemical manufacturers and food distributors emphasize their digital capabilities and data-driven approaches.

The funding and size data tells an interesting story. About 40% have disclosed funding, mostly at seed or Series A stages, with funding amounts typically between $2M and $20M. Employee counts cluster heavily in the 11-50 and 51-200 ranges. Very few are under 10 people or over 500. This suggests companies in active growth mode, past the garage startup phase but not yet established enterprises. They have enough traction to invest in tools but still need every advantage to scale efficiently.