Companies that use Cline

Source: Analysis of Linkedin bios of 112 companies that use Cline

I noticed that Cline's users cluster into three distinct groups: open-source infrastructure builders (blockchain protocols, developer tools, CMS platforms), software consultancies and agencies serving enterprise clients, and government or civic organizations modernizing their technology. These aren't typical SaaS companies. They're building complex technical systems, managing intricate integrations, or maintaining large-scale infrastructure where code quality and developer velocity matter enormously.

The maturity spectrum is surprisingly wide. I found seed-stage startups with under 10 employees (Nozomio, Usable, Fig) sitting alongside established enterprises with thousands of staff (Skatteetaten with 4,000+ employees, Palantir). However, the sweet spot appears to be teams of 11-50 employees who have found product-market fit but are still scaling. The funding data is telling: when companies do raise capital, it's often substantial Series A rounds ($25M+), but many profitable consultancies and agencies operate without external funding entirely.

Source: Analysis of tech stacks from 112 companies that use Cline

I noticed that companies using Cline are heavily invested in AI-assisted development tools, with an almost total overlap in their adoption of other code generation platforms. This isn't your typical enterprise software buyer. These are technology-forward development teams that are experimenting aggressively with multiple AI coding solutions simultaneously. They're likely startups or innovation-focused engineering teams trying to maximize developer productivity through cutting-edge tooling.

The pairing patterns are fascinating. First, seeing Cursor and Github Copilot appear alongside Cline at nearly 2000x the normal rate tells me these teams aren't betting on a single AI coding assistant. They're running multiple tools in parallel, probably comparing effectiveness across different use cases. The strong presence of Github Actions suggests they're automating heavily and likely integrating AI code generation directly into their CI/CD pipelines. The Gemini CLI correlation, though smaller in absolute numbers, shows these companies are comfortable with command-line AI tools and probably have engineers who prefer terminal-based workflows.

The full stack reveals product-led organizations in early to mid growth stages. These companies are focused on shipping code faster rather than building sales infrastructure. The absence of traditional enterprise software and the concentration on developer tools suggests engineering teams have significant budget authority and decision-making power. They're optimizing for speed and developer experience, not compliance or procurement processes.