Companies that use DeepSource

Source: Analysis of Linkedin bios of 125 companies that use DeepSource

I noticed that DeepSource users are overwhelmingly developer tool companies and infrastructure platforms. They build the picks and shovels of modern software: database systems (Redis, TiDB, TerminusDB), developer platforms (Fly.io, Okteto, Appsmith), API infrastructure (RudderStack, Twilio), and open-source tools (Novu, Requestly). A smaller segment includes fintech companies (Swissquote, Klever Brasil) and digital-first businesses in e-learning (Babbel) or marketplace platforms (Ordermentum, Tractor Zoom). These aren't companies selling to consumers directly. They sell to other developers and technical teams.

The funding stage distribution is telling. I counted roughly 15 seed-stage companies, 8 Series A or B companies, and a handful of mature players like Redis, Twilio, and Canonical. The majority sit in that 11-200 employee range, which suggests growth-stage startups past initial product-market fit but still scaling. Even the larger companies (Redis at 1,532 employees, Twilio at 6,609) maintain strong developer-first cultures rooted in their startup origins.

Source: Analysis of tech stacks from 125 companies that use DeepSource

I noticed that DeepSource users are developer-first companies with sophisticated engineering practices. The dominance of GitHub's entire security and automation suite tells me these are organizations that have made substantial investments in their development infrastructure. These aren't hobbyist projects or early-stage startups cobbling together free tools. They're companies that pay for premium developer tooling and treat code quality as a strategic priority.

The pairing of DeepSource with GitHub Advanced Security and Dependabot reveals a layered security approach. Companies aren't just checking a compliance box. They're running multiple overlapping systems to catch vulnerabilities at different stages, from dependency risks to code-level issues. Similarly, the strong correlation with Terraform suggests these teams are practicing infrastructure as code, which means they're applying the same rigor to their deployment infrastructure that they apply to their application code. The presence of AI coding tools like GitHub Copilot and Claude Code alongside DeepSource is particularly telling. These companies want AI to accelerate development, but they're also aware that AI-generated code needs extra scrutiny.

The full stack reveals product-led companies with mature engineering teams, likely Series A through Series C. They've moved past the "move fast and break things" phase into "move fast with guardrails." The GitHub Actions correlation suggests automated workflows are central to their operations. They're not waiting for manual code reviews. They're building continuous feedback loops. This level of automation indicates they're scaling their engineering teams and need systems to maintain quality without adding bottlenecks.