Largest Engineering Teams

Top 10 startups with the most GitHub contributors. Data from GitDealFlow signals - updated weekly from public GitHub activity across 400+ tracked startups.

About This List

This ranking tracks the 10 startups with the largest visible engineering organizations on GitHub. Contributor count reflects total distinct developers active across each startup's public repositories — including both core employees and open-source community contributors. All 10 teams on this list have 100+ contributors, demonstrating exceptional engineering scale.

The list spans 6 sectors, led by Data Infrastructure (6 of the top 10). PostHog, airbytehq, AdguardTeam, bevyengine, medusajs, dbt-labs, sonic-pi-net, redpanda-data, cilium, and langfuse each show maximum contributor counts of 100. PostHog leads in velocity with 1,621 commits in 14 days, followed by airbytehq at 1,031. These teams represent the engineering powerhouses of the startup ecosystem, with the deepest talent pools and highest output. All 10 are at Growth stage, reflecting mature, well-funded organizations.

Top 10 Largest Engineering Teams

# Startup Description Sector Stage Contributors 14d Velocity Profile
1 PostHog The single platform to analyze, test, observe, and deploy new features Data Infrastructure, HR Tech Growth 100 1621 View →
2 airbytehq Open source data replication platform and context layer for AI agents. Data Infrastructure Growth 100 1031 View →
3 AdguardTeam AdguardTeam Legal Tech Growth 100 643 View →
4 bevyengine A modular game engine built in Rust, with a focus on developer productivity and performance Gaming Growth 100 147 View →
5 medusajs Building blocks for digital commerce E-commerce Infrastructure Growth 100 105 View →
6 dbt-labs dbt helps data teams work like software engineers—to ship trusted data, faster. Data Infrastructure Growth 100 99 View →
7 sonic-pi-net Sonic Pi Network EdTech Growth 100 94 View →
8 redpanda-data The streaming data platform for developers Data Infrastructure Growth 100 91 View →
9 cilium eBPF-based Networking, Security, and Observability Data Infrastructure Growth 100 82 View →
10 langfuse Open source AI engineering platform. Debug, analyze and iterate together. Data Infrastructure Growth 100 78 View →

How to Use This Data

The largest engineering teams list identifies startups with the deepest engineering talent pools — organizations that have achieved 100+ visible GitHub contributors. These teams represent the engineering powerhouses of the startup ecosystem, combining scale with velocity. For VCs, a large engineering team signals significant product investment and the ability to execute at speed across multiple workstreams simultaneously.

Data Infrastructure dominates with 6 of the top 10 teams — PostHog (1,621 commits/14d), airbytehq (1,031), dbt-labs (99), redpanda-data (91), cilium (82), and langfuse (78). These companies are building the foundational tools that power the modern AI and data stack. The remaining 4 teams span Gaming (bevyengine), E-commerce Infrastructure (medusajs), EdTech (sonic-pi-net), and Legal Tech (AdguardTeam) — showing that large engineering teams exist across diverse sectors. All 10 teams are at Growth stage, reflecting mature commercial traction.

Methodology: Contributor count reflects distinct developers active across each startup's public GitHub repositories in the trailing period. This includes both salaried engineers and open-source community contributors. Data is updated weekly from public GitHub activity. For detailed methodology, visit signals.gitdealflow.com/methodology.

Sector Distribution

Data Infrastructure6
Legal Tech1
Gaming1
E-commerce Infrastructure1
EdTech1
HR Tech1

Velocity Trends

Avg 14d Velocity397 commits
Highest Velocity1,621 commits (PostHog)
Top StageGrowth (10 of 10)
Min Contributors100 (all teams)

Why Track Engineering Team Size

Engineering team size is a fundamental indicator of startup maturity and investment stage. The largest teams tracked by GitDealFlow demonstrate that engineering headcount correlates strongly with commit velocity, product complexity, and market reach. Tracking these teams helps investors identify which startups are investing most heavily in their technical organizations. Use our Velocity Checker to see how any startup's engineering velocity compares to these top teams by headcount.

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