Sleuth, the software engineering intelligence startup focused on helping development teams measure and improve engineering efficiency, has raised $22 million in a Series A funding round to expand its platform, accelerate product innovation, and grow its global team. The financing marks a significant milestone for the company as organizations increasingly seek data-driven ways to understand software delivery performance across distributed engineering teams.

The Series A round was led by Felicis, with participation from Menlo Ventures and existing investor CRV. The new funding follows Sleuth’s earlier $3 million seed round, which was led by CRV and included angel investors from New Relic, Atlassian, LaunchDarkly, and Datadog. The latest investment brings the company’s total funding to approximately $25 million and provides additional resources to expand its engineering efficiency platform.

Founded in 2020 by former Atlassian executives Dylan Etkin, Don Brown, and Brian Knighten, Sleuth was created to address a longstanding challenge facing software organizations: accurately measuring engineering productivity without relying on misleading metrics such as lines of code written or tickets completed. Drawing on their experience building and scaling developer tools at Atlassian, the founders recognized the growing need for objective measurements that help engineering teams improve delivery performance while maintaining developer trust.

Sleuth’s platform automatically gathers data from software development tools and deployment pipelines to generate engineering performance metrics. Rather than requiring organizations to manually collect information across fragmented systems, the platform integrates with more than 40 development and DevOps tools, providing engineering leaders with a unified view of software delivery performance.

A central component of the platform is its support for DORA metrics, an industry-standard framework developed through the DevOps Research and Assessment program. These metrics measure deployment frequency, lead time for changes, change failure rate, and mean time to recovery, helping engineering organizations evaluate the speed and reliability of software delivery. Sleuth automates the collection and reporting of these measurements while providing additional insights into engineering workflows.

The company says one of its primary goals is to make engineering efficiency measurable without encouraging unhealthy productivity behaviors. Instead of focusing on individual developer output, Sleuth emphasizes team-level performance and workflow optimization, enabling organizations to identify bottlenecks, evaluate process improvements, and monitor the impact of engineering investments over time.

Chief Executive Officer Dylan Etkin has said the software industry has historically lacked trustworthy quantitative measures for engineering efficiency despite engineering organizations often representing the largest operational investment within technology companies. According to the company, recent advances in cloud-based development tools, standardized Git workflows, and broader adoption of DevOps practices have created the opportunity to deliver accurate, automated engineering intelligence at scale.

The newly raised capital is being used to expand Sleuth’s product capabilities, including broader support for software development workflows, deeper engineering analytics, and enhanced automation features. The company also plans to continue expanding its global engineering, product, and sales organizations as demand for engineering intelligence platforms continues to grow.

Sleuth’s platform extends beyond performance measurement by helping engineering teams automate workflow improvements. Through no-code automation capabilities, organizations can create processes that respond automatically to deployment events, incidents, and engineering milestones. These workflow automations are intended to reduce manual coordination while improving visibility across software delivery pipelines.

The company serves organizations ranging from startups to large enterprises seeking better visibility into software development performance. Customers have used the platform to monitor engineering initiatives, improve deployment reliability, reduce delivery bottlenecks, and provide executives with objective insights into engineering operations without relying on manual reporting.

Investor interest in the company reflects broader demand for developer productivity tools as software engineering organizations become increasingly distributed. The rapid adoption of remote and hybrid work has made it more difficult for engineering leaders to understand team performance through informal communication alone, increasing the importance of objective operational metrics and workflow visibility.

With support from Felicis, Menlo Ventures, and CRV, Sleuth is positioned to continue expanding its engineering intelligence platform while helping organizations improve software delivery through data-driven decision-making. As businesses place greater emphasis on engineering effectiveness and developer experience, the company aims to provide software teams with the visibility, automation, and actionable insights needed to continuously improve development performance without compromising collaboration or innovation.

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