Engineering teams often struggle to identify and address inefficiencies within their development workflows, leading to suboptimal productivity and delayed project delivery. This lack of visibility into the development lifecycle makes it difficult to pinpoint bottlenecks and implement targeted improvements.

Weave offers a data analytics platform that provides engineering teams with deep visibility into their development processes. By ingesting and analyzing data from code repositories, version control systems, and collaboration tools, Weave surfaces actionable insights into team performance and workflow bottlenecks. The platform's proprietary algorithms model the entire development lifecycle, from code commit to deployment, identifying areas for optimization. This enables engineering leaders to make data-driven decisions to enhance team efficiency, improve code quality, and accelerate delivery cycles, allowing engineers to concentrate on core development tasks.

Integration with Git repositories (e.g., GitHub, GitLab, Bitbucket) and project management tools (e.g., Jira) for comprehensive data ingestion.

Automated analysis of pull requests, including review time, merge frequency, and comment sentiment.

Workflow modeling to visualize and quantify cycle time, lead time, and throughput across development stages.

Performance metrics for individual engineers and teams, focusing on contribution patterns and collaboration dynamics.

SOC 2 Type I certified for enterprise-grade data security and compliance.

Data encryption in transit (TLS 1.2+) and at rest (AES 256-bit) to ensure data confidentiality.

Cloud-hosted infrastructure on Google Cloud for scalability and reliability.

The primary users are engineering managers, VPs of Engineering, and CTOs at software development companies of all sizes, from startups to enterprises, seeking to optimize their development operations and team productivity.

Weave operates on a tiered subscription model based on the number of active users and the depth of analytics provided.