Weave analyzes engineering work using LLMs and domain-specific models to measure AI vs. human contribution, development speed impact, and effects on code quality and code reviews.
Weave is an analytics and observability platform that helps engineering leaders understand the impact of AI on software development. It combines large language models with domain-specific machine learning to analyze code, commits, and reviews, quantifying how much work is done by AI versus humans. The primary purpose of Weave is to provide clear, data-backed insight into whether AI tools are actually improving delivery speed, code quality, and collaboration within engineering teams.
Weave automatically attributes code changes to AI or human authorship, enabling teams to measure AI-assisted productivity and adoption across repositories and teams. It tracks how AI-generated code performs over time, including its relationship to defects, rework, and review outcomes, so organizations can assess whether AI is improving or degrading code quality. The platform also analyzes code review patterns, surfacing how AI influences review load, review depth, and feedback quality. With these capabilities, Weave gives engineering leaders concrete metrics instead of relying on anecdotal feedback about AI tools.
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