Normalized output measurement
Normalizes engineering work into a single unit so teams can compare output against expert benchmarks rather than raw line counts.
Weave is an engineering intelligence platform that measures engineering output, AI-assisted work, and code review impact for software teams. Plans include Starter, Pro, and Enterprise, with on-premise deployment for larger organizations.
Weave is an engineering intelligence platform that uses LLMs and domain-specific machine learning to analyze how engineering work gets done. It is designed to help teams measure output, separate AI-assisted work from human contributions, and understand whether AI is improving delivery, code quality, and code review throughput.
The product positions itself around a normalized unit of engineering work, calibrated to expert benchmarks instead of line counts. Across the site, Weave presents itself as a single workspace for engineering measurement, research, operational reporting, and code review intelligence, with enterprise deployment options for larger organizations.
Normalizes engineering work into a single unit so teams can compare output against expert benchmarks rather than raw line counts.
Shows AI vs. human contributions and breaks output down by AI tool, type, and team.
Connects signals from code, reviews, AI agents, project management, and communication into one graph of engineering work.
Quantifies AI impact on engineering velocity, code quality, and review throughput, with adoption rates by team, tool, and workflow.
Includes code review intelligence and operational reports as part of the platform.
Offers enterprise deployment options with SSO, SCIM provisioning, access controls, audit logs, and on-premise deployment.
Track how much engineering output comes from AI tools versus human contributors across PRs, reviews, and deploys.
Compare team output against normalized benchmarks to understand whether engineering throughput is changing over time.
Review whether AI is improving code quality and review throughput, instead of looking only at output volume.
Give leadership and engineering management a shared reporting layer for operational updates and investment decisions.
Deploy in regulated or security-sensitive environments that need on-premise options, role-based access, and compliance controls.
Weave combines LLMs and domain-specific machine learning to understand engineering work and separate AI-assisted contributions from human work across PRs, reviews, and deploys.
The pricing page shows Starter, Pro, and Enterprise options. Starter is listed at $0, Pro at $50 per engineer, and Enterprise is custom.
The enterprise page says Weave can be deployed on-premise within your own infrastructure, with an air-gapped deployment available.
The source highlights GitHub Enterprise support, SSO, SCIM provisioning, user permissions, and security/compliance features for Enterprise customers.
Traffic data is for reference only.
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