Normalized output measurement
Normalizes engineering work into a single unit so teams can compare output against expert benchmarks rather than raw line counts.
Weave
ReclamarWeave is an engineering intelligence platform that measures engineering output, AI-assisted work, and code review impact for software teams.
Overview
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.
Features
AI contribution analysis
Shows AI vs. human contributions and breaks output down by AI tool, type, and team.
Unified engineering signal graph
Connects signals from code, reviews, AI agents, project management, and communication into one graph of engineering work.
Engineering performance reporting
Quantifies AI impact on engineering velocity, code quality, and review throughput, with adoption rates by team, tool, and workflow.
Operational reporting and review intelligence
Includes code review intelligence and operational reports as part of the platform.
Enterprise security and deployment controls
Offers enterprise deployment options with SSO, SCIM provisioning, access controls, audit logs, and on-premise deployment.
Use Cases
Measure AI-assisted engineering work
Track how much engineering output comes from AI tools versus human contributors across PRs, reviews, and deploys.
Monitor engineering productivity
Compare team output against normalized benchmarks to understand whether engineering throughput is changing over time.
Evaluate AI impact on delivery quality
Review whether AI is improving code quality and review throughput, instead of looking only at output volume.
Create executive engineering reports
Give leadership and engineering management a shared reporting layer for operational updates and investment decisions.
Support enterprise security requirements
Deploy in regulated or security-sensitive environments that need on-premise options, role-based access, and compliance controls.
Pros and Cons
Pros
- Measures engineering output in a normalized unit rather than relying on raw line counts.
- Distinguishes AI-assisted and human contributions across PRs, reviews, and deploys.
- Combines multiple engineering signals into one graph for reporting and analysis.
- Offers a clear pricing structure with a free Starter tier, per-engineer Pro pricing, and custom Enterprise terms.
- Supports enterprise deployment needs with on-premise options, SSO, SCIM, and audit logging.
Cons
- The source gives limited detail on supported integrations and data-source setup beyond a broad connected-workspace model.
- Feature depth is only partially described, so some workflow specifics are unclear from the available pages.
- Pricing details are summarized at the plan level, but the source does not provide full usage limits or all plan differences.
FAQ
What does Weave measure?
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.
What pricing plans does Weave offer?
The pricing page shows Starter, Pro, and Enterprise options. Starter is listed at $0, Pro at $50 per engineer, and Enterprise is custom.
Can Weave be deployed inside our environment?
The enterprise page says Weave can be deployed on-premise within your own infrastructure, with an air-gapped deployment available.
What does the Enterprise plan include?
The source highlights GitHub Enterprise support, SSO, SCIM provisioning, user permissions, and security/compliance features for Enterprise customers.
Quick Facts
- Category
- Engineering intelligence
- Platform
- Web-based SaaS
- Primary users
- Engineering teams, including startups, scale-ups, and enterprises
- Pricing
- Starter $0, Pro $50 per engineer, Enterprise custom
- Deployment
- Cloud and on-premise options
- Domain
- workweave.ai
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