Turn Git Data into Actionable Insights

Track dead-end commits, review delays, and bug surges. minware transforms Git data into insights so you can improve performance.

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The output-first approach to AI Impact is broken.

Code output is up

Merged pull requests on GitHub have more than quadrupled since 2023, reaching 130M per month in August 2026.

Source: GitHub

Value is flat

Only 6% of companies are “high AI performers” that report “significant” AI impact and ≥5% impact on earnings, unchanged from 2025 to 2026.

Source: McKinsey

A strategy that works: stop slop to accelerate value.

minware’s Lean AI Framework™ unlocks value by eliminating everything that gets in the way: rework, bugs, reviewing low-quality code, context switching, babysitting agents, and more.

Measure best practices that drive AI impact.

Other platforms measure outcomes, but don’t tell you how to get better.

minware offers actionable metrics that help teams improve AI impact.

Team Workflow Efficiency

Ticket Work-in-Progress (WIP)

Planning and Prompting

Ticket Size

Pull Request (PR) Complexity

Pre-Merge Churn Rate

Post-Merge Churn Rate

Session Automation

Human Commit Rate

Agent Session Length

Human Intervention Rate

Cloud Agent Use/Success Rate

Tool Use/Runtime

Culture

AI Rules of Engagement

Read about best practices in the Lean AI Framework

Customize metrics for the way each team creates value.

minware’s patented hypercube data model and minQL language interlink and surface every SDLC artifact.

We help you customize editable metric formulas for each team’s value creation workflow – aligning statuses, labels, custom fields, and team conventions.

Any Metric ✕ Any Dimension ＝ Accurate Value-Aligned Insights

Start from comprehensive pre-built reports and industry benchmarks.

minware integrates with every major development tool.

minware also supports custom CSV/JSON and OpenTelemetry data for spreadsheets and internal tools.

See the full list of integrations

Save your tokens and leave the rest to us.

Get trustworthy insights faster with our data infrastructure.

Agents are great at a lot of things – enterprise-grade data quality, performance, and security are not among them.

Automated Caching & Orchestration

The minQL engine dynamically materializes tables and orchestrates updates so your results are always fresh and fast for millions of rows.

Standard Data Modeling & Benchmarks

minware provides pre-built models for common use cases like time allocation, cost attribution, DORA workflow efficiency, Agile and more.

Vendor Data Linking & Normalization

minware normalizes and links AI usage, pull requests, tickets, and more with advanced heuristics for unstructured relationships.

Error Handling & Recovery

minware handles errors caused by vendor API issues, schema updates, data anomalies, and more so your data is available 24/7.

Identity Resolution

minware reconciles names, emails, and user IDs across all vendors and matches them to multi-level team structure from any source.

Role-Based Access Control

Easily control team and individual data access permissions for minware users based on their role and team membership.

On-Premise Ingest Agent

For added security, the on-premise ingest agent runs locally and uploads data to minware. You maintain full control over keys and data.

AICPA SOC 2 Type 2 Certified

minware is SOC 2 Type 2 compliant. Learn more and access the full SOC 2 report from our security documentation.

Frequently Asked Questions

What does minware offer that GitHub, GitLab, Bitbucket, or Azure DevOps dashboards do not?

Platform-native dashboards only show activity within that tool. minware combines Git, ticketing, and CI/CD data to provide a unified view of engineering work across systems. This includes GitHub developer metrics, Bitbucket pull request metrics, and GitLab analytics dashboards with context like ticket flow, unplanned work, and code review depth. The result is full visibility that connects code to actual business value.

Can minware help us track Git metrics across multiple teams and repositories?

Yes. minware can consolidate Git metrics across repositories, and teams into a single reporting layer. It calculates GitHub PR metrics, review latency, and throughput with breakdowns by team, service, or sprint. This avoids the manual effort of aggregating Git project statistics or maintaining Git report generators.

How does minware improve PR analytics and pull request statistics?

minware captures data on PR lifecycle stages, including time to review, review depth, rework rate, and merge success. These PR analytics go beyond what platform-native dashboards offer by linking pull requests to associated tickets and deployments. The result is actionable metrics for improving review processes and reducing delivery risk.

How does minware help with engineering performance visibility in Git-based workflows?

minware provides engineering performance metrics based on Git activity, review behavior, and deployment data. It reveals delivery bottlenecks, inefficient review loops, and time spent on rework. This allows teams to improve throughput and maintain quality in fast-moving environments.

Can minware analyze organizational Git metrics for compliance and governance?

Yes. minware supports metrics at scale, including PR activity by team, time-to-merge tracking, and review compliance across repositories. This is especially useful for teams enforcing secure development lifecycles or looking to standardize reporting tools across large organizations.

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