NoBull SaaS

What does LinearB do?

Tool: LinearB

The Tech: Engineering Analytics

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Their Pitch

The AI productivity platform for engineering leaders.

Our Take

It's a dashboard that shows engineering managers where their code gets stuck and automates the boring parts of code reviews. Think Google Analytics for your development process, plus a robot that routes pull requests.

Deep Dive & Reality Check

Used For

  • +**Your pull requests sit for days before anyone reviews them** → Automatically routes code to the right reviewers and nudges people in Slack when things stall
  • +**You're guessing why deployments take 3 weeks instead of 3 days** → Shows exactly where code gets stuck - coding time, review time, or deployment bottlenecks
  • +**Manual code reviews miss security bugs and performance issues** → AI reviews catch problems before they hit production
  • +Tracks impact of AI coding tools like GitHub Copilot - measures if your $200k investment actually speeds up delivery
  • +gitStream automation approves low-risk changes automatically - no waiting for humans to approve typo fixes

Best For

  • >Your engineering team keeps missing deadlines and nobody knows why
  • >You're promoting developers to managers and they need data instead of gut feelings
  • >Spending $200k on GitHub Copilot and your CEO wants proof it's working

Not For

  • -Teams under 15 engineers — the insights come from comparing teams and patterns, not much to compare with 5 people
  • -Companies still deploying manually or using basic Git workflows — needs mature CI/CD pipelines to be useful
  • -Anyone wanting simple project tracking — this is for engineering process optimization, not basic task management

Pairs With

  • *GitHub or GitLab (where your actual code lives and LinearB pulls all its data from)
  • *Jira (to connect code changes with actual project progress and business requirements)
  • *Slack (where the coaching bot sends passive-aggressive reminders about stalled pull requests)
  • *GitHub Copilot (LinearB measures if your AI coding investment actually makes teams faster)
  • *Snowflake or BigQuery (to export engineering metrics into your company's data warehouse for executive dashboards)

The Catch

  • !No public pricing, which usually means "enterprise expensive" — likely $5k-50k annually based on the target market
  • !Requires connecting all your tools (GitHub, Jira, Slack) via APIs — if your workflow is spread across random tools, setup gets messy
  • !The automation features need someone technical to configure properly — not just point-and-click for non-technical managers

Bottom Line

Finally answers "why does shipping code take forever?" with actual data instead of developer shrugs.