Drive productivity with engineering context

LinearB accelerates every step of the SDLC, with guardrails and scale built in, from an agent cutting the cost of a code change to a board-ready AI ROI report on demand.

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Context for your software factorySample data

Collect

Every commit, ticket and build across your SDLC

Planning
Code
AI tools
Quality
CI/CD
Incidentsvia API

+ 40 more integrations

Normalize
Enrich
Augment

How the context layer works

Serve

Context for every person and agent, where they work

PeopleAsk AI in LinearB

What's my AI ROI?

2 tools used

Cost per effective PR is $602, down 4% since the AI rollout. Copilot PRs return the most per dollar.

Agents

Claude CodeLinearB MCP

Refactor the retry logic in payments-api

get_ai_dev_tools · payments-api

Low-risk refactor, so switching to Sonnet at medium effort. Est. $1.30, down from $4.10.

Save moneyGain velocityImprove quality

Explore engineering context on demand in Agentic Studio

Explore
Measure
Act

Ask a question in plain language and LinearB's AI assistant answers in place, with the chart and the figures behind it. You can bring the same context into Claude, ChatGPT or Cursor through MCP.

try a prompt

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Sample data

Hello, Sam!

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Build?

Chart PRs merged per week by teamCompare cycle time across teamsShow AI cost per PR for each tool

LinearB dashboards track AI adoption and cost, cycle time and DORA metrics for every team. When a team measures something its own way, LinearB builds the metric from a plain-language description.

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See engineering metrics

DashboardsAI impactSample data

Act on it in every PR, with agents and workflows

Explore
Measure
Act

Your agents and gitStream act on LinearB's context in every PR. LinearB recommends the effort each task needs from how risky the code is, and gitStream merges low-risk changes and routes risky ones to the reviewers who know the code.

run a workflow

See workflow automation

payments-api/Pull requests#9201Sample data

Refactor the retry logic in the payments webhook handler #9201

OpenClaude Code wants to merge 3 files into main

low risk

Customers

How engineering leaders are proving AI impact

Gartner® Magic Quadrant™

LinearB is a Leader

Nik SudanEngineering Operations LeadRead the Kraken story

Natively secure, obsessively compliant

LinearB is independently audited against the following standards, and can provide supporting evidence and information about the controls we have in place:

LinearB Inc. participates in the EU-U.S. Data Privacy Framework, the UK Extension to the EU-U.S. DPF, and the Swiss-U.S. Data Privacy Framework. Our participation can be verified on the Data Privacy Framework List.

GDPR: General Data Protection Regulation

See whether AI is paying off, pillar by pillar

APEX is LinearB's framework for proving AI is lifting throughput without costing delivery confidence, efficiency or developer experience.

APEX Platform team · last 90 daysSample data

AI leverageWeekly
Is AI helping us ship more?
Merged PRs a week212▲ 18%
Human-writtenAI-assisted
In LinearB: AI & developer productivity insights, AI code reviews, MCP server
PredictabilityEvery sprint
Do we deliver what we commit to?
Planning accuracy84%▲ 6 pts
In LinearB: Dev team management, Executive reporting & ROI
EfficiencyMonthly
How smoothly does work reach production?
Cycle time1.8 days▼ 31%
In LinearB: Workflow automation, gitStream, Resource allocation
eXperienceQuarterly
Are the gains sustainable for developers?
Developer satisfaction4.1 / 5▲ 0.3
In LinearB: Developer experience optimization, Developer surveys