Linear connector

Use your Linear data for reporting, automation and AI.

Data Panda brings your Linear data together with the data from the rest of your business. From one place, we turn it into dashboards, automations, AI workflows and custom apps your engineering leads, product managers and operators use every day.

Data Panda Reporting Automation AI Apps
Linear logo
About Linear

The opinionated issue tracker tech-forward teams run on.

Linear was founded in 2019 by Karri Saarinen, Jori Lallo and Tuomas Artman, with the explicit thesis that engineering teams had outgrown the heavy, configurable issue trackers built for the previous decade. The product is keyboard-first, real-time, and prescriptive about how teams should work: short cycles instead of open-ended sprints, issues as the unit of communication instead of user stories, projects rolling up into initiatives. The GraphQL API exposes issues, projects, cycles, teams, milestones, labels, workflow states, comments and attachments, which is the same surface the desktop app reads and writes against. Today Linear runs more than 25,000 organisations including OpenAI, Coinbase, Ramp, Mercury and Vercel.

For engineering and product leaders, Linear is the system of record for what's in flight, what shipped this cycle and what's blocked. The built-in views cover the daily work well. The harder questions sit between Linear and the systems around it: how planned cycle scope tracks delivered scope, where lead time is widening, how PR review time compares across teams, and which customer-reported bugs from the CRM still sit open against a renewing account. Pulling Linear into a warehouse is how those questions stop being a weekly screenshot in the leadership channel.

What your Linear data is for

What you get once Linear is connected.

Engineering and delivery reporting

Cycle throughput, lead time, project burn-up and initiative progress in one place, across teams and products.

  • Cycle throughput per team, against the scope committed at cycle start
  • Lead time and cycle time per issue type and project, on a rolling window
  • Initiative burn-up with real issue close dates, not manual percentage fields

Process automation

Turn CRM, support and product-feedback events into the right Linear work, without anyone copying messages into issues each morning.

  • Create bug issues from support escalations with customer tier and repro steps attached
  • Route customer-reported defects on top-tier accounts to the right team and project
  • Close issues automatically when the linked GitHub PR is merged and deployed

AI workflows

Put issue, comment and cycle history behind AI that knows how your teams really deliver.

  • Reopen-risk scoring on closed issues based on comments, label history and component churn
  • AI summaries of cycle and project status for product and exec updates
  • Intake triage that routes new bugs and requests to the right team and label

Custom apps on your data

Internal tools on Linear data that teams keep rebuilding as Linear views or Notion dashboards.

  • Engineering-health workbench with cycle throughput, lead time and PR review time per team
  • Customer-bug console mapping open issues to CRM accounts and contract value
  • Release-notes app driven by issues closed between two deploy tags
Use cases

Use cases we deliver with Linear data.

A list of concrete reports, automations and AI features we have built on Linear data. Pick the one that matches your situation.

Cycle throughputIssues completed per cycle and team, against the scope committed at cycle start.
Cycle timeTime from started to completed, per issue type and team.
Lead timeTime from issue creation to release, per project and team.
PR-to-deployMerged GitHub pull request to production deploy, per team and service.
Reopen rateIssues closed then reopened within N days, per team and label.
Initiative burn-upInitiative scope against completed issues, with scope-change history.
Project healthProject status, target date drift and at-risk issues per project lead.
Customer-bug loadOpen bug issues linked to a CRM account, weighted by contract value.
Triage backlogNew issues sitting unassigned, per project and priority.
Release notes draftIssues closed between two deploy tags, grouped for changelog.
Workload per assigneeOpen issue count and estimate per assignee, per cycle.
Label trendIssue count by label over time, surfaces drifting categories.
Real business questions

Answers you will finally get.

Are we shipping the scope we committed at cycle start?

Cycle throughput per team next to the scope set at cycle planning, with the issues that landed in-cycle versus those that slipped to the next cycle. Engineering managers see the gap on day three of the cycle to rebalance, instead of in the cycle review when the slip is already locked in.

Where is lead time widening?

Median and 90th-percentile lead time per project and issue type, on rolling windows. Where lead time on a specific project has doubled over eight weeks, it surfaces as a number, alongside the PR review time and reopen rate that usually move with it.

Which customer-reported bugs are sitting on top-tier accounts?

Open Linear bug issues joined to the CRM account that raised them, weighted by contract value and renewal date. Account managers see the operational picture on the account record before the renewal call, instead of asking engineering to export a Linear filter the morning of.

Value for everyone in the organisation

Where each function gets value.

For finance leaders

Engineering effort per project and product line next to the budget line it sits on. The finance view of capex-versus-opex on software work stops being a per-quarter reclassification and becomes a living report drawn from Linear cycles.

For sales leaders

Customer-reported bugs and feature requests tied back to the CRM account. Account executives see whether the three promised fixes shipped on time, before the renewal call rather than during it.

For operations

Cycle throughput, lead time, release cadence and triage backlog in one view. Engineering managers, product and ops share the same numbers instead of three different Linear screenshots taken the morning of the steerco.

Ideas

What you can automate with Linear.

Pair with GitHub

Sync GitHub pull requests with Linear issues

Linear issues link to the GitHub pull requests that close them, and the warehouse joins both sides so cycle time, PR review time and merge-to-deploy land in one number per team. When a PR is merged on the branch tied to LIN-1234, the issue moves to Done automatically, and the deploy tag attaches the resolved issues to the release record. Engineering leads stop reconciling Linear cycles against GitHub branches by hand.

Pair with Slack

Post Linear cycle and incident updates to Slack

Cycle-status changes, P1 issues and triage backlog growth post into the right Slack channels with the team, project and assignee in the message. The leadership channel gets a single end-of-cycle digest pulled from the warehouse instead of someone screenshotting the cycle view each Friday. Account-team channels get pinged the hour a P1 opens against one of their named accounts.

Pair with HubSpot

Link HubSpot accounts to their open Linear bugs

HubSpot accounts and deals tie back to Linear issues raised on their behalf, so CSMs see open bug and feature-request counts per account, weighted by ARR. Account owners are notified the hour a P1 on their account opens in Linear, instead of finding out from the customer the next day. Renewal-pipeline reviews show which top-tier accounts have unresolved engineering work against them before the call goes out.

Pair with Notion

Push Linear cycle and project status into Notion

Linear cycle throughput, project health and initiative burn-up land on the Notion pages product and engineering already use for weekly updates. The Notion roadmap stops being a stale block of bullets, and the cycle-review doc opens with the real numbers instead of an embed someone has to refresh by hand. The same warehouse layer feeds the engineering wiki and the exec-update template.

Your existing tools

Your data lands in a warehouse. Your BI tools read from it.

You keep the reporting tool you already have. We connect it to the warehouse where your Linear data lives.

Power BI logo
Power BI Microsoft
Microsoft Fabric logo
Fabric Microsoft
Snowflake logo
Snowflake Data warehouse
Google BigQuery logo
BigQuery Google
Tableau logo
Tableau Visualisation
Microsoft Excel logo
Excel Sheets & pivots
Three steps

From Linear to answers in three steps.

01

Connect securely

OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.

02

Land in your warehouse

Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.

03

Reporting, automation, AI

We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.

Two ways to work with us

Pick the track that fits how you work.

Track 01

Self-serve

We set up the foundation. Your team builds on top.

  • Linear connector configured and running
  • Warehouse set up in your cloud account
  • Clean access for your Power BI, Fabric or Tableau team
  • Documentation on what's in the data model
  • Sync monitoring so you're warned before reports break

Best fit Teams that already have a BI analyst or data engineer and want to own the build.

Track 02

Done for you

We build the whole thing, end to end.

  • Everything in Self-serve
  • Dashboards built to the questions your team actually asks
  • Automations between your systems
  • AI workflows scoped to real tasks your team runs
  • Custom apps where a dashboard does not cut it
  • Ongoing delivery at a pace that fits your team

Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.

Before you book

Frequently asked questions.

Who owns the data?

You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.

How fresh is the data?

Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.

Do I need a warehouse already?

No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.

Do cycles, projects and initiatives all come across?

Yes. Cycles, projects, initiatives and the issues that roll up into each one all land in the warehouse on the same schema Linear's GraphQL API exposes. That keeps cycle throughput reportable next to project burn-up and initiative progress, instead of needing three separate exports.

What about labels, workflow states and custom estimation?

Labels, workflow states and the team-level estimation scale come across as their own dimensions, so reports can group on them and history is preserved when teams rename a state or retire a label. When a workflow state is renamed in Linear, the warehouse keeps the prior name in the history so older cycles still report cleanly.

GDPR-compliant
Data stays in the EU
You own the warehouse

A first deliverable live in four to six weeks.

We review your Linear setup and the systems around it. Together we pick the first thing worth building.

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