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Automate Gitlab with AI Agents.

Automate software delivery and engineering operations with GitLab and AI workers. Use Toolhouse to streamline development workflows, reduce manual coordination, and keep teams shipping faster.

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Your GitLab AI Worker

GitLab AI Worker

Active

You: Review all new GitLab issues opened in the last 24 hours, classify them by bug, feature request, support, or internal task, assign priority based on customer impact, and draft recommended owners for each item.

Scanning new GitLab issues across active projects...

Classifying requests and ranking by business impact...

47 new issues triaged and routed in one pass.

The worker grouped incoming issues by type, highlighted 9 high-priority items tied to customer impact, and prepared owner recommendations so engineering and support can...

47Issues triaged

9High-priority issues flagged

6 hoursBeforeto8 minWith Toolhouse

Use cases

Top GitLab automation use cases

Use case 1

Triage issues automatically

Toolhouse AI workers can use GitLab to organize incoming issues, classify requests, and route work to the right team automatically. This helps engineering, support, and operations teams reduce manual triage and respond faster to bugs, feature requests, and internal tasks. Better issue routing keeps development workflows moving and lowers administrative overhead. It is a practical way to improve workflow automation around product delivery.

Your GitLab AI Worker

GitLab Merge Review AI Worker

Active

You: Check all open merge requests, identify anything stalled for more than 48 hours, summarize what changed in each MR, and draft follow-up notes for the right reviewer or team lead.

Reviewing open merge request activity...

Flagging stalled approvals and summarizing code changes...

14 stalled merge requests surfaced before they delayed release.

The worker summarized each open merge request, identified bottlenecks in review flow, and prepared follow-up prompts for reviewers so code moves through approval faster...

14Stalled MRs found

22Reviewer nudges prepared

1 business dayBeforeto11 minWith Toolhouse

Use case 2

Monitor merge request activity

Merge requests often create repetitive coordination work across reviewers, managers, and contributors. AI workers can watch GitLab activity, summarize changes, flag stalled reviews, and prompt the right next step before delivery slows down. This helps teams move code through review with less status chasing and fewer bottlenecks. The result is faster engineering operations and more reliable software delivery automation.

Your GitLab AI Worker

GitLab Release Coordination AI Worker

Active

You: Audit the upcoming release branch, list unresolved blockers, confirm which merge requests are still pending, and draft a release readiness summary for engineering, product, and support.

Checking release branch status and pending dependencies...

Compiling launch blockers and readiness updates...

Release blockers reduced from 11 to 3 before launch review.

The worker pulled together release status, identified unresolved dependencies, and created a concise readiness summary for cross-functional teams. That cuts last-minute...

11Blockers identified

3Teams aligned

2 daysBeforeto18 minWith Toolhouse

Use case 3

Speed up release coordination

Releases depend on many moving parts, from final approvals to stakeholder communication. With GitLab in the workflow, AI workers can track release readiness, alert teams to blockers, and coordinate follow-up tasks automatically. That reduces the manual effort required to keep launches on schedule. For growing teams, this creates a more scalable operations platform for shipping product updates.

Your GitLab AI Worker

GitLab Incident Follow-Up AI Worker

Active

You: Take the issues and merge requests related to yesterday's production incident, summarize what changed, generate post-incident action items, and draft remediation tasks with owners and due dates.

Collecting incident-related issues and merge requests...

Drafting action items and assigning remediation owners...

23 post-incident tasks created with clear ownership.

The worker connected incident-related GitLab activity into one follow-up package, drafted remediation tasks, and organized owners and due dates so engineering teams can...

23Follow-up tasks created

1Incidents summarized

7 hoursBeforeto14 minWith Toolhouse

Use case 4

Automate incident follow-up

When incidents or urgent fixes happen, teams need fast context and consistent follow-up. Toolhouse can use GitLab to help AI workers create remediation tasks, summarize what changed, and ensure action items are assigned after the issue is resolved. This improves accountability without adding more manual process after a stressful event. It is especially useful for support, engineering, and operations workflows that need tighter execution.

Your Gitlab AI Worker

Gitlab AI Worker

Active

You: Automate software delivery and engineering operations with GitLab and AI workers. Use Toolhouse to streamline development workflows, reduce manual coordination, and keep teams shipping faster.

Reading workflow context...

Preparing the next best action...

Automate incident follow-up

When incidents or urgent fixes happen, teams need fast context and consistent follow-up. Toolhouse can use GitLab to help AI workers create remediation tasks, summarize...

-Tasks handled

-Actions ready

manualBeforetominutesWith Toolhouse

Use case 5

Report on engineering workflow health

Engineering leaders need visibility into issue volume, review delays, release cadence, and delivery bottlenecks. AI workers can turn GitLab activity into simple reporting that highlights trends and surfaces where manual work is slowing the team down. This makes it easier to improve workflow tools and prioritize automation efforts with clear business impact. Better reporting supports stronger planning, operations, and team performance.

Your Gitlab AI Worker

Gitlab AI Worker

Active

Reading workflow context...

Preparing the next best action...

Report on engineering workflow health

Engineering leaders need visibility into issue volume, review delays, release cadence, and delivery bottlenecks. AI workers can turn GitLab activity into simple reportin...

-Tasks handled

-Actions ready

manualBeforetominutesWith Toolhouse

Testimonials

What our customers say

1,000,000+ agents· 15,000+ teams· 1,000+ integrations· Start for free

“We built in record time what would have taken weeks otherwise! I can honestly say that without Toolhouse, our team would have been spending much MUCH more time delivering AI features in the products we're building.”

Marcos Ocón

COO @ Develative (Developer Agency)

EngineeringSince 2025

“I built an agent that qualifies my leads and books calls automatically. No developer, no agency. It paid for itself in the first week.”

Andrew Njoo

Founder @ Stack2Sale

MarketingSince 2025

“Our team of 12 was drowning in repetitive tasks. We described what we needed and the agent just worked. We didn't write a single line of code.”

Kristian Freeman

Manager @ Large Engineering Company

InfrastructureSince 2025

Pricing

Simple, transparent pricing

Start free, scale as you grow. No hidden fees, no surprises.

Business

$500/month

Includes FREE unlimited tokens

Credits / month25,000
Workers50
Log retention30 days
Worker email inboxIncluded
OnboardingIncluded
Organizations—
Account engineer—
SupportSlack, Email

Start now →

No credit card needed

For scaling businesses

Business Max

$1,200/month

Includes FREE unlimited tokens

Credits / month80,000
Workers500
Log retention1 year
Worker email inboxIncluded
OnboardingIncluded
OrganizationsIncluded
Account engineerOn demand
SupportPriority (Slack, Email, Phone)

Start now →

No credit card needed

For larger companies

Enterprise

Custom

For scaling needs

Credits / monthVolume pricing
WorkersUnlimited
Log retentionCustom
Worker email inboxIncluded
OnboardingIncluded
OrganizationsIncluded
Account engineerNamed
SupportCustom

Talk to sales →

14-day free trial on all plans · cancel anytime

FAQ

Using Gitlab with AI workers

Common questions about GitLab automation with AI workers.

How can Toolhouse automate GitLab workflows?

Toolhouse lets you build AI workers that use GitLab to automate issue triage, merge request monitoring, release coordination, incident follow-up, and engineering reporting. This reduces repetitive manual work and helps teams move faster.

Is GitLab a good fit for AI workers?

Yes. GitLab is a strong fit for AI workers because it sits at the center of software delivery, team coordination, and engineering operations where workflow automation can save significant time.

What teams benefit from GitLab automation?

Engineering, product, support, DevOps, and operations teams benefit most because they can automate repetitive development workflows, improve visibility, and keep projects moving with less manual coordination.

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