Build CI Pipelines Without Writing YAML

1. 1

   Create your account

   Sign up with email, Google, or GitHub — or join the waitlist while PipeStudio is in development.

   Available sign-up methods

   • Email and password
   • Google account (OAuth)
   • GitHub account (OAuth)
   • Waitlist at /signup (pre-launch)
2. 2

   Build your project definition

   Use the guided wizard or drag-and-drop canvas. Both paths produce the same project definition.

   What you'll configure

   • Repository URL and CI platform (GitLab or GitHub)
   • Language, framework, stages, build, and test settings
   • See Wizard vs Canvas if you're unsure which path to pick
3. 3

   Simulate on PipeStudio

   Run your pipeline in-platform before exporting. Stream logs, inspect block output, and fix issues while context is fresh.

   Learn more

   • See Pipeline Simulation for the full workflow
   • Confirm stages pass before committing config to CI
4. 4

   Export and commit

   Generate platform-specific config, review output, and commit to your repository.

   You can

   • Download YAML for GitLab CI or GitHub Actions
   • Save your pipeline for future reference
   • Track changes in Git via pull request — see Versioned Configs

First pipeline in minutes

Answer wizard questions about your repo and stack — or skip to the canvas when you already know your CI shape. Generate a reviewable pipeline from a clear project definition instead of a blank config file.

WizardCanvasQuick start

Ship CI with confidence

Run the pipeline on PipeStudio before anything reaches GitLab or GitHub. Fix broken stages early with streamed logs and block-level output, then commit only when the run looks right.

SimulationLogsValidation

One definition, both platforms

Keep a single project definition and export GitLab CI or GitHub Actions config when you're ready. Switch platforms without rebuilding from scratch.

Multi-platformExportGit

9-step pipeline wizard

Walk through project basics, pipeline structure, runners, build, testing, notifications, advanced options, review, and generation.

Visual pipeline editor (canvas)

Drag and drop stages and jobs, connect dependencies, and preview config updates in real time. Switch between wizard and canvas on the same project.

In-platform pipeline simulation

Run the full pipeline flow inside PipeStudio. Stream logs per block, confirm stages pass, and iterate without burning CI minutes.

AI pipeline generation

Turn wizard answers or canvas layouts into GitLab CI or GitHub Actions config. Preview, simulate, edit, and regenerate as your project evolves.

AI-powered suggestions

Get recommendations for security, performance, testing strategy, and platform-specific best practices.

Multi-platform support

Generate GitLab CI and GitHub Actions pipelines from the same project definition.

Real-time validation

Receive immediate feedback on required fields, syntax, security, and configuration issues while you build.

Versioned project configs

Commit generated config to Git for review in pull requests. Promote changes through branches with a clear audit trail.

File management

Save pipeline definitions, download exports, and manage your pipeline library in one place.

When to use the wizard

• You're new to CI or want guided questions about repo, language, stages, and tests
• You want defaults suggested from your repository and stack
• You prefer a checklist-style flow with validation at each step

When to use the canvas

• You already know your pipeline shape and want full control
• You need to fine-tune every command, param, and dependency
• You want to compose lint, test, build, and deploy blocks visually

1. 1

   Project & repo basics

   Provide your repository URL, choose GitLab or GitHub, and configure language and framework.

2. 2

   Pipeline structure

   Define stages and jobs — the skeleton of your pipeline from lint through deploy.

3. 3

   Execution mapping

   Map jobs to runners or agents, including labels, environments, and execution targets.

4. 4

   Build configuration

   Define build commands, caching, environment variables, and artifact management.

5. 5

   Testing & security

   Configure tests, coverage, security scans, and linting tools.

6. 6

   Notifications

   Set up Slack, Discord, email, or custom webhook notifications.

7. 7

   Advanced options

   Configure matrix builds, schedules, manual approvals, and timeouts.

8. 8

   Review

   Confirm your complete configuration before generation.

9. 9

   Generate pipeline

   Generate GitLab CI or GitHub Actions config and download when ready.

For field-level detail on every step, see Wizard Field Reference.

Known gaps (not in current wizard flow)

1. 1

   Add stages

   Click the "+" button to add a stage. Stages run in sequence and group related jobs.

2. 2

   Add jobs

   Drag job templates into stages and configure commands, environment, and dependencies.

3. 3

   Connect jobs

   Define dependencies with edges so jobs run only after prerequisites succeed.

4. 4

   Preview config

   Watch your pipeline config update in real time, then export when ready.

What simulation does

In-platform simulation executes your project definition inside PipeStudio. You see real-time logs, block-level pass/fail status, and stage progression without consuming CI minutes or pushing config to your repository.

How to start a simulation

1. 1

   Build your project definition

   Complete the pipeline wizard or compose blocks on the visual editor canvas.

2. 2

   Open the simulation view

   From your project dashboard at launch, click "Simulate" to run against your current configuration.

3. 3

   Review results

   Watch logs stream block-by-block. Inspect stdout, stderr, and exit codes before exporting.

What you see during a run

Streamed logs

Live log output per block and stage.

Real-timeBlock output

Pass/fail indicators

Each block shows success or failure as the run progresses.

Status badges

Stage timeline

Visual timeline of stages and job dependencies.

StagesDependencies

Recommended workflow

1. 1

   Simulate your pipeline on PipeStudio

2. 2

   Fix configuration issues based on logs and validation feedback

3. 3

   Re-simulate until all stages pass

4. 4

   Export GitLab CI or GitHub Actions config to your repo

Per-step wizard validation

At generation time

• Syntax checks on generated YAML output
• Security and best-practice recommendations via AI
• Missing required fields surfaced on the Review step
• Platform-specific conventions for GitLab CI and GitHub Actions

Simulation as deeper validation

Validation catches structural and syntax issues early. Simulation goes further by executing your pipeline flow in-platform so you can confirm stages behave as expected before committing config. See Pipeline Simulation.

How it works

1. 1

   Provide project context

   Wizard answers or canvas block layout define your repo, stack, stages, build, and test setup.

2. 2

   Generate with AI

   PipeStudio uses AI (enabled by default) to produce platform-specific config matching your project definition.

3. 3

   Preview and iterate

   Review generated output, simulate the pipeline, adjust your definition, and regenerate as needed.

4. 4

   Export

   Download or copy `.gitlab-ci.yml` or workflow YAML and commit to your repository.

Distinct from AI suggestions

AI pipeline generation produces your full config file. AI suggestions (see AI Suggestions) recommend improvements to security, performance, and best practices — they do not replace generation.

Security recommendations

Security scans, dependency checks, and secret detection.

SASTDependency scanning

Performance optimization

Caching strategies, parallel jobs, and build-time reduction.

CachingParallel jobs

Best practices

Industry-standard patterns for your stack and pipeline layout.

Stage orderingResource limits

Testing strategies

Unit, integration, and E2E testing recommendations.

Test coverageTest matrix

Deployment types

• Docker
• Serverless
• Bare Metal
• Static Hosting

Target environments

• development
• staging
• production
• testing
• preview
• other

How to import

1. 1

   Open the visual editor

   From your project dashboard, open an existing project or create a new one and switch to the canvas.

2. 2

   Paste your config

   Paste GitLab CI YAML or GitHub Actions workflow YAML into the import panel.

3. 3

   Review the visual representation

   PipeStudio parses the config and converts it to stages, jobs, and dependencies on the canvas.

4. 4

   Edit and re-export

   Adjust blocks, simulate, and regenerate config for any supported platform.

Workflow

1. 1

   Generate from one project definition

   Wizard or canvas produces GitLab CI or GitHub Actions config.

2. 2

   Review in a pull request

   Commit generated config to your repo and review changes alongside application code.

3. 3

   Promote through branches

   Merge pipeline updates through your normal Git workflow — main, develop, release branches.

4. 4

   Maintain an audit trail

   Every pipeline change is versioned in Git with a clear history of who changed what and when.

Download config

Download generated config and commit it to your GitLab or GitHub repository. See Versioned Configs for the recommended Git workflow.

Save for later

Save your pipeline configuration to your account for future reference or as a reusable template.

Import existing config

Already have a pipeline? See Import Existing Pipelines.

Email & password

Create an account with your email. Verify with the OTP code or confirmation link we send.

Google OAuth

Sign in with Google. We only access basic profile information with your permission.

GitHub OAuth

Connect GitHub to access repositories and validate pipeline configurations.

What you can do from the dashboard

• View all pipeline projects
• Start a new pipeline via "Start New Pipeline"
• Open the guided wizard or drag-and-drop canvas for any project
• Run in-platform simulation and view run history
• Export GitLab CI or GitHub Actions config
• Access saved files and generated exports

Typical flow

1. 1

   Create or open a project

2. 2

   Build with wizard or canvas

3. 3

   Simulate and review logs

4. 4

   Export and download config

Settings

Manage your profile, account, security, and preferences from the dashboard settings area. You can update your display name and avatar, change email or password, review active sessions, export account data, and configure notification preferences.

Managing your files

Pipeline configurations and generated files are stored securely in your account. From the dashboard you can:

• View all saved pipelines
• Download YAML exports
• Edit and regenerate configurations
• Delete files you no longer need

Team workspaces

Shared workspaces for teams to collaborate on pipeline definitions. Coming in a future release.

Planned

Sharing & collaboration

Share projects with teammates, comment on pipeline changes, and co-edit configurations.

Planned

Billing & plans

Free tier at launch with premium features such as advanced AI, team collaboration, and priority support.

Planned

Enterprise

SSO/SAML, audit logs, and VPC or on-prem deployment options for larger organizations.

Planned

Setup checklist

Optionally provide a Personal Access Token to validate repository access. Commit the generated YAML to your repository.

1. 1

   Select GitLab CI in the wizard or project settings

2. 2

   Generate your pipeline YAML using the wizard or canvas

3. 3

   Download the generated `.gitlab-ci.yml` file

4. 4

   Commit the file to your GitLab repository

Setup checklist

Download workflow YAML and commit it to your repository's `.github/workflows/` directory.

1. 1

   Select GitHub Actions in the wizard or project settings

2. 2

   Sign in with GitHub OAuth for easy setup

3. 3

   Or create a token at GitHub → Settings → Developer settings with `repo` scope

4. 4

   Commit workflow YAML to `.github/workflows/`

How do I create a pipeline in PipeStudio?

Start with a guided wizard or a drag-and-drop canvas. Both paths build the same project definition — define your pipeline, simulate it on the platform, then export GitLab CI or GitHub Actions config when you are ready.

When should I use the wizard vs the drag-and-drop builder?

Use the wizard when you want step-by-step questions about your repo, language, stages, tests, and deploy targets. Use the canvas when you want full control — compose blocks and edit configs, params, and values directly. See Wizard vs Canvas.

How does AI pipeline generation work?

PipeStudio turns your wizard answers or canvas layout into reviewable GitLab CI or GitHub Actions config. Inspect the output, adjust your project definition if needed, simulate again, then commit the config to your repo. See AI Pipeline Generation.

Can I test a pipeline before pushing to my repo?

Yes. PipeStudio simulates runs on the platform so you can stream logs, inspect block output, and fix issues before the config lands in GitLab or GitHub. See Pipeline Simulation.

Can I store pipeline definitions in Git?

Yes. Generate config from your project definition, review the output, commit it to your repo, and run it on your CI provider. See Versioned Configs.

What platforms are supported?

GitLab CI and GitHub Actions. Choose your platform in the wizard or project settings and PipeStudio generates the matching config format from the same project definition.

What types of pipelines can I create?

Pipelines for any programming language and framework supported in the wizard — including Node.js, Python, Java, .NET, Go, Rust, Ruby, PHP, and Docker-based workflows.

Do I need to know YAML to use PipeStudio?

No. PipeStudio is visual-first. Advanced users can edit generated YAML output directly, or import existing config via the visual editor.

Is PipeStudio free to use?

Yes — PipeStudio is free. The product is currently in development; join the waitlist at /signup and we'll email you when it's ready. Premium features are planned for the future.

Is my data secure?

Yes. Data is encrypted in transit and at rest. Repository credentials are stored securely and never exposed to third parties. See Security.

Can I import my existing pipelines?

Yes. Paste existing YAML into the visual editor. See Import Existing Pipelines.

Pipeline won't generate

If pipeline generation fails, check the following:

• Verify all required wizard steps are completed
• Ensure all required fields are filled correctly
• Check that your project configuration is valid
• Review validation errors on the Review step

Generated config has errors

If validation errors appear in your generated config:

• Review error messages and fix missing required fields
• Ensure environment variables are properly quoted
• Check that image names and paths are valid
• Re-generate after fixing the project definition

Simulation fails or blocks don't pass

If in-platform simulation fails:

• Inspect streamed logs for the first failing block
• Verify build commands, test commands, and image references
• Confirm runner/agent mapping matches your intended environment
• Fix the project definition and re-simulate before exporting

Import doesn't parse correctly

If pasted YAML doesn't import as expected:

• Check for platform-specific syntax (matrix, child pipelines, custom DSL)
• Simplify complex sections and re-import in smaller pieces
• Manually adjust blocks on the canvas after import
• Validate with simulation before re-exporting

Can't save files

If you cannot save your pipeline configuration:

• Refresh the page and try again
• Clear your browser cache and cookies
• Ensure you're logged in with a verified account

Email support

Send us an email for technical support or product questions.

GitHub issues

Report bugs or request features on our GitHub repository.

Community & launch updates

Join the waitlist to get updates and connect with other users.

Overview

PipeStudio respects your privacy. This policy describes what data we collect, how we use it, and your rights. A full policy will be published before public launch.

Data we collect

• Waitlist email addresses when you sign up for launch notifications
• Account information when you register (email, OAuth profile basics)
• Pipeline project definitions and generated config you create in PipeStudio
• Usage data to improve the product (pages visited, features used)

How we use your data

• Provide and improve the PipeStudio service
• Send launch updates and product notifications (you can unsubscribe)
• Generate AI-powered pipeline YAML from wizard answers
• Secure your account and prevent abuse

Third parties

We use OpenAI only for AI pipeline YAML generation. OAuth providers (Google, GitHub) handle authentication. We do not sell your data to third parties.

Contact

Privacy questions: sudopeyman@gmail.com

Agreement

By using PipeStudio you agree to these terms. A complete terms of service will be published before public launch.

Service availability

PipeStudio is currently in development. Features, availability, and pricing may change. We provide the service on an "as is" basis during beta and pre-launch periods.

Acceptable use

• Do not use PipeStudio for unlawful purposes
• Do not attempt to access other users' data or accounts
• Do not abuse AI generation or platform resources
• Do not upload malicious code or credentials in pipeline definitions

Limitation of liability

PipeStudio generates CI configuration as a tool. You are responsible for reviewing generated config before deploying to production systems. We are not liable for pipeline failures, data loss, or downtime in your CI environment.

Data protection

All data is encrypted in transit (TLS) and at rest. We follow industry-standard security practices for authentication, storage, and access control.

Credentials

Repository credentials and tokens are stored securely and never exposed in generated config or logs. OAuth tokens are scoped to minimum required permissions.

Enterprise features (planned)

• SSO / SAML authentication
• Audit logs for team activity
• VPC and on-prem deployment options
• Vulnerability disclosure program

Report a security issue

Contact sudopeyman@gmail.com to report security concerns.