ReleasePilot AI

ReleasePilot is an AI release agent that reads your GitLab repo, scores deployment risk in real time, and tells your team exactly what to fix — before a bad release reaches production.

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Inspiration

Software releases often require manual checks across multiple GitLab resources, including open issues, merge requests, pipeline status, deployment readiness, and approval workflows. This process is repetitive, time-consuming, and prone to human error. We wanted to build an AI-powered agent that helps engineering teams make faster and more informed release decisions.

What it does

ReleasePilot AI is an intelligent release-readiness agent that analyzes GitLab repositories and helps teams determine whether a release is ready for deployment.

The platform:

  • Analyzes GitLab repositories using repository URLs
  • Retrieves repository metadata, issues, merge requests, and pipeline information
  • Calculates release risk indicators
  • Generates AI-powered release summaries using Gemini
  • Highlights deployment blockers and findings
  • Automatically creates release checklists in GitLab for engineering teams

Instead of manually reviewing multiple sources, teams receive a consolidated release assessment in seconds.

How we built it

ReleasePilot AI was built using:

  • Angular for the frontend user interface
  • Spring Boot and Java 17 for backend services
  • Google Gemini for AI-powered reasoning and release analysis
  • GitLab APIs for repository, issue, merge request, and pipeline integration
  • Render for cloud deployment

The frontend accepts a GitLab repository URL and sends it to the backend. The backend gathers repository information from GitLab, performs release-readiness analysis, and uses Gemini to generate an actionable summary. Users can also generate release checklists directly within GitLab.

Challenges we ran into

  • Integrating multiple GitLab APIs and handling different repository states
  • Designing a meaningful release risk assessment workflow
  • Managing environment variables securely for deployment
  • Containerizing and deploying the Spring Boot application with Docker
  • Configuring Angular production builds and deployment on Render
  • Ensuring smooth communication between frontend and backend services

Accomplishments that we're proud of

  • Successfully built and deployed a full-stack AI-powered release management platform
  • Integrated Gemini to provide intelligent release summaries
  • Automated release checklist generation within GitLab
  • Created an end-to-end workflow that reduces manual release review effort
  • Deployed both frontend and backend services in the cloud

What we learned

Through this project we gained hands-on experience with:

  • Building AI-powered developer productivity tools
  • Integrating Gemini into enterprise workflows
  • Working with GitLab APIs and automation workflows
  • Deploying full-stack applications using Docker and Render
  • Designing practical AI-assisted decision-making systems

What's next for ReleasePilot AI

Future enhancements include:

  • Security vulnerability and dependency scanning
  • Historical release trend analysis
  • Multi-repository release orchestration
  • Slack and Microsoft Teams integrations
  • Automated release approval workflows
  • Support for additional DevOps platforms beyond GitLab
  • Advanced agent-based release planning and deployment recommendations

ReleasePilot AI aims to become a complete AI-powered release engineering assistant that helps teams ship software faster, safer, and with greater confidence.

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