Open-source ticket-driven AI engineering for the full SDLC
By Tanmay Verma, Founder · Last verified 05 Jul 2026
In short
Openase — Open-source ticket-driven AI engineering for the full SDLC. Best for Engineering teams automating development workflows, Open-source contributors seeking AI-driven CI/CD pipelines, DevOps teams integrating AI agents into existing infrastructure. Free to use.
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OpenASE is a solid open-source option for teams wanting AI-driven SDLC automation. Its ticket-driven orchestration across multiple AI models (Claude Code, Codex, Gemini CLI) and live-editable Skill System set it apart from simpler code-gen tools. However, it requires self-hosting technical expertise, and documentation is sparse. If you need a polished SaaS or comprehensive docs, consider alternatives like GitLab Duo or GitHub Copilot Workspace. Best for early-adopter engineering teams comfortable with self-hosted infrastructure.
Skip Openase if Skip OpenASE if you need a polished SaaS with minimal setup, comprehensive documentation, or a large ecosystem of integrations—this is a self-hosted tool for technical teams.
Compare with: Openase vs Poolside AI, Openase vs Marvin, Openase vs Zhipu GLM
Last verified: July 2026
How likely is Openase to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →OpenASE, by Pacific Studio, is an open-source platform that automates the entire software development lifecycle using AI agents. Teams create tickets, assign agents, and watch the full cycle—from design through deployment—happen automatically. It supports multi-agent coding across Claude Code, Codex, and Gemini CLI, orchestrated via a Kanban board for real-time tracking. The Skill System lets you live-edit reusable expertise packages, giving agents domain-specific instructions. Built in Go as a single binary, OpenASE is self-hosted and ideal for teams accelerating development with AI without sacrificing control.
OpenASE addresses a real need: automating the entire software development lifecycle through AI agents. Its ticket-driven workflow means you create a ticket, assign an agent, and it handles design, coding, testing, deployment, and operations—all tracked on a Kanban board. The multi-agent support (Claude Code, Codex, Gemini CLI) gives flexibility. The Skill System is a standout: you can live-edit reusable packages with files and instructions, shaping agent behavior for your domain. Being open-source and self-hosted (Go single binary) gives you full control and data privacy. However, setup is not trivial; you need technical skills to deploy and maintain. The documentation is minimal, and the UI is basic—no mobile app, no polished reporting. Integrations are currently limited to GitHub and GitHub Actions. For teams that value control and are willing to invest in setup, OpenASE is promising. For teams needing a turnkey solution, look elsewhere.
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Concrete scenarios for the personas Openase actually fits — and what changes day-one when you adopt it.
Create a ticket 'Add OAuth2 login' on the Kanban board, assign it to a Claude Code agent, and watch as it generates 327 lines of code, opens a pull request, and passes review.
Outcome: Feature delivered in hours instead of days with full traceability.
Set up a CI/CD pipeline via GitHub Actions integrated with OpenASE; create a ticket to deploy a microservice, and the agent handles testing and deployment automatically.
Outcome: Automated deployments with zero manual intervention, reducing release cycles.
Create a security audit ticket on the board, assign a Claude Code agent with a security skill, and it scans endpoints for vulnerabilities and generates a report.
Outcome: Automated security reviews that catch issues before production.
as of 2026-07-05
as of 2026-07-05
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
For each published Openase tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Open Source (Community)
$0/mo
Ideal for
Engineering teams comfortable with self-hosting who want full control over their AI development pipeline without per-seat costs.
What this tier adds
Starting point: free and open-source with full features, self-hosted on your infrastructure.
The company stage and team size where Openase's pricing actually pencils out — and where peers do it cheaper.
OpenASE is free and open-source, making it ideal for cost-conscious teams that can self-host. Unlike proprietary platforms like GitLab Duo ($19/user/month) or GitHub Copilot ($10/user/month), you pay only for your infrastructure. Best for teams that value control over convenience.
How long it actually takes to get something useful out of Openase — broken out by persona, not the marketing-page minute.
For a team with Go experience and existing infrastructure, you can have OpenASE running in under an hour by downloading the single binary and configuring GitHub integration. Adding skills and fine-tuning workflows may take a day.
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
Common stack mates teams adopt alongside Openase, with the specific reason each pairing earns its keep.
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