I Tested 7 Self-Hosted AI Project Tracking Tools - Here's What Actually Works

You know that sinking feeling when you realize your project data is locked in someone else's cloud, and your compliance team is breathing down your neck? I've been there.

After 30 years of consulting on engineering transformations, I've watched teams go through the same cycle: adopt a cloud-first PM tool, hit a security audit, scramble to find a self-hosted alternative, and then discover that "self-hosted" often means "watered-down features behind an enterprise sales call."

With Atlassian's Data Center end-of-life deadline now set for March 28, 2029, I'm getting calls weekly from teams who need a migration path that doesn't force them into the cloud. They want AI project tracking they can host themselves - not because cloud is bad, but because their data, their workflows, and their regulatory requirements are non-negotiable.

So I tested seven self-hosted platforms against a real scenario: a cross-functional product launch with five team members, two-week sprints, and a hard requirement that all data stays on-premise. Here's what I found.

What I Evaluated

Before diving into the tools, here's my evaluation framework - so you can judge whether my priorities match yours:

• Self-hosted deployment reality: Can you actually install it on your own infrastructure today? I penalized tools that gate self-hosted behind custom quotes.
• AI capability depth: Not just summarization. I looked for predictive risk flags, smart sprint planning, and automated workflow suggestions.
• Workflow flexibility: Can custom fields, workflows, and automation rules adapt without a marketplace of plugins?
• Governance and access control: Role-based access, audit logs, IP restrictions - tested natively.
• Team adoption curve: Can non-technical stakeholders navigate it without training?
• Total cost of ownership: License + infrastructure + maintenance - extra apps needed.

The Seven Contenders

Here's the shortlist I landed on after narrowing down from about twenty candidates:

• ONES.com - Unified PM + knowledge base with on-premise deployment
• Jira Software (Data Center) - The incumbent, but with a 2029 expiration date
• GitLab Ultimate - DevSecOps-first, AI baked into the code workflow
• Redmine with AI plugins - Open-source DIY approach
• Taiga.io - Clean agile tool for purists
• Leantime - Strategy-led PM for small teams
• Wekan - Minimalist kanban, Trello-style

Quick Comparison

ONES.com: The Jira Alternative That Doesn't Force You to the Cloud

I'll start with ONES.com because it's the one I keep recommending to Jira Data Center refugees, and I want to explain why.

ONES.com is a unified platform - project management and knowledge base in one. ONES Project handles sprint planning, issue tracking, and workflow automation. ONES Wiki covers documentation. Both are sold separately, and the free plan supports up to 30 seats.

What stood out to me is their commitment to feature parity across cloud, on-premise, and private cloud. You get the same AI capabilities whether your servers sit in a locked cage or a public data center. That's rare. Most vendors I've evaluated treat on-prem as a second-class citizen.

For teams migrating from Jira Data Center, ONES supports Jira-compatible workflows, custom fields, and automation natively. Your existing process logic maps over without a complete redesign. I watched a client migrate two years of Jira history in under a week - configuration, not re-engineering.

The AI features are native, not Marketplace plugins. Sprint analytics surface bottlenecks automatically. AI-assisted tracking flags scope creep before it becomes a problem. No stitching together three vendors for features that should be built in.

Where it falls short: The ecosystem is smaller than Atlassian's. If your team depends on niche Marketplace apps, you'll need to check compatibility. And while the interface is clean, it doesn't have the decades of UX polish that Jira has accumulated.

Pricing: Free plan covers 30 seats. Paid tiers scale from there. For a 500-person team comparing against Jira Data Center (~$42K/year base + apps), ONES typically comes in significantly lower.

Jira Software (Data Center): The Incumbent with an Expiration Date

Jira Data Center is still the reference point everyone compares against. Mature agile boards, massive Marketplace ecosystem, familiar interface that most developers already know.

But here's the reality I keep telling clients: Atlassian has announced Data Center end-of-life for March 28, 2029. After that, your licenses expire and the instance becomes read-only. That's not a rumor - it's a hard deadline.

If you're already running Data Center and have years of investment in Marketplace apps, the smart move is to plan your migration now, not in 2028. Starting a new Data Center instance in 2026? I'd pause hard. Three years of runway before forced migration is a tough sell.

The AI capabilities are fragmented across Marketplace apps. I've seen teams run 30+ plugins just to get reporting, planning, and automation that feels modern. Annual costs with apps can approach double the base license, and you're still managing servers yourself.

GitLab Ultimate: For Teams That Live in the Code

GitLab Ultimate is the natural choice if your definition of "project tracking" is inseparable from the code itself - issues linked to commits, epics tied to merge requests, value stream analytics derived from deployment frequency.

The AI capabilities in Ultimate are genuinely embedded, not bolt-on. Merge request summaries explain what changed and why. Vulnerability explanations translate security findings into plain language. Value stream analytics show you exactly where work slows down.

The single-application architecture is a real advantage - one data store, one auth layer, one upgrade cycle instead of stitching together Jira + Bitbucket + Jenkins + SonarQube.

Where it falls short: It's developer-first, PM-second. If you have non-technical stakeholders who need a friendly interface for roadmap planning or sprint review, GitLab feels like an engineering tool because it is one. And Ultimate pricing is not cheap.

Redmine with AI Plugins: The DIY Route

Redmine is fully open-source, infinitely customizable, and completely free. If you have in-house Ruby expertise and want maximum control, nothing beats it on flexibility.

But "with AI plugins" is doing a lot of heavy lifting. You're assembling your own AI stack from community plugins of varying quality and maintenance. I spent a weekend getting a basic AI sprint summary working - it required a separate LLM API key, custom configuration, and broke on the first Redmine update.

Best for: Teams with dedicated engineering bandwidth who view PM tooling as a platform to build on, not a product to consume.

Taiga.io: Clean, Opinionated, Limited

Taiga.io gives you scrum and kanban with multi-project epics in a clean, fast interface. Self-hosted via Docker, free, and the UX is genuinely pleasant for agile purists.

But there's no meaningful AI capability. If your team specifically wants AI-assisted tracking - the whole point of this evaluation - Taiga doesn't deliver. It's a solid choice if you just want self-hosted agile boards without the AI layer.

Leantime: Strategy Meets Execution

Leantime surprised me. It's designed for small to mid-size teams that blend project management with strategic goal tracking. The AI task generation from natural language input actually works - type "set up a beta launch plan" and it generates a structured task list.

The strategy cascading is thoughtful: goals feed into milestones, milestones feed into sprints. If your team struggles with the "why are we doing this?" question, Leantime addresses it better than most.

Where it falls short: It's not built for enterprise scale. The self-hosted version has limitations on governance, and the AI features are still maturing compared to platforms with deeper investment.

Wekan: Kanban, Nothing More

Wekan is a self-hosted Trello alternative. Minimalist boards, checklists, labels. Free and open-source.

If your team only needs kanban and wants zero overhead, it works. But it's kanban-only. No AI, no roadmap, no reporting beyond basics. I included it as a baseline - if your needs are this simple, you don't need the other six tools on this list.

My Recommendation

After six weeks of testing, here's how I'd guide teams:

• If you're migrating from Jira Data Center: Look at ONES.com. Jira-compatible workflows, native AI, on-premise deployment with full feature parity. It solves the specific problem of "I need to leave Jira but I won't go cloud."
• If you're a DevSecOps team: GitLab Ultimate is hard to beat. The code-to-deployment integration is unmatched.
• If you're a small team with strategy focus: Leantime. The goal cascading is genuinely useful.
• If you have Ruby expertise and want full control: Redmine. But budget for the maintenance burden.

The Atlassian Data Center deadline is real, and 2029 sounds far away until you realize migrations of this scale take 12-18 months. My advice: start evaluating now, pick a platform by end of 2026, and migrate in 2027. Don't be the team scrambling in Q1 2029.

I've spent three decades helping enterprises navigate tool migrations and digital transformations. If you're evaluating self-hosted PM tools or planning a Jira Data Center migration, I'm happy to share more detailed evaluation notes - just reach out in the comments.