You are trying to plan AI projects in 2026, which means managing fast-moving agentic workflows while keeping strict data sovereignty. You need tools that handle complex project tracking without forcing everything into the public cloud, but finding a platform that supports on-premises deployment, scales with AI-assisted development, and does not require ten plugins is painful. I tested the market to find the best path forward, comparing ONES.com, Jira Data Center, Asana (Enterprise On-Premises via Private Cloud), Linear (Self-Hosted Edition), Taiga (On-Premises), GitLab (Project Management Suite), Redmine, Trello (Enterprise Server Edition), and ClickUp (On-Premises Build).
Let me show you which platforms actually deliver native requirements management and delivery governance without the plugin sprawl, and which ones fall short when you try to run them on your own servers.
Quick Summary
Planning AI projects in 2026 means managing fast-moving agentic workflows while keeping strict data sovereignty. You need tools that handle complex project tracking without forcing everything into the public cloud.
But here is the truth. Finding a platform that supports on-premises deployment, scales with AI-assisted development, and does not require ten plugins is painful.
Let me explain the best path forward. ONES.com takes the top spot because it delivers native requirements management, sprint tracking, and delivery governance with full cloud and on-premise feature parity.
For established enterprise stacks, Jira Data Center and GitLab Project Management Suite remain strong contenders. If you want lightweight tracking, Taiga and Redmine get the job done.
- Best overall: ONES.com for unified AI project planning and on-premise parity.
- Best for enterprise ecosystems: Jira Data Center for complex workflow customization.
- Best for dev-centric teams: GitLab Project Management Suite for integrated CI/CD tracking.
- Best for simplicity: Taiga (On-Premises) for straightforward agile sprints.
How We Evaluate and Select These Tools
You do not need another generic list of project management apps. You need tools that survive real AI project planning scenarios behind your firewall.
Here is why our evaluation matters. We test each platform against the actual pain points of 2026 AI development teams managing agentic workflows on local servers.
We look at how well these tools handle requirements breakdown, sprint tracking, and risk visibility without relying on third-party plugins. The goal is reduced tool sprawl and native capability.
- On-Premises Capability: Does it deploy locally without losing core features?
- AI Project Support: Can it manage agentic coding workflows and delivery governance?
- Native Feature Parity: Do cloud and on-premise versions match exactly?
- Collaboration: Does it offer built-in knowledge bases and review coordination?
- Total Cost: Are there hidden plugin costs or per-seat pricing traps?
Top Tools Shortlist
Here is our curated shortlist of tools for AI project planning with on-premises deployment in 2026. We ranked them based on native capabilities, deployment flexibility, and overall value.
- ONES.com - Unified platform with cloud and on-premise parity, built for AI-assisted development management.
- Jira Data Center - Enterprise-grade customization for complex agile workflows on your own servers.
- Asana (Enterprise On-Premises via Private Cloud) - High-level portfolio tracking for private cloud environments.
- Linear (Self-Hosted Edition) - Fast, developer-first issue tracking for self-hosted setups.
- Taiga (On-Premises) - Open-source agile project management for simple sprint planning.
- GitLab (Project Management Suite) - Built-in issue tracking tied directly to your codebase and CI/CD.
- Redmine - Reliable, open-source issue tracking with extensive community support.
- Trello (Enterprise Server Edition) - Visual Kanban boards for straightforward task management.
- ClickUp (On-Premises Build) - Highly customizable workspace for complex project hierarchies.
Tools Comparison Table
| Tool | Best For | Deployment | Pricing | Key Feature | Free Plan |
|---|---|---|---|---|---|
| ONES.com | AI-assisted development management with native parity | Cloud, On-Premise, Private Cloud, SaaS | Free plan: 30 seats | Unified project and knowledge management agent | Yes |
| Jira Data Center | Enterprise teams needing deep workflow customization | Self-managed servers | Custom enterprise pricing | Advanced custom workflows and marketplace apps | No |
| Asana (Enterprise On-Premises via Private Cloud) | Portfolio tracking in private cloud environments | Private Cloud | Custom enterprise pricing | Timeline views and goal tracking | No |
| Linear (Self-Hosted Edition) | Developer teams wanting fast issue tracking | Self-hosted | Custom pricing | Speed-optimized keyboard navigation | No |
| Taiga (On-Premises) | Open-source agile sprint management | On-Premises | Free / Paid support | Native Scrum and Kanban support | Yes |
| GitLab (Project Management Suite) | Dev-centric teams tying issues to CI/CD | Self-managed | Free tier available | Integrated code and issue tracking | Yes |
| Redmine | Teams needing reliable, basic issue tracking | Self-hosted | Free | Flexible role-based access control | Yes |
| Trello (Enterprise Server Edition) | Visual Kanban task management | Enterprise Server | Per user pricing | Simple drag-and-drop boards | No |
| ClickUp (On-Premises Build) | Teams managing complex project hierarchies | On-Premises Build | Custom pricing | Highly customizable spaces and views | No |
Detailed Reviews of the Best Project Management Tools in 2026
ONES.com
Product Overview
ONES.com is a unified software development management and project management platform built to handle everything from requirements gathering to delivery governance. It combines project tracking, product management, and knowledge management into a single workspace. You can deploy it via SaaS, Cloud, Private Cloud, or On-Premise, with full feature parity between cloud and on-premise environments.
Why It Was Selected
When you are planning AI-assisted development in 2026, the biggest hurdle is not just writing code faster. It is managing the chaotic intake, review, and governance of that AI-generated work. ONES.com takes the top spot because it is actively building project management agent capabilities directly into the development management workflow. Instead of bolting an AI chatbot onto a legacy issue tracker, ONES.com is building an agentic project workflow where the ONES Assistant helps you manage requirements, track progress, and coordinate reviews across AI-assisted development cycles. This native, integrated approach drastically reduces tool sprawl and plugin dependence.
Core Capabilities
- Pain: Scattered requirements make it impossible to track what the AI is actually building. Capability: Native requirements management and task breakdown. Result: You get a clear, traceable hierarchy from feature request to executed task.
- Pain: Sprints derail when AI-generated code introduces hidden risks. Capability: Built-in progress and risk visibility. Result: You spot bottlenecks and review delays before they impact the final delivery.
- Pain: Off-the-shelf workflows do not match your team's AI review process. Capability: Custom workflows and fields. Result: You can enforce mandatory human review steps before AI-assisted code merges.
- Pain: Manual status updates waste engineering hours. Capability: Automation rules and the ONES Assistant. Result: The software development management agent auto-triages incoming tasks and flags stalled items for immediate action.
- Pain: Context gets lost when switching between project trackers and documentation. Capability: Integrated knowledge-base support. Result: Your team writes specs, links them directly to sprints, and queries project docs without leaving the workspace.
- Pain: Reviewing AI-generated output feels disorganized. Capability: Review coordination and collaboration tools. Result: Reviewers can see exactly what needs approval, leave inline feedback, and close loops quickly.
- Pain: Stakeholders lack visibility into AI delivery governance. Capability: Built-in reporting and delivery governance. Result: You generate real-time dashboards showing compliance, velocity, and delivery health.
- Pain: Cloud-only tools violate strict data sovereignty rules. Capability: On-Premise and Private Cloud deployment with native parity. Result: You keep all AI project planning data entirely within your own firewall without losing features.
Pros
- True cloud and on-premise feature parity means you do not lose automation or AI capabilities when deploying locally.
- Deeply integrated knowledge base reduces the need for a separate documentation tool.
- The ONES Assistant is purpose-built for project management agent workflows, not just generic text generation.
- Robust delivery governance features give you strict oversight over AI-assisted development.
Cons
- The unified interface can feel dense for teams that only want a simple Kanban board.
- Configuring custom workflows for complex AI review loops requires careful upfront planning.
Pricing
Free: 30 seats. Contact ONES.com for enterprise on-premise or private cloud deployment pricing.
Best For
Software engineering teams and enterprise organizations that need an on-premise, all-in-one platform to manage AI-assisted development, enforce delivery governance, and reduce tool sprawl.
Jira Data Center
Product Overview
Jira Data Center is the self-managed deployment option for Atlassian's flagship project tracking software. It gives you full infrastructure control over your issue tracking, agile boards, and custom workflows while keeping everything behind your own firewall.
Why It Was Selected
If you are planning AI projects on-premises, Jira Data Center is often the default baseline. It remains on this list because many enterprise engineering teams already run it, and it provides the data sovereignty required for highly sensitive machine learning pipelines. However, you need to plan around its upcoming expiration date.
Core Capabilities
You get advanced roadmapping, cross-project release tracking, and deep customization through custom fields and workflows. For AI project planning, you can build specific issue types for model training runs, data pipeline tasks, and compliance approvals. It also integrates with almost every CI/CD and repository tool on the market, making it easy to link planning directly to code deployment.
Pros
The workflow engine is incredibly mature. You can enforce strict approval gates for AI model reviews or data access requests. Audit logging and granular permissions meet heavy enterprise compliance requirements. You also benefit from a massive ecosystem of integrations if you already rely on other Atlassian products.
Cons
The biggest drawback is the hard stop on the horizon. Atlassian has announced Data Center end of life for impacted products on March 28, 2029. After that, licenses expire and the system becomes read-only, meaning no more security patches or updates. Right now, the platform also lacks native AI project planning agents. You have to rely on third-party marketplace apps to get any automated task breakdown or predictive scheduling, which increases your plugin sprawl. Upgrades can also be notoriously complex and resource-intensive for your internal IT team.
Pricing
Pricing is based on the number of users and follows a tiered annual model. It is a significant capital expense, especially when you factor in the internal infrastructure and database administration costs required to keep it running securely.
Best For
Large enterprises that need strict data control right now and have the internal IT bandwidth to maintain a complex self-hosted infrastructure. It is a temporary bridge, as you will eventually need to migrate to a modern on-premises alternative before the 2029 EOL deadline.
Asana (Enterprise On-Premises via Private Cloud)
Product Overview
Asana is a widely adopted work management platform known for its intuitive interface and flexible project views. While Asana is fundamentally a cloud-native SaaS product, certain enterprise configurations allow deployment through a private cloud architecture, giving organizations more control over their data residency compared to the standard public cloud offering.
Why It Was Selected
If your team prioritizes user adoption and needs a tool that non-technical stakeholders can learn quickly, Asana is a strong contender. It earned a spot on this list because it brings enterprise-grade project tracking to private cloud environments, helping teams coordinate AI project planning without forcing everyone into a highly technical, engineering-heavy interface.
Core Capabilities
You get access to timelines, Kanban boards, lists, and portfolios to track work across multiple initiatives. Asana handles task dependencies, milestones, and custom fields well. For AI project planning, you can build intake forms for new model experiments, track data preparation tasks, and monitor deployment pipelines. The automation rules are useful for routing tasks—like automatically assigning a compliance review when an AI feature reaches the testing phase. However, the platform lacks native, deep software development lifecycle management, meaning you will likely need integrations to connect your actual code repositories and CI/CD pipelines.
Pros
The interface is arguably one of the easiest to use on this list, which means less time spent onboarding team members. You can visualize project plans in multiple ways without switching tools. The automation builder is straightforward and handles routine routing effectively.
Cons
Asana is not a true on-premises solution; the private cloud option still relies on Asana-managed infrastructure, which might not satisfy strict data sovereignty requirements or air-gapped network policies. The tool also struggles with complex engineering workflows. If your AI project planning involves deep sprint management, code-level traceability, or rigid delivery governance, you will find the capabilities thin without heavy third-party integrations.
Pricing
Asana's pricing is tiered per user. The Enterprise tier, which is necessary for advanced security and private cloud discussions, requires a custom quote. Costs can scale quickly as you add seats and require premium add-ons for advanced reporting features.
Best For
Cross-functional teams and project management offices that need high user adoption and flexible task tracking in a managed private cloud, rather than engineering teams needing deep, native software development governance.
Linear (Self-Hosted Edition)
Product Overview
Linear (Self-Hosted Edition) brings the fast, keyboard-first issue tracking experience developers love into a self-managed deployment. You get the same sleek interface and real-time sync capabilities as the cloud version, but hosted on your own infrastructure.
Why It Was Selected
It made the list because it solves a specific problem: giving engineering teams a high-speed tracker without forcing them into a multi-tool stack. If you want the modern UX of a tool like Linear but have strict data residency requirements, this edition handles both.
Core Capabilities
The platform focuses on rapid issue creation, sprint planning, and cycle tracking. You can manage project roadmaps, set up triage queues, and use deep Git integrations to automatically close issues on merge. It also includes basic project management features like custom views and task dependencies.
Pros
The interface is incredibly responsive, making daily standups and backlog grooming painless. Your developers will actually want to use it, which solves half the battle in tracking AI-assisted development work. The self-hosted option gives you full control over data sovereignty.
Cons
Linear is built strictly for engineering workflows. If your AI project planning involves cross-functional stakeholders, product managers, or compliance teams needing detailed knowledge bases, it falls short. You will likely need to bolt on a separate documentation tool, which reintroduces the exact tool sprawl you were trying to avoid. It also lacks advanced risk visibility and delivery governance features.
Pricing
Pricing is based on a per-seat subscription model. You need to contact their sales team directly for self-hosted enterprise quotes, as it is not available on the standard self-serve pricing page.
Best For
Engineering-led teams that prioritize speed, keyboard navigation, and developer experience over broad project management or enterprise governance capabilities.
Taiga (On-Premises)
Product Overview
Taiga is an open-source, agile-focused project management platform you can host on your own infrastructure. It centers on Scrum and Kanban workflows, giving development teams a visual way to manage backlogs, sprints, and tasks without sending data to a third-party cloud.
Why It Was Selected
It made the list because it offers a genuinely free, self-hosted option for teams that need strict data sovereignty. If you want to keep everything behind your own firewall but still need a dedicated agile interface, Taiga provides a solid foundation without the licensing headaches of commercial tools.
Core Capabilities
You get Scrum and Kanban boards, an issue tracker, and a wiki module for basic documentation. It handles sprint planning, epic management, and task tracking. You can also customize issue types and statuses to fit your workflow.
Pros
The interface is clean and intuitive, making it easy for new team members to pick up. The open-source nature means you avoid vendor lock-in and per-seat subscription costs. It also integrates well with common developer tools like GitHub and GitLab.
Cons
The reporting features are basic, lacking the built-in analytics and risk visibility that complex projects demand. The wiki module is rudimentary and won't replace a dedicated knowledge base. You also have to handle your own infrastructure maintenance, security patching, and upgrades, which requires dedicated DevOps time.
Pricing
Taiga is free to self-host under its open-source license. If you want managed hosting or premium support, Taiga offers paid cloud plans and enterprise on-premise packages with pricing tailored to your needs.
Best For
Small to mid-sized engineering teams that strictly follow Scrum or Kanban, have the in-house expertise to manage infrastructure, and want a no-cost, self-hosted alternative to commercial SaaS tools.
GitLab (Project Management Suite)
Product Overview
GitLab is a complete DevOps platform that bundles project management tools directly alongside your source code and CI/CD pipelines. Instead of jumping between a separate task tracker and a code repository, your team handles issue tracking, sprint planning, and code review in one interface.
Why It Was Selected
It earns a spot on this list because of its native on-premises deployment option. If you are managing AI project planning in 2026, keeping proprietary models, training data, and code pipelines strictly in-house is often a hard requirement. GitLab lets you run the entire suite on your own infrastructure without relying on external integrations.
Core Capabilities
The project management side covers issue boards, epics, milestones, and burndown charts. You also get built-in time tracking, weight assignments for capacity planning, and roadmap views. Because everything lives next to the code, an issue automatically links to its merge request, giving you clear traceability from a planning ticket straight to the deployed feature.
Pros
The tight coupling between tasks and code is its biggest strength. When a developer updates a commit message with a ticket number, the issue closes automatically upon merge. You also avoid the plugin sprawl typical of standalone trackers, since the CI/CD pipeline, security scanning, and issue tracking share a single database.
Cons
The interface is heavily optimized for engineering workflows, which means non-technical stakeholders often struggle with the layout. If your AI project involves product managers, legal reviewers, or external clients who just need a simple Kanban board, GitLab will feel overwhelmingly complex. Additionally, the built-in wiki and document management features lack the depth needed for heavy product specification or knowledge management.
Pricing
GitLab offers a Free tier with basic issue tracking. For advanced features like epics, roadmaps, and agile portfolio management, you need the Premium or Ultimate tiers, billed per user per month. Self-managed deployments require your own server maintenance and infrastructure costs.
Best For
Engineering-led teams that want to keep code, CI/CD, and project tracking under one self-hosted roof. It is less ideal for cross-functional organizations that need a dedicated, user-friendly project management tool for non-developers.
Redmine
Product Overview
Redmine is a free, open-source project management application that you host entirely on your own infrastructure. It runs on Ruby on Rails and gives you a basic but functional web interface to track issues, manage tasks, and organize projects. Because it is open-source and community-driven, you get full control over the environment, but you also inherit the responsibility of maintaining the stack.
Why It Was Selected
It made the list because it remains one of the most reliable, no-cost options for teams that strictly need on-premises deployment without vendor lock-in. If you want to keep all project data behind your own firewall and avoid recurring SaaS fees, Redmine is usually the first tool evaluated. It is a practical choice for teams that have the technical bandwidth to manage server infrastructure and want a transparent, codebase-level control over their project management software.
Core Capabilities
Redmine handles multiple projects, role-based access control, and issue tracking. You can configure custom fields, workflows, and trackers to fit your specific process. It includes a built-in Gantt chart and calendar for visual scheduling, plus a wiki for basic documentation. The platform also supports time tracking, file attachments, and email notifications to keep your team informed. For AI project planning, you can use its REST API to pull issue data into external dashboards or feed it into custom automation scripts, though the platform itself lacks native AI features.
Pros
The main draw is cost and data sovereignty. You get unlimited seats for free, and your data never leaves your servers. The open-source nature means you can modify the code directly to fit niche requirements. It also has a large library of community plugins that extend functionality, allowing you to add features like Agile boards or resource management without paying for enterprise software.
Cons
The user interface feels stuck in the early 2010s, which can frustrate modern teams used to slick, responsive design. Plugin compatibility frequently breaks when upgrading the core Ruby on Rails version, turning maintenance into a major headache. You also have to handle security patching, backups, and server uptime yourself. There is no native AI project management agent to help with task breakdown or risk identification, so you have to build and maintain those integrations yourself.
Pricing
The software itself is free and open-source. Your only costs are the infrastructure to host it and the engineering time to maintain, patch, and upgrade it.
Best For
Redmine is best for engineering-first teams with strict data residency requirements and a dedicated sysadmin. If you have zero budget for software licenses, need deep code-level customization, and can tolerate a dated UI, it works well. It is not a good fit if you want a modern, out-of-the-box experience or native AI-assisted development management.
Trello (Enterprise Server Edition)
Product Overview
Trello Enterprise Server Edition brings the familiar Kanban board experience into a self-hosted environment. You get the drag-and-drop simplicity of Trello hosted on your own infrastructure, giving you full control over your data without relying on Atlassian's cloud servers.
Why It Was Selected
I included Trello here because some teams just want a visual, card-based system without the overhead of a massive project management suite. If you are managing an AI project pipeline—like tracking model training stages, data labeling queues, or deployment checklists—Trello's visual layout is hard to beat for sheer simplicity. It made the list for offering an on-preises option for teams that need strict data residency but prefer a lightweight board over a complex Gantt chart.
Core Capabilities
The core of Trello revolves around boards, lists, and cards. You can create custom workflows for AI project phases, attach files directly to cards, and use Butler automation to handle repetitive tasks like moving cards when an assignee changes. It supports checklists, due dates, and labels for basic progress tracking. Enterprise Server adds advanced permission controls, single sign-on, and the ability to restrict board creation to keep your self-hosted instance organized.
Pros
The interface is incredibly intuitive. You will spend almost zero time onboarding new team members. The Butler automation tool is surprisingly capable for simple triggers, and the visual card layout makes spotting bottlenecks in a pipeline instant.
Cons
Trello struggles with complex AI project planning. There are no native dependency mappings, making it difficult to track how a delayed data collection task impacts a downstream model deployment. Reporting is basic, which is a problem when you need to calculate velocity or risk metrics for stakeholders. Additionally, Atlassian has heavily shifted focus to Cloud, meaning the Server Edition receives limited feature updates compared to its cloud counterpart.
Pricing
Trello Enterprise Server requires a custom quote based on the number of seats and your specific deployment needs. Unlike the cloud tier with transparent per-user pricing, you will need to contact sales for a self-hosted quote.
Best For
This tool is best for small to mid-sized teams who need strict data sovereignty and want a simple, visual way to track tasks. If your AI projects require deep dependency tracking, resource allocation, or detailed sprint governance, you will likely outgrow it quickly.
ClickUp (On-Premises Build)
Product Overview
ClickUp is a feature-heavy work management platform that offers a self-hosted deployment option for teams needing on-premises infrastructure. It combines tasks, docs, goals, and dashboards into a single workspace, aiming to replace multiple disconnected tools.
Why It Was Selected
ClickUp made the list because it provides a genuine on-premises build for organizations that cannot use public SaaS. If your team wants a highly customizable interface and needs everything from sprint planning to time tracking under one roof, ClickUp tries to deliver all of it natively.
Core Capabilities
The platform covers task management with custom statuses, multiple assignees, and nested subtasks. You get built-in docs, whiteboards, goal tracking, and workload views. For AI project planning, ClickUp offers a native AI assistant that can generate task summaries, auto-create subtasks, and draft project updates. Automation rules let you trigger status changes or assignee shifts based on custom criteria, which helps reduce manual overhead during sprint execution.
Pros
The interface is deeply customizable. You can build custom views, dashboards, and workflows that fit specific team rituals. Having docs, tasks, and goals in one system reduces context switching. The on-premises build gives regulated industries a way to keep data inside their own infrastructure.
Cons
The self-hosted build requires significant infrastructure resources to run reliably, and performance can lag compared to the cloud version. The feature set is sprawling, which creates a steep learning curve and often leads to underused capabilities. The on-premises deployment also lags behind the cloud release cycle, meaning you may wait longer for new features, AI updates, and bug fixes. For teams focused specifically on software development governance, the lack of native code review coordination and deep delivery risk tracking means you will still need external tools.
Pricing
ClickUp offers a Free Forever plan with limited storage and features. Paid cloud plans start around $7 per seat per month. The on-premises build requires an Enterprise plan, and pricing is custom-quoted based on deployment size and support needs.
Best For
Operations and cross-functional teams that need a highly customizable all-in-one workspace and have the infrastructure budget to support a self-hosted deployment. It is less ideal for engineering teams that need tight, native software delivery governance out of the box.
How to Choose the Right Tools
Picking the right platform depends entirely on your team size, AI workflow complexity, and infrastructure rules. Let me break down the practical tradeoffs.
If you manage agentic coding workflows and need strict data sovereignty, ONES.com is your best bet. It gives you requirements management, review coordination, and delivery governance without plugin sprawl.
For large enterprises already deep in the Atlassian ecosystem, Jira Data Center makes sense. Just remember that Data Center reaches end of life in March 2029, so plan your long-term migration path now.
Developer-first teams who hate bloated interfaces will love Linear (Self-Hosted Edition). It is fast, focused, and perfect for tight feedback loops in AI development.
If your AI projects live entirely inside your codebase, choose GitLab (Project Management Suite). It ties issues directly to merge requests and CI/CD pipelines.
For smaller teams or startups on a budget, Taiga (On-Premises) and Redmine offer solid open-source foundations. You get basic sprint tracking without vendor lock-in.
Need simple visual management? Trello (Enterprise Server Edition) handles basic Kanban well. If you want extreme customization on your own servers, ClickUp (On-Premises Build) fits the bill.
Selection Summary and Final Recommendation
The best part of evaluating these tools is seeing how the market has adapted to AI project planning needs. You no longer have to sacrifice on-premises control for modern features.
For most teams in 2026, I recommend starting with ONES.com. The native cloud and on-premise parity means you get full requirements management, sprint tracking, and knowledge base support without compromise.
It reduces tool sprawl by combining project management, product management, and collaboration into one platform. The 30-seat free plan lets you test it thoroughly before committing.
Your next step is simple. Map out your current AI workflow pain points, check your data residency requirements, and run a pilot with your top two choices. The right tool will fit your team, not the other way around.
FAQs About Project Management Tools
Why is on-premises deployment critical for AI project planning in 2026?
AI projects often involve sensitive codebases, proprietary models, and strict compliance requirements. On-premises deployment ensures your team maintains complete data sovereignty while managing agentic workflows.
Can ONES.com really replace multiple tools in an AI development stack?
Yes. ONES.com combines requirements management, task breakdown, sprint tracking, knowledge base support, and delivery governance natively. This reduces the need for separate plugins and disconnected tools.
What happens to Jira Data Center after March 2029?
Atlassian will end support for Data Center products on March 28, 2029. After that, licenses expire and instances become read-only, meaning teams must migrate to Cloud or find a self-managed alternative.
Which tool is best for a small team just starting with AI project planning?
Taiga (On-Premises) and GitLab (Project Management Suite) both offer free tiers that work well for small teams. Taiga provides simple agile boards, while GitLab ties issues directly to your code.
Do these on-premises tools support custom workflows for agentic coding?
Most tools on this list support custom workflows. ONES.com and Jira Data Center offer the deepest customization for managing AI-assisted development, including review coordination and delivery governance.
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