Comparison
AI4Kanban vs.
Multica
Both products let agents execute tasks. AI4Kanban is a ready-to-use AI project-management system; Multica is a general-purpose multi-agent platform.
People set direction, bring ideas, and make the key calls. Agents discover work, clarify requirements, set priorities, execute tasks, and feed what they learn back into project memory.
You create multiple agents, give each one responsibilities, Skills, and a runtime, then manage assignments, execution, retries, reviews, and team collaboration in one place.
Two products for two different needs
AI4Kanban helps people and AI manage a project together. Multica helps teams create, organize, and run multiple agents.
AI4Kanban
Manages the project
Multica
Runs the agents
What is in each box?
Both are complete on day one, but they are complete at different things. AI4Kanban ships the project management; Multica ships the machinery to run agents.
AI4Kanban
Project management, ready to run
- A working method for people and AI
- A board with the full card lifecycle
- Project memory kept in the repository
Multica
Agent infrastructure, ready to run
- Agent identities, Instructions, and Skills
- Squads, chat, and task queues
- Automation, retries, and run history
What matters most
A marks the stronger fit for that need; a dash marks a trade-off.
A complete project-management workflow for people and AI, ready to use.
A general workspace for multi-agent teams; users define the roles and workflows.
Agents read the project and its memory, then propose, refine, and prioritize work.
Possible with Agents, Skills, and Autopilots, but you configure the behavior yourself.
Uses the code and project record to fill in context, leaving only product trade-offs for people.
No ready-made project-clarification workflow; you add one through Agent Instructions or a Skill.
Project decisions, rejection reasons, and redesign lessons feed directly into future planning.
Skills preserve working methods; comments and run history preserve the execution record.
Can launch Claude Code, Codex, Cursor, OpenCode, DeepSeek Harness, ZCode, or Grok Build on a card and track the full lifecycle from proposal to archive.
Runs multiple agents in parallel, with queues, retries, replay, cost tracking, review gates, and PR and CI links.
Local-first, for individual developers and small teams collaborating through git.
Multi-user workspaces, roles, Squads, comments, permissions, and notifications.
Cards and memory live in the repository; no database, account, or board server.
Uses PostgreSQL, a server, and a local daemon; available hosted or self-hosted.
Apache-2.0, including commercial use, hosting, and embedding.
Source-available; hosted services and commercial embedding are restricted by the Multica License.
They remember different things
Both keep notes between runs. They keep different notes.
Project judgment
Why a decision was made
Why did the board stop proposing idea X?
rejected.md records why it was rejected. Without new evidence, the idea stays out.
Working method
How an agent should work
How should this agent run a security review?
Attach a Skill with the steps, files, and requirements for the review.
What would you need to add in Multica?
You can build a project-manager agent on Multica. Creating the agent is the quick part; four questions are then yours to answer, and to keep answering as the project changes.
You still build
The project-management behavior
Choose for the problem you have
AI4Kanban is focused, complete, and ready to use. Multica is broad and flexible, built to operate multiple agents.
AI4Kanban
Project management out of the box
No need to design a project-manager Agent first. Once installed, people and agents can plan, clarify, and execute through one shared workflow.
Rejected ideas stay rejected
Past decisions shape the next planning cycle and reduce repeated discussion.
Everything lives in git
Cards and memory are readable and diffable, with no separate board service to run.
Multica
Full execution control
Queues, retries, replay, reviews, cost tracking, and PR and CI links are all built in.
Built for people and multiple agents
Workspaces, roles, Squads, comments, permissions, and notifications live in one platform.
Broader runtime support
A local daemon connects many agent CLIs. AI4Kanban currently supports Claude Code, Codex, Cursor, OpenCode, DeepSeek Harness, ZCode, and Grok Build.
Which should you choose?
Choose AI4Kanban if you
- Want a ready-made way for people and AI to manage a project together.
- Need agents across planning, clarification, and execution.
- Want project decisions and rejection reasons to shape future planning.
- Prefer a lightweight, repository-native system with no extra service.
Choose Multica if you
- Need to create and operate several agents with different roles.
- Need a shared workspace, issues, and run history for people and agents.
- Need retries, replay, cost tracking, or PR and CI integrations.
- Are prepared to define your own project-management Agent, Skills, and workflows.
Choose AI4Kanban for a ready-to-use AI project-management system. Choose Multica for a general platform to build and operate a multi-agent team. Both use agents to execute tasks; one is for project management, the other for multi-agent operations.