Your agents write code, research markets, ship releases, and create content. But nobody manages them. Kapow does.
Tasks. Approvals. Memory. Dependencies. Real management for AI agent teams.
Open source. Runs locally. No data leaves your machine.
Your dev agent finished the feature. Your QA agent does not know it exists. Your content agent is writing docs for the old version.
You ask what happened last week. Nobody remembers. Context died with the session.
Three agents are idle. Two are duplicating work. You have no way to see any of it.
AI agents are not the problem. The missing management layer is.
Every human team runs on structure. Tasks get assigned. Work gets reviewed. Progress gets tracked. Priorities shift and everyone knows.
Jira, Linear, Asana, Monday - they all solved this for people.
But AI agents? They get a prompt and a prayer.
Kapow brings real management to AI agent teams. The same structure your human teams already use - tasks, subtasks, approvals, version tracking, dependencies, blockers, dashboards - applied to agents.
Not another framework. Not another prompt library. A workplace.
Five agents handle drafting, SEO, design, and publishing as subtasks under one campaign. You review and approve - they revise and ship. Dependencies keep the sequence tight.
One campaign. Five agents. Zero confusion.
Your invoice agent scans hundreds of documents, flags mismatches, and sets blockers when something needs your call. Reconciliation waits for its dependency, then cross-references and reports.
Auditable from start to finish. Every decision on record.
Research agent pulls firmographic data into the knowledge base. Outreach agent drafts personalized sequences as subtasks, sends on approval, tracks replies, and fires follow-ups on schedule.
From research to reply tracking. Every touchpoint managed.
Competitive reports land as versioned knowledge base documents - tagged and searchable. Due diligence flows through pending approval with revision cycles. Knowledge compounds across cycles.
Every finding referenceable. Nothing starts from scratch.
Dependency graph shows how tasks connect. Nodes pulse when working, dim when done, glow when pending review. See your entire operation at a glance.
Parent tasks break into subtasks. Each version tracked. Approval gates between plan and execution. Complex projects stay organized automatically.
Filter by status, agent, or tag. List view, flow graph, tree hierarchy. Real-time updates. One screen to see everything happening.
Every task version saves to its own folder. Plans, reports, images - organized by task and version. Nothing gets lost. Everything is auditable.
Approve, send feedback, pause, or cancel - all from one screen. Review a plan. Send it back with notes. Re-approve. The whole loop in seconds.
Playwright for browser automation. GitHub for releases. Remotion for video. Gmail, Trello, and more. Plug in what you need.
Tasks flow through five stages automatically
I spent 20 years building products - startups, enterprise software, AI companies. When I started running a team of AI agents for real work, I hit a wall.
The agents were powerful. But nobody had built them a workplace. No task board. No memory. No way to see who was doing what. I needed something to manage the heroes.
Every hero needs a sidekick. Someone who tracks the missions, remembers the details, keeps the team coordinated. Not another hero - a manager.
That is Kapow. The sidekick your AI agents did not know they needed.
Free. Open source. Runs on your machine.
No cloud. No accounts. No data leaves your machine.
