Organize and track projects, set deadlines, and gain insights with customizable boards and advanced analytics.
Epismo
$4Starting price
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About Epismo
Epismo is a workflow platform where teams create, share, and execute structured AI workflows. Users define goals and tasks, assign them to AI agents or human team members, and monitor progress through a shared project board that keeps both humans and AI aligned. The platform supports repeatable workflows, enabling teams to automate routine processes while maintaining oversight and collaboration. Epismo offers a public marketplace for sharing proven workflows, allowing users to adopt or adapt templates created by others. The free plan provides core features, though credit limits apply, and the platform requires initial setup time to define workflows before use. It is designed for project managers, operations teams, entrepreneurs, and business analysts who need to coordinate tasks between AI systems and people. The tool emphasizes structured checklists and progress tracking to ensure clarity and accountability across projects.
Key features
- Create and share structured AI workflows
- Assign tasks to AI agents or team members
- Track progress via a shared project board
- Public marketplace for sharing workflow templates
- Free plan with core features available
- Credit limits on the free tier
- Structured checklists for task tracking
- Supports repeatable AI-assisted project workflows
Use cases
- Building repeatable AI-assisted project workflows
- Coordinating tasks between AI agents and team members
- Sharing proven workflows through a public marketplace
Pros
- Enables creation and sharing of versioned playbooks for consistent execution by teams and AI agents
- Supports structured decision-making workflows with evidence gathering and actionable outcomes
- Provides multiple installation routes including CLI, MCP, and native binaries for flexibility
- Facilitates collaboration through a public marketplace for sharing and adopting workflow templates
- Emphasizes private intermediate work and concise handoffs to maintain clarity and accountability
Cons
- Requires initial setup time to define and publish playbooks before use
- Not suitable for simple tasks like bulk campaigns or automated email sending
- Execution conventions may limit direct repository file creation unless explicitly requested
- Setup and configuration may involve a learning curve for new users
Frequently asked questions about Epismo
What is Epismo and what does it do?
Epismo is a workflow platform where teams create, share, and execute structured AI workflows called playbooks. Users define goals and tasks, assign them to AI agents or human team members, and monitor progress through a shared project board.
Who is Epismo designed for?
The tool is designed for project managers, operations teams, entrepreneurs, and business analysts who need to coordinate tasks between AI systems and people. It is particularly useful for those who require structured checklists and progress tracking.
How do I get started with Epismo?
Users can get started by installing the Epismo CLI via npm, downloading native binaries, or using the MCP server. After installation, they can log in and begin creating or running playbooks by asking their AI agent or using the provided commands.
What are playbooks in Epismo?
Playbooks are versioned workflows that teams and AI agents follow together. They can be created, published, and reused, ensuring consistent execution of tasks. Playbooks can be built by asking an AI agent or manually defined through the platform.
Does Epismo support integrations with other tools?
Epismo supports integrations through its CLI and MCP server, allowing users to connect with various AI agents and systems. It also provides a public marketplace for sharing and adopting workflow templates created by others.
What are the limitations of Epismo?
Epismo is not intended for support-volume reporting, bulk campaigns, or automated email sending. It emphasizes structured workflows and may require initial setup time to define workflows before use. Intermediate work is kept in runtime-private scratch state unless explicitly exported.
