Devin-AXIS/iPolloWork

Enterprise-grade, local-first Agent Workbench for people and agent teams. A unified multi-engine workspace for Codex Harness, DeepSeek Harness, and...

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Summary Information

Updated 39 minutes ago
Added to GitGenius on September 11th, 2026
Created on August 25th, 2025
Open Issues & Pull Requests: 81 (+0)
GitHub issues: Enabled
Number of forks: 1,117
Total Stargazers: 5,905 (+3)
Total Subscribers: 638 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 22.6 hours
Mean response time: 2.2 days
90th percentile: 6.3 days
Tracked items: 30

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 87% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Almost all tracked open issues have seen activity in the last three months. Only 14% of issues opened in the past year have been closed.

Charts & Analytics

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Issue Activity (beta)

Open issues: 62
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 44 days
Stale 30+ days: 53
Stale 90+ days: 0

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • bug (14)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

iPolloWork is an enterprise-grade, local-first agent workbench that provides a unified workspace for coordinating multiple AI agent engines and teams.

The tool addresses the fragmentation problem of managing multiple agent frameworks and their extensions across different runtimes. It consolidates Codex Harness, DeepSeek Harness, and OpenCode into a single control surface where teams can coordinate agents, tasks, plugins, and Skills without context switching. Users describe outcomes to the system, agents plan and execute the work, and team members review progress, approve actions, and edit results all within the same interface. The workbench supports creation and editing across code, documents, presentations, websites, design, and video outputs.

Organizations with multi-agent teams or those evaluating different agent frameworks should consider this tool if they want to avoid managing separate workspaces for each engine. It suits enterprises that need a unified plugin and Skills system across heterogeneous agent runtimes, and teams that require human-in-the-loop review and editing capabilities alongside agent execution. The local-first architecture appeals to organizations with data residency or privacy requirements.

The project maintains a substantial base of real-world adopters, with almost all open issues raised by outside users rather than the core team. Maintainers typically respond to new issues and pull requests within a day. Work in the issue tracker is dominated by bug reports, indicating the team prioritizes stability and reliability for its user base.