Is the agent stuff real, or is Jev a chatbot bolted on?

The Scrum side is the product; Jev AI is an opt-in, per-project layer that only makes the small routing calls: picking which agent handles a message from agent descriptions, filling blank task fields, picking an assignee, and branching an automation on a decision.

What happens when Jev is unsure or unavailable?

Auto-fill only applies confident answers and never overwrites a field a person set. Auto-assign leaves the task unassigned and says why in the activity feed. The Jev Condition node in an automation falls through to its Else branch.

Can I point it at something other than TypeSafe?

Yes: bring your own key for TypeSafe by default, or any Jev-compatible provider such as OpenJev, configured under Settings. The key is encrypted at rest and never displayed again, and a project with no key behaves exactly as before.

Will the routing actually pick the right agent?

Unproven: both the agent picker and auto-assign work from descriptions you write, so quality depends on how agents and members are described. No routing accuracy or benchmark figure is published.

What key and configuration does the Jev integration need?

Jev AI is opt-in and per-project from Settings → Jev AI. Bring your own TypeSafe key, or point it at any Jev-compatible provider such as OpenJev. The key is encrypted at rest and never shown again, and a project without a key behaves exactly as before.

Which decisions can Jev make inside a project?

Four: Agent Auto-routing picks the best-fit agent for a chat message from agent descriptions; Task Auto-fill sets blank priority, type, story points, tags, epic, and select fields; Task Auto-assign picks the best member; and a Jev Condition routes an automation branch on a choice, score, or yes/no answer.

What license is Paca under, and can I self-host it?

Apache 2.0 and fully self-hosted, so you own the data and the workflow. The core is lightweight and extendable through configuration and plugins, with backend plugins compiled to WebAssembly and run in a sandboxed, capability-based permission model.

CommunityJev Tools & CLIs

Paca

A Go-based team workspace with optional Jev AI for agent auto-routing, task auto-fill, auto-assign, and automation condition nodes.

See highlights

Open github.com

Stars: 1.9k
Language: Go
License: APACHE-2.0
Published by: Community
Author: Paca-AI
Last verified: Oct 2026

Paca-AI/paca

Organization repository on GitHub

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AI-native, free, open-source alternative to Jira, Trello, ClickUp & Monday. Built for Scrum teams where humans and AI agents collaborate as equals — on the same board, the same sprints, the same goals. Self-hosted. Fully customizable via config and plugins.

Forks: 165
Last pushed: Updated Oct 2026

Repo stats from the GitHub API, cached Oct 2026.Homepage

About this project

AI-native. Free. Lightweight. Open-source. The fully customizable alternative to Jira, Trello, ClickUp, and Monday. Getting Started · MCP Server · Paca Skills · Architecture · Contributing · Roadmap. Paca is a self-hosted project management platform where AI agents and humans collaborate as equal teammates inside a Scrum team — not as chatbots bolted on the side.

Quoted from the project's README. Read the full README.

Tagscommunity go agents routing

Works forJev for Routing Jev for Classification Jev for Scoring

Used inJev for Software & DevTools Jev for HR & Recruiting

Languages: Go
Platforms: API
Capabilities: Open sourceRequires API key

Highlights

Settings encrypt a per-project TypeSafe or OpenJev-compatible key; projects without a key behave as before.
Auto agent picker routes messages from agent descriptions; task auto-fill only applies confident field answers.
Jev Condition automation nodes branch on choice, score, or yes/no with an Else path when Jev is unsure.

Watch out

Bring-your-own-key SaaS-style self-host; routing quality depends on how agents and members are described.

Questions about this entry

Short answers drawn from the linked project or page.

Reactions & coverage

Posts, threads, and videos about this entry from around the web.

Facebook: Intake Router keeps diagnosis out of the answer space at the front desk.

FacebookClinicnotes

YouTube: Jev explained for routing and judging, with a comparison against LLMs.

Hacker News: Vercel on using Jev for defined decisions and GPT-6 Astra when the job also has to write or use tools.

flashbrew4 pointsTypeSafe AI Jev vs. GPT-6 AstraRead the thread on Hacker News

Hacker News: ASTGL replay chose local Laya routing over hosted Jev on one Mac Studio setup.

Jmeg8r15 pointsDoes an open-weight decision model beat a hosted one? Jev vs. LayaRead the thread on Hacker News

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