OrlojHQ

OrlojHQ / orloj

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An orchestration runtime for multi-agent AI systems. Declare agents, tools, and policies as YAML; Orloj schedules, executes, routes, and governs them for production-grade operation.

orloj.dev agent-framework agentic-ai agentic-orchestration ai ai-gents
40
0
100% credibility
Found Mar 27, 2026 at 40 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
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AI Summary

Orloj orchestrates multi-agent AI workflows declared in YAML files, providing scheduling, execution, governance, and a web console for monitoring production runs.

How It Works

1
🔍 Discover Orloj

You hear about Orloj, a friendly tool that coordinates teams of AI helpers to tackle complex tasks automatically.

2
📥 Get started quickly

Download the simple app for your computer and launch your own AI coordinator with one easy command.

3
🖥️ Open the dashboard

Visit the built-in web page to see a welcoming control center where everything is easy to manage.

4
📋 Load a sample workflow

Choose a ready example like a research pipeline, and apply it to see AI agents spring into action.

5
👀 Watch the magic

Follow along live as your AI team plans, researches, and delivers results right in the dashboard.

✅ Enjoy smart outcomes

Receive polished reports or decisions from your AI crew, ready to use, with full details on what happened.

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Star Growth

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AI-Generated Review

What is orloj?

Orloj is a Go orchestration runtime for multi-agent AI systems on GitHub, bringing container orchestration github-style reliability to agent workflows. You declare agents, tools, policies, and graphs in YAML manifests, then use the CLI (`orlojctl apply -f`) to deploy; it schedules tasks via DAGs, routes to models like OpenAI or Anthropic, isolates tools in containers or WASM, and enforces governance. A built-in web console shows live traces, metrics, and topology views for runtime orchestration status.

Why is it gaining traction?

Unlike ad-hoc scripts or basic workflow orchestration github tools, Orloj delivers production features like lease-based task claims, exponential retries, dead-letter queues, and role-based permissions out of the box—no vendor lock-in for ai agent orchestration github or claude code orchestration github setups. The declarative YAML + CLI mirrors Kubernetes, with Docker Compose for quick Postgres/NATS scaling and examples for pipelines, loops, and swarms. Devs love the observability and security without custom plumbing.

Who should use this?

AI engineers building multi agent orchestration github pipelines for research, incident response, or chat swarms; DevOps teams governing tool access in shared agent fleets; backend devs needing workflow orchestration github for scheduled tasks or webhooks without LangChain bloat.

Verdict

Grab it for agent orchestration github copilot-style experiments—solid docs, CLI, and UI make it dev-friendly despite 40 stars and pre-1.0 flux (APIs may shift). 1.0% credibility score flags early maturity, but tests and examples signal promise; monitor releases before prod.

(198 words)

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