Orloj is an open-source orchestration runtime for multi-agent AI systems. Define agents, tools, policies, and workflows in YAML. Orloj schedules, executes, and governs them.
Same agent ambition. Different operational outcomes once runtime constraints are enforced as policy, not convention.
| Capability | Today | With Orloj |
|---|---|---|
| Tool Boundaries | Agents call tools they should not touch. | Tool permissions enforced at execution time. |
| Cost Controls | Token spend spikes without policy limits. | Per-agent token caps and model allowlists. |
| Failure Handling | Retries and dead-letter handling are hand-rolled. | Lease-based retry, replay, and dead-letter primitives. |
| System Composition | Multi-agent wiring lives in bespoke glue code. | Declarative YAML graphs with fan-out and join gates. |
| Auditability | No end-to-end trace when incidents hit production. | Full task trace and message lifecycle logging. |
TodayAgents call tools they should not touch.
With OrlojTool permissions enforced at execution time.
TodayToken spend spikes without policy limits.
With OrlojPer-agent token caps and model allowlists.
TodayRetries and dead-letter handling are hand-rolled.
With OrlojLease-based retry, replay, and dead-letter primitives.
TodayMulti-agent wiring lives in bespoke glue code.
With OrlojDeclarative YAML graphs with fan-out and join gates.
TodayNo end-to-end trace when incidents hit production.
With OrlojFull task trace and message lifecycle logging.
The platform is designed for teams that need deterministic execution, policy enforcement, and safe operations under real production load.
Version-controlled manifests for agents, tools, models, and workflows. Apply once, diff in PRs, and roll back safely.
Policies and permissions are evaluated inline on every turn and tool call. Unauthorized actions fail closed with traceable outcomes.
Lease-based ownership, bounded retries with jitter, dead-letter handling, fan-out/fan-in orchestration, and cron scheduling.
orlojctl apply -f ./your-system/ reconciles agents, graph, governance, and tasks in a single declarative pass.
apiVersion: orloj.dev/v1
kind: Agent
metadata:
name: research-agent
spec:
model_ref: openai-default
prompt: |
You are a research assistant.
Produce concise, evidence-backed answers.
tools:
- web_search
- vector_db
roles:
- analyst-role
limits:
max_steps: 6
timeout: 30sapiVersion: orloj.dev/v1
kind: AgentSystem
metadata:
name: report-system
spec:
agents:
- planner-agent
- research-agent
- writer-agent
graph:
planner-agent:
next: research-agent
research-agent:
next: writer-agentapiVersion: orloj.dev/v1
kind: AgentPolicy
metadata:
name: cost-and-security-policy
spec:
apply_mode: scoped
target_systems:
- report-system
max_tokens_per_run: 50000
allowed_models:
- gpt-4o
blocked_tools:
- filesystem_deleteCore runtime capabilities exposed as resources and controls your platform team can reason about, review, and operate.
Single process. In-memory storage. Sequential execution. No external dependencies.
orlojd --embedded-worker --storage-backend=memory
Webhook-triggered. Agents pull logs, correlate metrics, check recent deployments. Read-only tool permissions mean investigation agents can look but can't roll back infrastructure.
Pipeline agents check contracts against regulatory requirements. Model whitelists keep sensitive content off unapproved providers. Every finding is traced and auditable.
Researcher, analyst, and editor stages in a hierarchical agent system. The researcher can query CVE databases; only the editor can write to the output. Token budgets enforced per run.
Agents scan infrastructure for stale or exposed secrets using WASM-isolated tools. Metadata-only access patterns let agents audit secrets without reading secret values.
20 templates planned. See the full roadmap → or contribute a template →
brew tap OrlojHQ/orloj brew install orlojctl orlojctl init example-system
curl -sSfL https://raw.githubusercontent.com/OrlojHQ/orloj/main/scripts/install.sh | sh
orlojd --storage-backend=memory --embedded-worker
orlojctl apply -f example-system
Orloj is Apache 2.0. The full runtime is open source: governance, orchestration, scheduling, observability.
Define your agents, enforce your policies, and ship to production.