Agent Orchestrator
Multi-Agent Workflows in Markdown
Define multi-step AI agent workflows in a simple markdown DSL. The compiler converts them into deterministic execution plans, then the orchestration engine runs each step with the right model, tools, and context. Approval gates, fan-out loops, scheduled runs, and live progress tracking in the console.
What it does
Agent Orchestrator lets you define complex multi-agent workflows using a simple markdown format. You write steps in natural language, assign AI models and tools to each step, and the orchestrator handles compilation, validation, execution, and monitoring. Workflows run on an in-process runner on your own appliance, with a separate agent invocation for each step.
Each workflow step is an independent AI agent call. Steps run in dependency order, reference outputs from earlier steps, fan out over collections with parallel branches, and can pause for human approval. The orchestrator compiles your markdown into a deterministic JSON execution plan, validates it, then executes it step-by-step with full observability.
See It In Action
How It Works
Markdown Workflow DSL
Write workflows the way you think about them — in natural language with simple markdown formatting.
YAML frontmatter configures agents, models, and inputs. Each ## Step heading
becomes a workflow step with its own model, prompt, and dependencies. No JSON, no YAML graphs, no proprietary DSL.
Workflow Copilot
New
Describe what you want in plain English and the AI copilot generates the workflow markdown for you.
It knows your connected MCP servers and automatically adds the right
Tools: directives.
Chat back and forth to refine steps, add approval gates, change models, or restructure the workflow —
each response updates the editor in real time.
Console Dashboard
Manage workflows from the console with a full-featured editor featuring syntax highlighting, model autocomplete, and live validation. The built-in AI copilot helps you write workflows conversationally. Browse example templates, run workflows with custom inputs, and monitor executions with real-time step-by-step progress tracking.
Native MCP Tool Access
New
Every MCP server connected to your gateway is available to your workflow agents. Built-in services like
RAG Engine and Media Storage work out of the box —
plus any server you've added: GitHub, Neon, Supabase, Zapier, and more.
Just add Tools: rag-engine to an agent definition and it can search your knowledge base during execution.
Key Features
Markdown-First
Write workflows in markdown with YAML frontmatter. No proprietary DSL or visual builder required.
Multi-Model Support
Assign different models per step — Haiku for fast tasks, Sonnet for reasoning, Opus for complex analysis. Amazon Nova Lite and Nova Pro are available too. Use logical model names that resolve automatically.
Parallel Fan-Out
Fan out over a collection with for_each: the branches run in parallel, ten at a time by default. Steps themselves run in dependency order.
Approval Gates
Pause execution for human review before critical steps. Approve or reject from the console dashboard.
Real-Time Monitoring
Track execution progress step-by-step. See token usage, model selection, and output for each step as it completes.
Native MCP Tool Access
Agents connect natively to MCP Gateway Pro. Add Tools: rag-engine, github to any agent and it can search your knowledge base, create issues, send messages, and more.
Example Workflow
# Market Research Report ## Inputs - topic: The subject to research (string, required) ## Agents ### Researcher Expert market analyst who gathers data from internal knowledge base and identifies key trends. Model: Sonnet Tools: rag-engine ### Writer Technical report writer who produces clear, structured reports. Model: Sonnet ## Steps ### Research Search the knowledge base for information about {inputs.topic}. Identify key players, trends, and opportunities. ### Write Report Using the research: {steps.research.output} Write a comprehensive market research report with executive summary, key findings, and recommendations.
REST API
The orchestrator has a full REST API for programmatic workflow management and execution.
/workflows Create & compile workflow /workflows/{id}/run Execute with inputs /executions/{id} Status + progress /executions/{id}/steps Per-step results /executions/{id} Stop execution Pricing
Included in the AppXen Platform appliance: from $0.149 per instance-hour or $949 per year on the large instance types ($0.199 or $1,299 on the xlarge types), billed hourly or annually through AWS Marketplace, plus your own AWS usage and Amazon Bedrock tokens, billed by AWS. AppXen does not meter requests, storage or tokens.
Learn moreSpecs
Dashboard
Run Agent Orchestrator in your AWS account
Agent Orchestrator ships inside the AppXen Platform appliance. It runs in your AWS account on your own Amazon Bedrock, billed hourly or annually through AWS Marketplace, plus your own AWS usage.