Visual pipeline builder
Arrange agents in sequence or branches with a clear canvas. Name each step, set inputs, and preview how work flows from trigger to completion.
Chain Agents Into Automated Workflows
One agent researches. Another writes. A third publishes. All automated.
Example pipeline flow
Research Agent
Writer Agent
Editor Agent
Publisher Agent
Key capabilities
Step-by-step monitoring
See which step is running, what finished, and where a run stalled. Timestamps and status chips make handoffs between agents easy to audit.
Shared context between agents
Outputs from earlier steps become structured inputs for the next - no copy-paste. Context stays versioned so teams can reproduce results.
Per-step token tracking
Attribute spend to each step and model choice. Finance sees fair allocation; builders see which stages dominate cost before optimizing.
Error handling and retries
Transient failures backoff and retry with limits. When a step truly fails, the run surfaces the error clearly so you can fix upstream data or prompts.
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Multi-agent pipeline builder - steps and connections
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Pipeline run monitoring - per-step status and timing
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Frequently asked questions
- What is multi-agent orchestration?
- Multi-agent orchestration chains specialized AI agents into an end-to-end workflow — for example research → draft → review → publish. Each agent has its own role, model, and tools, and the next agent receives the previous agent's output. AgentWorks runs these as named pipelines you can trigger manually or on a schedule.
- How do AgentWorks multi-agent pipelines work?
- You compose a pipeline by adding agent steps in order. Each step picks its own LLM (GPT, Claude, Gemini, Mistral), its own knowledge base, and its own tools. Outputs flow into the next step. Pipelines run inside the same workspace as chats and tasks, so the result stream and audit log are unified.
- Can I schedule multi-agent workflows?
- Yes — on Pro and higher tiers. Schedule pipelines to run daily, weekly, monthly, or at a custom time. Each scheduled run debits the workspace euro wallet with full per-step token transparency.
- What's the difference between an AI agent and a multi-agent pipeline?
- A single AI agent is one model + one set of tools doing one task (e.g. "draft a sales email"). A multi-agent pipeline is multiple agents stitched into a single workflow, where each step refines or extends the previous one — closer to how a human team operates.
- Are multi-agent pipelines EU AI Act compliant?
- AgentWorks is EU AI Act-ready, not blanket "compliant" — the risk class depends on your use case. Every step in the pipeline inherits the same EU AI Act controls: per-step risk classification, PII redaction at the gateway, a complete audit log of every model call, and human-in-the-loop approval where required.
Explore More Features
See how other platform capabilities work together.
Last updated: March 2026