An autonomous AI agent platform: you give an agent a goal in plain English and it plans, uses real tools, and delivers the finished work.

Is there a free plan?

Yes. Actus has a free plan to get started, with paid plans that add higher limits and advanced features like scheduled automations and team workspaces.

Can agents run automatically on a schedule?

Yes — agents can run hourly, daily, or on a custom cadence, so routine work happens automatically without you starting it each time.

How is Actus different from a chatbot?

A chatbot replies with text. An Actus agent takes action: it uses real tools to research, write, build, and send, then returns a finished deliverable instead of just advice.

Do I need to know how to code?

No. You describe your goal in plain English and the agent plans and executes the steps. Agents can write and run code when a task needs it, but you never have to.

Do I stay in control of what an agent does?

Yes. Irreversible actions require your approval, every run has budget and step limits, and each step is logged so you can see exactly what happened.

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Multi-Agent Systems for Business Workflows

Actus · October 5, 2026

multi-agent systemsAI workflowbusiness automationagent coordination

Multi-Agent Systems for Business Workflows

A multi-agent system divides work among specialized agents that each handle one clear responsibility. Instead of asking a single agent to research, qualify, draft, send, and follow up, the work is split across focused agents with hand-offs at natural boundaries.

Why Specialize

A single large prompt becomes fragile. It attempts every task, handles exceptions poorly, and is difficult to improve. Specialization allows each agent to do one job well. A research agent gathers evidence. A qualification agent scores fit. A drafting agent writes personalized messages. A sending agent logs outcomes and manages failures.

The Coordinator Pattern

A coordinator agent receives the job, decides which specialists are needed, passes context to each one, and assembles the results. This is cleaner than a long chain where each agent calls the next. The coordinator controls sequence, error handling, and approval gates.

Design Each Agent

Define its input, output, decision rules, and success criteria. Keep the responsibility narrow. A drafting agent should not make qualification decisions. A research agent should not send messages. Clear boundaries reduce errors and make the workflow easier to fix.

Hand-Offs

Pass structured data, not prose summaries. Include source links, confidence scores, and required next fields. Log each step so failures can be traced to the right agent.

Approval Gates

Insert human review between agents when the decision is commercial, the output is public, or the evidence is unclear. Automation should prepare; people should approve.

Example Workflow

A lead generation workflow might use five agents:

Prospector: finds businesses that match the target market
Enrichment: gathers website, contact, and public details
Qualifier: scores fit and need based on evidence
Auditor: inspects website and prepares recommendations
Drafter: writes personalized outreach

A coordinator receives the request, runs each agent in sequence, and presents the qualified leads with draft messages for approval.

Failure Handling

One agent can fail without breaking the entire workflow. A missing website means the auditor cannot run, but the enrichment and qualification steps can still succeed. Log the failure, mark the record incomplete, and continue.

Iteration

Start with two agents. Prove the hand-off works. Add specialists as the workflow grows. Do not build five agents before testing whether one works.

Conclusion

Multi-agent systems create leverage by dividing complex workflows into reliable, testable steps. Actus Agent connects specialized agents, hand-offs, approval gates, and operational steps into one platform. Learn more at https://actusagent.cc.