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Synchronize your AI agents for seamless multi-agent orchestration

Swiftask integrates with agentOS to orchestrate your AI agents. Enable specialized tools to collaborate and handle complex workflows end-to-end.

Result:

Boost operational efficiency by breaking down silos between your AI agents.

The growing complexity of your AI deployments

Scaling AI agents without an orchestration platform creates silos. Each agent works in isolation, data doesn't flow, and maintenance becomes a nightmare for your technical teams.

Main negative impacts:

  • Inefficient data silos: Your agents do not share information, preventing the resolution of cross-functional workflows.
  • Maintenance overhead: Managing each agent individually exponentially increases technical debt and configuration time.
  • Lack of decision consistency: Without central orchestration, agents may make conflicting decisions impacting your operations.

Swiftask and agentOS provide a unified orchestration layer. Define workflows where your agents collaborate, share context, and handle complex business processes.

BEFORE / AFTER

What changes with Swiftask

Isolated agent management

Your AI agents function as islands. For a simple task, you must manually transfer data from Agent A to Agent B. The process is slow, error-prone, and impossible to scale.

Orchestration with agentOS

Your agents are connected in a coherent ecosystem. The output of Agent A automatically becomes the input of Agent B. Orchestration handles dependencies, logic, and exceptions without human intervention.

Deploying your multi-agent ecosystem

STEP 1 : Centralize your agents in agentOS

Import your existing AI agents into the agentOS environment for unified management.

STEP 2 : Connect agentOS to Swiftask

Use the Swiftask connector to steer orchestration through our business-ready interface.

STEP 3 : Define orchestration rules

Configure triggers and sequences of collaboration between your specialized agents.

STEP 4 : Monitor global performance

Analyze the effectiveness of your multi-agent workflows from the Swiftask dashboard.

Advanced orchestration capabilities

The orchestrator analyzes load, agent specialization, and request priority to optimize task routing.

  • Target connector: The agent performs the right actions in agentos based on event context.
  • Automated actions: Dependency management between agents. Semantic context sharing. Intelligent task routing. Error handling and feedback loops. Centralized performance monitoring.
  • Native governance: All orchestration benefits from the governance and audit trail of the Swiftask platform.

Each action is contextualized and executed automatically at the right time.

Each Swiftask agent uses a dedicated identity (e.g. agent-agentos@swiftask.ai ). You keep full visibility on every action and every sent message.

Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.

Why adopt multi-agent orchestration

1. Increased scalability

Add new agents to your ecosystem without complicating your architecture.

2. Resource optimization

Intelligent routing ensures the right task is handled by the right agent.

3. Process consistency

Standardize data exchanges between your different AI modules.

4. Business agility

Modify your workflows in a few clicks without rewriting agent code.

5. Full visibility

Track the complete lifecycle of a request across multiple agents.

Security and governance

Swiftask applies enterprise-grade security standards for your agentos automations.

  • Data isolation: Each agent accesses only the data necessary for its function.
  • Access management: Finely control interaction permissions between agents via agentOS.
  • Full traceability: Detailed logging of every interaction between agents for auditing.
  • Enterprise compliance: Architecture designed to meet the most demanding security standards.

To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.

RESULTS

Impact on your productivity

MetricBeforeAfter
Workflow processing timeSeveral hours (manual)A few seconds (orchestrated)
Error managementDelayed human detectionAutomated real-time handling
Maintenance costHigh (custom development)Low (no-code configuration)

Take action with agentos

Boost operational efficiency by breaking down silos between your AI agents.

Configure your services in real-time with the power of agentOS

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