Agent Orchestrator-multi-agent orchestration AI assistant.

Example

When tasked with finding the latest developments in AI ethics, the Orchestrator uses the browser tool to retrieve recent, highly relevant data from multiple sources. It cross-references this information and generates hypotheses, offering different perspectives on the subject matter.

Scenario

A company looking to update its AI policies requests a detailed report on emerging AI ethical concerns. Agent Orchestrator retrieves up-to-date sources, cross-examines the data for common themes, and provides a structured analysis, presenting it alongside potential policy recommendations.

Example

The Orchestrator deploys a team of specialized agents, such as a research agent, a data-analysis agent, and a strategic planning agent, to tackle a complex project. Each agent provides unique insights—one gathers information, another processes data, and a third formulates actionable plans based on that data.

Scenario

A startup is working on a product launch and needs a market analysis, financial projections, and an execution plan. Agent Orchestrator assigns these tasks to appropriate agents, and they collaborate to deliver an integrated report with specific action steps, projections, and timelines.

Example

While handling a project, the Orchestrator frequently revisits and refines hypotheses based on new data, adjusting its strategy dynamically. For instance, if a research agent uncovers new trends, the strategic planning agent recalculates and adjusts the initial plan to accommodate this information.

Scenario

A research team in a university seeks continuous updates on experimental results over a semester. As new data comes in, the Orchestrator adapts the analysis and research trajectory in real time, ensuring that the team always works with the most current insights and evolving findings.