Effectively Group Agents in Workspaces

Validated on 1 Jul 2025 • Last edited on 8 Jul 2025

GradientAI Platform lets you build fully-managed AI agents with knowledge bases for retrieval-augmented generation, multi-agent routing, guardrails, and more, or use serverless inference to make direct requests to popular foundation models.

Workspaces group related agents together in a single space so you can manage AI agents, share them across your team, and run evaluations to test and compare their performance in a structured way.

For example, you can create a workspace for your customer support agents, another for your marketing agents, and a third for your sales agents. This allows you to manage each group of agents separately, and run specific test cases to evaluate their performance based on the unique requirements of each group.

All agents in GradientAI Platform exist in a workspace. You can assign agents to an existing workspace during creation or create an agent directly in a workspace, and you can move agents between workspaces at any time.

Note
Agents created 1 July 2025 (when workspaces became available) have been automatically moved into a default workspace named “My Agent Workspace (Created by Default)”.

Effectively Grouping Agents in Workspaces

You can group agents in workspaces for a variety of reasons, such as:

  • Purpose: Where agents are grouped by their intended use or business goal. For example, you might have an agent workspace for sales agents that handle customer inquiries and another for support agents that assist with technical issues.
  • Development stage: Where agents are grouped by their development stage, such as testing, staging, and production. This allows you to manage agents at different stages of their lifecycle and run evaluations to test their performance before deploying them to production.
  • Side-by-side comparisons: Where agents are grouped to compare their performance against each other. For example, you might have a workspace for two different sales agents that use different foundation models or knowledge bases, allowing you to run evaluations to see which set of agents performs better in specific scenarios.
  • Team collaboration: Where agents are grouped by the team that manages them. This allows teams to share agents, collaborate on evaluations, and manage their agents in a structured way.

Effectively grouping your agents in a workspace and running evaluations on them can help you identify areas for improvement, optimize their performance, and ensure they meet your business goals.

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