How to Use ClickUp AI Agents in a Decentralized Workspace

ClickUp offers decentralized AI agents that you can query from your own environment while keeping data secure and under your control. This guide explains how to connect, configure, and use these agents so your team can search, summarize, and act on your workspace content safely.

Understanding ClickUp AI Agents

Before you start, it helps to understand what these agents actually do in a decentralized setup.

What AI agents can access in ClickUp

The AI agents are built to work with multiple data sources inside your workspace. They can access:

• ClickUp tasks and task details
• ClickUp Docs and internal knowledge
• Team communication records linked to your workspace
• Connected tools and workflows, when enabled

The agents analyze these sources to answer questions, draft content, or surface insights while respecting the access controls defined for your domain.

Benefits of a decentralized approach in ClickUp

The decentralized design gives you control over where the AI runs and what it can reach. Key benefits include:

• Queries run from your own environment against your ClickUp data
• Fine-grained access controls based on user groups and domains
• Separation between communication channels and production data
• Support for on-premise or hybrid setups where needed

This approach makes it easier to adopt AI while preserving security and governance around your workspace information.

Preparing Your Environment for ClickUp AI Agents

To use decentralized agents effectively, you should first prepare your environment and policies.

Define access policies for ClickUp data

Start by mapping who should be able to query which parts of your workspace. Consider:

• Departments or teams (marketing, engineering, support)
• Projects or spaces that contain sensitive tasks
• Docs that should only be used by certain roles
• Tools or integrations that must be restricted

Translate these rules into access-control policies so the AI agents only query data that matches the user group and domain making the request.

Decide where agents will run

In a decentralized model, you can choose where computation runs. Typical options include:

• Within your company network for sensitive workloads
• Within a dedicated cloud environment you manage
• In a hybrid approach that separates high-risk and low-risk data

Your choice should align with internal compliance, legal, and security standards for ClickUp usage.

Connecting Your Workspace to ClickUp AI Agents

Once your policies are clear, you can connect your workspace to the AI agents and configure how they operate.

Step 1: Establish a secure connection

First, set up a secure, authenticated connection from your environment to the workspace. General steps include:

1. Register your environment or service that will query the agents.
2. Configure authentication (such as API keys or identity federation).
3. Limit the connection to the ClickUp resources allowed by policy.
4. Test a basic request with a non-sensitive query to confirm connectivity.

Keep credentials stored in a secure secret manager and avoid embedding them directly in code.

Step 2: Configure domain-based access for ClickUp

Domain-based access lets you align AI behavior with how your organization is structured. To configure this:

1. Map email domains or identity domains to user groups.
2. Associate each group with specific spaces, folders, lists, and Docs.
3. Define which tools and connectors the agents can call per group.
4. Apply read or write limits depending on the sensitivity of the data.

This ensures that a user querying the agent from your environment only gets results from the parts of ClickUp they are allowed to see.

Using ClickUp AI Agents to Query Your Data

With connectivity and access in place, you can begin using the agents to interact with workspace content.

How to ask questions to ClickUp AI agents

Follow these guidelines when forming queries:

• Be specific about projects, spaces, or time periods.
• Reference task types, assignees, or statuses when needed.
• Indicate if you want summaries, lists, or detailed answers.
• Include whether the agent can take actions (such as updating tasks) or only read data.

For example, you can ask the agent to summarize all high-priority tasks in a particular space, or to retrieve Docs that describe a given process.

Combining tools and ClickUp content in one query

One of the strengths of the decentralized architecture is the ability to combine data from your workspace with other tools. When enabled by your policies, the agent can:

• Pull context from ClickUp tasks and Docs
• Cross-reference information from connected tools
• Return unified answers that span multiple systems

This keeps your team in one conversational interface while still honoring the separation between communication and production data.

Managing Security and Compliance in ClickUp AI

Security is central to the design of decentralized AI in your workspace.

How ClickUp agents protect sensitive data

The agents introduce multiple security layers:

• Access checks at the domain and user-group level
• Limited visibility into sensitive tasks or Docs
• Control over what tools and connectors can be called
• Separation of query interfaces from underlying data stores

By keeping AI requests constrained to allowed content, you maintain a clear boundary around your most important information.

Align ClickUp with your governance model

To align AI usage with existing governance, you should:

• Document which teams can use agents and for what purposes
• Set retention rules for logs and query histories
• Regularly review access policies and update them as teams change
• Provide internal training on safe request patterns

When governance is explicit, adoption of AI in your workspace becomes smoother and more predictable.

Optimizing Team Workflows with ClickUp AI Agents

After the initial rollout, you can optimize how teams interact with agents to unlock more value.

Practical use cases for ClickUp AI

Teams commonly apply the agents to tasks such as:

• Summarizing long project Docs into short briefs
• Generating status overviews from current tasks
• Answering onboarding questions using existing documentation
• Surfacing blockers or risks based on task metadata

Each use case should be reviewed and approved according to your internal security and compliance guidelines.

Monitoring performance and iterating

To keep improving results, you can:

• Track common questions and refine prompts or templates
• Identify gaps in Docs and tasks where context is missing
• Adjust access rules when agents return too broad or too narrow answers
• Gather feedback from teams on response quality and speed

This feedback loop helps your organization get more from AI while staying within the boundaries defined by your policies.

Next Steps and Additional Resources

To go deeper into the decentralized AI architecture and capabilities, review the official information provided by the platform. You can find more about the current model and roadmap at this detailed overview of decentralized AI agents.

If you want expert help designing secure, scalable setups, consult specialized implementation partners such as Consultevo, who can advise on best practices for policy design, access control, and workflow optimization.

By following the steps in this guide, you can configure decentralized AI agents to work safely with your workspace, enabling your teams to search, summarize, and act on information with confidence while maintaining strong security and governance.

Need Help With ClickUp?

If you want expert help building, automating, or scaling your ClickUp workspace, work with ConsultEvo — trusted ClickUp Solution Partners.

Get Help

“`