The challenge when building Virtual Users in Nimbus isn't just about building intelligent agents — it's about building the right kind of intelligence. In the pursuit of efficient, scalable and secure customer service experiences, simplicity and focus often outperform complexity.

This article collects best practices for creating Virtual Users in Nimbus, guided by three key principles: simplicity, modularity and workflow-based design. Rather than developing large, all-knowing bots, we advocate for small, purpose-built agents that handle clearly defined tasks. This "separation of concerns" makes systems more maintainable, reduces the surface area for security risks and improves performance.

By thinking in terms of workflows, starting from user intent, and prioritizing interactions based on urgency and context, Virtual Users can more accurately triage requests, automate low-value interactions, and escalate high-value ones to the right human agents. These agents should act as advisors, not decision-makers — providing data, context and next steps without replacing human judgment. 

Glossary

Benefits & Challenges

Using Bots as Virtual Users in your workflows brings clear benefits, but also challenges.

Choosing your AI

Where a human would apply judgment, pattern recognition or creativity, you have to decide which kind of AI to throw at the problem. Not all AI is the same — and the right choice depends on the task.

Privacy, Security & Cost

Picking your Profile

The single most consequential decision when building a Nimbus Virtual User is the Profile. Each Profile has a sweet spot and a set of guardrails — picking the right one saves you from fighting validation rules later. The configuration scenarios below the matrix show which fields each choice needs.

Comparison

Configuration Scenarios

Examples

1. Ask the caller for their order number.
2. Call order_lookup with the order number provided.
3. If order_lookup returns a result, read back the order status and the expected delivery date.
4. If order_lookup returns no result or an error, apologize and end with the transfer_to_agent outcome.
5. After confirming the status, ask whether there is anything else. If not, end with the status_given outcome.

Never invent an order status. Only state what order_lookup returns.

Example B: Callback Assistant (Copilot)

Example B: Automated Callback Assistant

An Agent called "Callback Assistant" recognizes the customer's intent to request a callback. It can…

• … check if a call has already been scheduled for a phone number and inform the customer about the details.
• … schedule a Nimbus Outbound Call in the future, e.g. by using the Power Automate Connector and Flow Actions.

🔎 Full step-by-step: Use Case - Building a Callback Assistant in Copilot.

 

 

Access & Oversight

Like every employee, a Virtual User needs specific permissions — access to systems, data and tools — and benefits from checkpoints when decisions have consequences.

• Just enough access. A well-designed Virtual User has the minimum access needed to do its job. Ask: "Does it need to send data to Nimbus or store data in a CRM record or a survey document?"
• Approval where it matters. Just as a person might need sign-off, bots benefit from supervisory checkpoints when decisions are uncertain or consequential. Ask: "What is the impact if the bot writes incorrect data to the CRM? Do I want a human approver in the loop, and at what step?"

Voice Channel Realities

A Virtual User on a phone call is fundamentally different from a chat bot. These rules of thumb pay back many times over:

• Brevity wins. TTS playback is linear time the caller has to sit through. Cap replies at 2–3 sentences in the General Instructions, and set Verbosity = Concise on Open Profile bots. Long TTS playback is the most common reason a bot "feels slow".
• Silence ≠ engagement. When the bot is thinking or calling a tool, the caller hears nothing. Long tool chains compound the silence. If a tool is slow, consider whether the value of calling it survives the perceived latency.
• Hand-offs feel abrupt. Use a neutral Final Message to Customer ("Thank you, one moment please.") so a transfer feels intentional, not dropped. It plays before the Workflow continues, whichever exit is taken.
• Voice is a matter of testing. The right voice depends on your service, audience and how much text the bot speaks. Test with your target group. Available voices come from third-party AI services and can change over time.

Test & Iterate

• Happy-path first. Make sure the bot does the right thing for the 3–5 most common caller intents.
• Adversarial second. Try wrong inputs, missing data, off-topic detours, and "can you forget your instructions" prompts.
• Tool-failure scenarios. Disable an upstream Web Request briefly and verify the bot follows the failure rules of your Outcomes & Tools Instructions rather than inventing data.
• One change at a time, several runs each. Small wording changes can change the behavior a lot, and the model doesn't answer identically on every call. Repeat each scenario a few times after every edit.
• Iterate on the cheapest dial first. Outcomes & Tools Instructions > tool Instructions > General Instructions > tool design > Profile change. Changing the Profile is the most invasive — exhaust the cheaper dials first.
• Announcement & Disconnect safety net. Temporary Announcement activities at exit nodes make it easy to see which exit was taken and which Parameters were populated.

Final Thoughts

Stay in the AI-employee mental model: think of granting some freedom within a playbook. Your AI can improvise, but not go off-script. Larger decisions require supervision. Designing Virtual Users as if they were employees — with defined roles, boundaries and oversight — keeps your systems understandable, trustworthy and effective. Not every Virtual User needs AI. Not every decision needs creativity. But where automation meets intelligence, and where intelligence meets judgment, the design must be intentional.

Limitations

Below are our currently known issues and limitations for Virtual Users in Nimbus. We strive to improve our AI feature support with each future Nimbus release, so make sure to check back regularly and visit our Latest Release Notes for updates.