Virtual Users

Leverage AI-driven bots to use within your workflows

A Virtual User is an AI-powered assistant that interacts directly with customers - greeting the callers, capturing context parameters and handing the conversation result back to Nimbus Workflow.    

Use Cases

Virtual Users enable responsive, scalable self-service bots that can detect caller intent and integrate with external systems before — or instead of — handing over to a human agent. The list below is non-exhaustive; pick the closest pattern and adapt it.

Call triage Captures the callers intent and routes to its downstream flow. Set up with Virtual User Outcomes: such as "Create ticket", "Check status", “Escalate”
Identification gate Outcomes: Identified, Not Verified, Fraud Suspected — personalized self-service vs. manual verification vs. priority security queue.
FAQ with escalation Outcomes: Answer Found, Low Confidence, User Requests Agent — answer in-bot, offer alternative handling, or hand straight to an agent.
Payment / transaction Outcomes: Successful, Failed, User Aborted — confirmation, retry, or graceful exit.
Password reset Outcomes: Reset Successful, Reset Failed, User Locked Out — confirmation, retry, or escalation to support desk.
Survey Outcomes: Completed, Partial Completion, Drop Off — thank-you message, follow-up, or callback workflow.
Card blocking Outcomes: Card Blocked, Identification Failed, User Cancelled — confirmation with audit log, high-priority escalation, or safe exit.
 

INC AI and Virtual User Preconditions

PRECONDITIONS: AI Features, Bots and Virtual Users

✅ Nimbus Tenant Admin consent is required to enable the use of AI features. This is done in the Data Privacy Tenant Settings.  AI use will require your Tenant data (e.g. caller information) to be processed by external services

💡Good to know - shared setup effort: Once consent is granted, both Admin Roles “Tenant Admins” and “OU Admins” are able to create various AI Configuration items in the Nimbus Admin Portal. This also includes:

  • Access to Service Distribution Settings, e.g. to test workflows with your configured Virtual Users. 
  • Steer feature visibility via Companion Service Settings (e.g. when activities are supposed to happen unobtrusive in the background).
 
 

Virtual User Licensing

✅Nimbus License Management

  • Contact Center Enterprise Routing service licenses are required to use AI-driven Virtual User functionality. 
    ⮑With the license applied, corresponding Service Features (e.g. workflow activities, configuration tabs) are enabled.
  • Individual Virtual User license requirement: Same as regular Nimbus users, each Virtual User requires a separate license. This license can be applied individually in the Virtual User configuration - or in bulk - via Admin > Licensing view. 
    ⮑The license enables usage of the “Add Virtual User” Workflow Activity, without it the activity will be skipped over. For additional Virtual User licenses on your service, get in touch with your Customer Success representative.
 
 

Virtual User Bot Configuration

Virtual Users rely on Nimbus Configuration items:

✅ ALL: Virtual Users require Bots to be configured. Your bot choice also determines the underlying AI LLM into which the Nimbus Virtual User integrates. Your bot typ and profile should therefore be chosen with the intended use case in mind.

INC Language model comparison matrix

Defined in Bots Defined in Virtual Users 

Type

Nimbus managed or BYO

Agent Type

Underlying LLM

Virtual User Profile

Pre-built configurations to fulfill a certain use case

Nimbus AI Services Azure OpenAI – (GPT Realtime)1
  • Intent Analyzer  - Intent Analysis Use Cases. 
  • AI Workflow - Extending Virtual User with additional external system capabilities (MCP and/or Web Request, both optional) and route the conversation outcome back into Nimbus Workflows 

Custom AI Services

 

  • Intent Analyzer  - Intent Analysis Use Cases. 
  • AI Workflow - Extending Virtual User with additional external system capabilities (MCP and/or Web Request, both optional) and route the conversation outcome back into Nimbus Workflows 
  • Open Profile - Same as AI Workflow, but with additional controls over Verbosity, Tone, Role 
M365 Copilot Direct Line 3.0

Notes

1 Due to Microsoft Azure AI foundry availability in limited regions, data processed by a Nimbus Virtual User “GPT”-Realtime" integration might temporality leave due to failover scenarios:

  • Nimbus Cluster DE01, DE02, CH01, CH02, UK01, EU01, AU01 computation will be primarily performed in Sweden Central region.
  • Nimbus Cluster US01 computation will be primarily performed in the US East region.
 

✅SPECIFIC AI services / Agent technologies (e.g. Microsoft Copilot) may require additional configuration items such as: 


🔎For more details and specific configuration steps, refer to our AI Use Cases category and the specific Use Cases and pages linked above.

 
 
 

General

General

Nimbus-related general settings for the Virtual User.

Field Description
Name The name of the Virtual User, as it will appear in other selection dialogues of Nimbus (e.g. within Workflows).
Organization Unit Determines where the Bot will be available for selection.
Description

A Nimbus-internal description, e.g. “Support Bot for first response IVR”.

💡This field is optional, just for identification within the Nimbus UI and will have no impact on the Bot behavior.

Bot Configuration

✅Dependent on the “Organization Unit” selected: Provides a selection of previously configured Bots (AI models) and related configuration profiles. 
⮑ Based on the Bot and profile choice, other tabs and options become available .

Property Description Notes
Bot

Pick a previously configured Bot


⮑ The Bot's underlying model determines which options become available in the following.

🔎More details in the Preconditions above.
Profile

Various configuration profiles that steer the AI behavior. Choices are:

  • Intent Analyzer - Simple intent analysis and routing in Workflows
  • AI Workflow - Additional MCP and Web Request capabilities
  • Open Profile - Same as AI Workflow, but with additional controls over Verbosity, Tone, Role 

⮑ The choice automatically changes the visible properties on the tabs described further below.

✅ Required except for “Copilot Direct Line 3.0”

Bot Response Template 

 

Bot Response Templates map the JSON response your Bots (external APIs) deliver, with the goal to use that response as criteria within your Workflows.  Required when “Copilot Direct Line 3.0” was selected as a Bot

Modalities

Property Description Notes
Modalities

Enables the bot to handle and react to Audio/Video (calls).


⮑ Depending on Bot selection, an additional Speech Recognizer may be required → See below.

💡Currently the choice is locked. Further modalities will be made available in future.
Speech Recognizer

Speech Recognizers (used for speech-to-text transcription) to be configured for selection in this menu.

💡 Speech Recognizers are used to parse the language of the calling customer into text for the bot to process. They can be configured as multilingual-capable, but are more effective when set to a specific language.

Required when “Copilot Direct Line 3.0” was selected as a Bot.
Licenses

✅When you configured a new Virtual User: You need to save and re-open your Virtual User configuration before you can apply a “Virtual User” license. 

⮑ This actively draws from your License Management pool and allows services to effectively use your “Virtual User” in production.

 

💡If you require additional Virtual User licenses, get in touch with Luware Customer Success.
 
 

Behavior

Behavior

✅ This tab and contents are shown depending on General > Bot Configuration. It steers general instructions for the Virtual User, e.g. the instructions sent to the AI model.

Property Description Notes
System Instruction Free-text prompt that defines the bot's persona, domain knowledge and rules. 

10,000 chars limit


Supports Custom Parameters and System Parameters 

Timeouts

Property Description Notes
Session Timeout Maximum total duration the Virtual User stays in the call. seconds
Idle Timeout How long the bot waits for caller input before taking the Idle Timeout exit. seconds
 
 

Conversations

Conversation

✅ This tab is shown for all Bot Configurations. It steers the how to engage with the customer, defining the messaging, language, and tone.

Property Description Notes
Initial Message

First thing the caller hears when the Virtual User joins. 

 

Free-text prompt that defines the bot's persona, domain knowledge and rules. 

💡When the Virtual User is invoked from Outbound Call with Workflow, this is the message played when the called party picks up.

500 chars limit


Supports Custom Parameters and System Parameters 

Closing Message

Final line the bot says before the activity exits. 

 

💡Useful for handing the caller over politely ("Connecting you now…") or closing the loop on a self-service interaction. 

500 chars limit


Supports Custom Parameters and System Parameters 

Voice & Language

Property Description Notes
Language / Voice

Optional spoken-language. 

💡Not available for Copilot Bots, which are configured via Speech Recognizers instead.

✅Only visible on bot profile: “AI Workflow” or “Intent Analyzer”
User Voice

Voice selection for the chosen language.

💡Not available for Copilot Bots, which are configured via Speech Recognizers instead.

Verbosity

Short label describing how chatty the bot should be:

  • Concise 
  • Balanced 
  • Detailed
✅Only visible on bot profile: “Open Profile”
Tone Short label describing the desired conversational tone (e.g. "Friendly and professional", "Concise and factual"). Combined with Role and Verbosity to color the bot's style.

Role 

(deprecated1)

1 Deprecation Note: The Role field will be phased out soon, to be merged with the “System Instructions” in a future release.

 

Short label describing the persona the bot plays (e.g. "Customer service representative", "Pharmacy advisor"). Used as a building block of the system prompt so admins do not have to re-write the role into every System Instruction.

 
 

Tools & Outcomes

Tools & Outcomes

✅ This tab and contents are shown depending on General > Bot Configuration. It steers how the AI interacts with external systems and how to orchestrate the tool flow when interacting with the customer. 

Property Description
Flow Description

A single free-text field on the Virtual User that tells the model…

  • … how to drive the conversation when Extension Tools (both MCP or Web Request) are involved. It is the bot's "playbook" — the model reads it alongside the System Instruction every turn and uses it to decide when to call a tool, which tool to pick, and what to do with the result.
  • how to use the “Outcomes:” in a conversation (which can be used to retrieve information for the customer, fill Parameters and (optionally) follow exit the “Virtual User” Conversation Handling Activity.

💡How to write a good Flow Description

  • Keep it concrete and step-driven. The model performs best when it can read the description as a numbered playbook rather than as prose:
  • Spell out the conversation phases (greet → identify → look up → confirm → close).
  • Name each tool by the exact label it has on the Virtual User — "call the OrderLookup Web Request", not "call the order system".
  • The order of execution (e.g. FIRST validate bank name, IBAN, THEN retrieve user name, ONLY THEN answer the inquiry)
  • Mandatory and optional steps with clear signal words (e.g. these steps must be successful | this step can be optional)
  • Handle errors, outlining what to do if the tool fails or returns nothing.
  • Avoid duplicating the system Instruction (role, tone, language). The Flow Description is about  the technical information flow, not personality.

☝️Note: The following examples are mere reference points, not functionally verified with specific use case scenarios or products.

Example 1 — Web-Request-only Virtual User (order status bot)

1. Greet the caller and ask for their order number.
2. Call the OrderLookup Web Request with the order number the caller provided.
3. If OrderLookup returns a result, read back the order status (shipped / processing / cancelled)
 and the expected delivery date.
4. If OrderLookup returns no result or an error, apologise, offer to transfer to a human agent,
 and end the conversation.
5. After confirming the status, ask whether there is anything else. If not, say goodbye and close.

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

Example 2 — MCP-Server-only Virtual User (internal Jira helper)

1. Greet the caller and ask which Jira ticket they are calling about.
2. Use the JiraServer MCP Server to look up the ticket by ID.
 - Prefer read-only tools first (get-issue, search-issues).
 - Only use write tools (add-comment, transition-issue) if the caller explicitly asks for it
 and confirms with "yes" before you make the change.
3. Summarise the ticket: title, status, assignee, last update.
4. If the caller asks for a change, perform it through the JiraServer, then read back what changed.
5. Close by confirming what was done and offering to do anything else with the same ticket.
 
 

Example 3 — Mixed Web Requests + MCP Servers (concierge bot)

You handle two kinds of requests: account questions and ticket questions.

Account questions:
 - Use the CustomerLookup Web Request to identify the caller by phone number.
 - If CustomerLookup returns no match, ask the caller for their customer ID and try again.

Ticket questions:
 - Use the JiraServer MCP Server for everything related to support tickets.
 - Always look up the ticket first; never quote a status from memory.

General rules:
 - Never expose internal IDs, URLs or raw tool output to the caller.
 - If a tool fails twice in a row, apologise and offer to transfer to a human agent.
 - Keep answers under three sentences unless the caller asks for detail.
 
 
 

Extensions Tools

💡These settings allow to extend the Virtual User with external system capabilities: MCP Server and Web Requests. They can be selected independently and are both optional. Unselecting a tool keeps its stored configuration, so re-selecting it later restores everything you entered.

✅Precondition: Available when Bot Profile: “AI Workflow” or “Open Profile”  were selected in the ”General" tab.

 

☝️PLEASE TAKE NOTE:

  • Failure Case handling: For both MCP and Web Request your flow description doesn't need to handle failure cases manually. This is done in the "Add Virtual User" Conversation Handling Activity. You can also define multiple “Outcomes:” and treat them each like a different case.
  • We highly recommend to limit and purpose-scope retrieved context via MCPs and Web Requests. If too many tools added, the Virtual User may slow down from tool usage or get the context wrong if too much data is provided. Also refer to our Best Practices - Virtual Users in Nimbus for further considerations.
 

Web Requests

Web Requests

A previously configured Web Request can be bound to the to the Virtual User, so the model can call it mid-conversation. Each binding has two fields on this page — the Web Request name itself, and an AI Description that tells the model when to call it.

✅Precondition: Requires at least one configured configured Web Requests from the same (or a parent) Organization Unit where your Virtual User lives in.

💡Use this when …

  • … you want transparent definition and orchestration in Nimbus.
  • … the validation logic must be auditable directly in Nimbus.
  • … your called APIs are time-sensitive and tightly sequenced.
 

☝️Accounting for delays: Virtual User AI models are optimized for timely responses to a customer. A missing web request status code may be interpreted as “unresponsive”, which results in the “Failed” condition exit in Workflows being taken.

✅ Recommendation: When using AI-driven workflows, always enable “Wait for response” in your Web Requests > Response configuration. This is especially important when your AI workflow depends on the data being available. 

💡Of course “Wait for response” also means that long-running requests may incur a delay that the customer will perceive as silence from the AI. (Expected) long-running requests should therefore be announced to the customer beforehand. Also, timeout exit codes are expected be sent by the target system so the AI knows when to move on.

 
Property Description
Web Request
(selection)

Each Web Request:

  • Is called directly from within the Nimbus configuration.
  • Uses HTTP Methods (POST, GET, PUT PATCH DELETE)-
  • Needs individual Headers / Authentication
  • Has Name fields for reference and…
  • AI Description fields for AI handling instructions.

☝️Flow Description dependency: 

  • Web Request Name / Description fields are used by the AI for reference during the Flow Description. 
  • The model will follow the order and logic you specify in the Flow Description, not the order in which the Web Requests were added to the Nimbus UI.
    In the → Flow Description field, you should clearly define how Web Requests are used in sequence
 

💡Example: Unlike MCPs more capability-based flow, Web Requests should have a clear order sequence to the flow, as information retrieved can be often co-dependent, specific and granular. An example Web Request-centric flow description could therefore look as follows:

This workflow is designed to handle complex banking inquiries with multiple steps and dependencies.
The assistant will guide the customer through a series of questions to gather necessary information, 
validate it, and provide appropriate responses based on the detected Outcomes:.
 
The workflow should work as follows:
 1. Ask for the users bank name and validate it.
 2. Ask for the last 4 digits of the iban number and validate it.
 3. Ask for the users name name and validate it.
 4. Only when all the information is collected and validated, the assistant should proceed to answer the users inquiry based on the detected intent.
AI Description

This field tells the Virtual User how the Web Request is to be used.


Note: The model does not see the Web Requests generic Description from its config page. Instead, use this AI Description to describe it to the model.

💡The AI Description should therefore also provide a precise description to the model, outlining the functional goals of the Web Request and necessary field descriptions to match with the customer conversation.

WEB REQUEST A (IBAN): For IBAN: “international bank account number (IBAN)”
WEB REQUEST B (Account): For Account Number: “bank-specific account number” (ACCT NO)
 
 

MCP Server

MCP Server

An MCP Server attaches a Model Context Protocol server endpoint to the Virtual User. Once attached, the server's tools are exposed to the model in real time during the call.

✅Precondition: Requires you to connect to a running, external MCP server, which offers more flexibility. The MCP server uses reusable Authentication configuration items — 🔎 also see Authentication in the property table row below.

💡Use this when…

  • …you already operate or connect to existing MCP servers.
  • …you want tools and capabilities to evolve independently of Nimbus, but constrain their usage.
  • …you want long‑term flexibility with less UI configuration.
 

🔎Notes

  • Scoped use: The AI model identifies each MCP Server by its Name and Description. The individual tools inside the server are advertised by the server itself over the MCP protocol — Nimbus does not rename or filter them. If you require scoped access, you should limit the capabilities server-side to prevent any unwanted tools from being (e.g only READ, not WRITE).
  • 💡In the general → Flow Description, you should clearly define how MCP tools are to be used. The model will follow the order and logic you specify in the flow description, not the order in which the MCP servers were added into the Nimbus UI.
  • Good to know: Nimbus Virtual User is compatible with MCP servers designed for OpenAI GPT‑Realtime, including remote MCP servers exposed over HTTP. More information can be found in the OpenAI MCP connector guide and Realtime API documentation.
 
Property Description
Name

Each MCP server:

  • Uses the Model Context Protocol
  • Runs outside as server and is consumed by Nimbus, with an URL like: 
    https://<yourdomain.com>/mcp/
  • Uses available tools (discovered dynamically)

☝️The MCP Server “Name” Must be unique on the Virtual User. The model reads this name when deciding which server to call — use the same label inside the Flow Description (e.g. "use the JiraServer MCP Server to look up the ticket"). 

 
URL The MCP Server's SSE endpoint (e.g. https://jira.example.com/mcp/sse). Nimbus opens a streaming connection to this URL for every Virtual User session that uses the server. 
Description Free-text summary of what the server is for and when the model should reach for it (e.g. "Internal Jira instance. Use for any ticket lookup, comment, or transition."). 
Authentication

✅Requires a (reusable) Authentication configuration to secure the connection to the MCP Server. 

💡The dropdown lists the Authentications available in the Organization Unit of your Virtual User (and its parent units).

Supported authentication types:

  • API Key — a header name and secret key (the previous behaviour).
  • OAuth 2.0 (Client Credentials) — Nimbus requests and refreshes a bearer token automatically from your identity provider. The Authentication holds the Access Token URL, Client ID and Client Secret.

🔍 Notes: 

  • Authentications are defined once, then reused across all MCP Servers.
  • The Authentication dropdown loads even for administrators who can manage Virtual Users but do not have direct access to the Authentications configuration.
  • Secrets are stored encrypted in the Nimbus vault and never returned to the UI in clear text.
 
 
 

Outcomes (Intents)

💡Note: The term “Intent” was introduced recently for Virtual Users in Nimbus. You consider the term “intent” and “outcome” interchangeably. We will unify the naming in a future release.

Outcomes represent the customer intentions the Virtual User can detect during a conversation. Instead of relying on a single Success conversation outcome, you define multiple, intent-driven results and decide how each one continues in the Workflow.

Outcome VS Non-Exit intent comparison during a “Virtual User” workflow interaction. Each allows to update parameters.

✅Preconditions 

🔎"Outcome" feature availability: Outcomes: are available for the following Bots: Intent Analyzer, AI Workflow and Open Profile, using either “Nimbus AI Services” and OpenAI GPT-Realtime models. 

  • ☝️Migration: Previous “Virtual User” activities: Previous Virtual User workflow activities had AI exits created on the workflow level (Audio Intent Analyzer) or hard-wired "Success" exits (AI Workflow, Open Profile) in the element. With the introduction of flexible Outcomes:, manual migration is necessary to avoid any disruptions and configuration errors.
    • Simply replace the “Add Virtual User” activity with a new one to leverage flexible Outcomes:.
    • Define at least one exit Outcome on the Virtual User configuration page, and map the exit on the workflow level. With no exit configured, the workflow will take the “AI Fallback”.
  • 💡No migration required for Copilot bots: Copilot uses its own exit handling1. Copilot "Topics”, of which the outputs are then mapped into Bot Response Templates

1 Depending on selected bot mode, the“Add Virtual User" Conversation Handling Activity is changing available configuration and exit properties.

 
Property Description
Outcome Name

Mandatory, unique name for the outcome — this is the label you later select on the “Add Virtual User” activity when mapping it to a Workflow exit.

💡Keep it to one word and avoid special characters (e.g. create_ticket) so the AI model detects it reliably.

Description Mandatory free-text that tells the Virtual User when to assign this intent (e.g. “The caller wants to create a new support ticket”).
“This outcome triggers an exit” (toggle)

Steers the behavior of this intent during the activity:

  • Exit intent — can be mapped to a dedicated Workflow exit on the “Add Virtual User” activity. Detecting it ends the conversation and steers the Workflow down the mapped path.
  • Non-exit intent — drives in-conversation behaviour only (e.g. capturing parameters) and does not end the Virtual User session.
Parameters Optionally attach up to 10 Parameters for storing customer-provided data. The AI decides which conversation data to write into them. 
💡The AI can immediately return the parameter contents back to the customer, e.g. to verify if it has correctly understood the instructions.

☝️Good to know

  • An exit-triggering outcome cannot be deleted while it is already used in any Workflow — the delete option is disabled to avoid breaking the Workflow.
  • At least one exit outcome must be mapped on the “Add Virtual User” activity before that activity can be saved.
 
 

Follow-up Steps

✅Follow-Up in other areas: 

  • In order to take effect, (licensed) Virtual Users must be added as a “Add Virtual User” Workflow Activity to your workflows.
  • We highly recommend to do test-calls to your service and thoroughly test every Virtual User change.
 

Limitations

INC AI and Virtual User Limitations

General note on AI-driven interactions

AI driven replies are very dependent on what the Customer is saying. For example, if the Customer is saying “I have trouble with my modem” it is not necessarily given that the bot will associate “Internet” as your workflow routing exit, unless specifically handled in your Virtual User integration and instructions. We therefore highly recommend to test and account for “creative” or “non-tech-savvy” wording when designing your Virtual User interactions within your workflows.

🔎Recommended reading for beginners: We collected and wrote down some Best Practices - Virtual Users in Nimbus to help you with considerations and risks when replaying human interaction with AI.

 

General Virtual User limitations

The current Nimbus implementation with AI-driven bots underlies the following limitations: 

  • Supported Modalities: Virtual Users (Bots) are currently available for Audio/Video modality tasks.
  • Virtual User Reporting: Sessions involving Virtual Users are not reflected as dedicated User Session. Virtual User session reporting is planned for a later point this year.
 
 

Microsoft Copilot Limitations

  • Expect processing delays: Processing AI answers takes a few seconds for voice-to-text-transcription, followed by AI processing and then the same transcription back into a voiced response. Luware is trying to minimize the delay on Nimbus call infrastructure, but the dependency on external APIs will always incur this delay. The Customer will hear silence during this processing and no audio feedback / silence detection.
  • Ensure you have no ambiguity in your topics. For instance, the word “Service” may be too generic if you want to transfer to different services. Rather use healthcare|medical|emergency as identifiers or use more complex Regular Expressions to identify replies.
 
 

Nimbus AI Services Limitations

Bot Configuration Profile 🔎 Design Notes (not limitations)
Intent Analyzer The Nimbus Virtual User Intent Analyzer is primarily designed to handle intent detection, as described under Use Case - Setting up a Nimbus Virtual User for Intent Analysis. Other use cases, such as self-service and customer feedback surveys are not supported by Intent Analyzer.
AI Workflow
  • Failed condition: If either a Web Request connection or MCP server connection fails, the “Failed” workflow activity exit will be taken immediately.  Also applies for any other Nimbus-internal or technical error.
  • Fallback condition: Any “Fallback” parameters will be updated with the response generated by the AI when a case cannot be handled.
Open Profile
 
 

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