Overview
Helena is DeskDay’s built-in AI assistant for MSP technicians. It helps technicians analyse tickets, identify possible solutions, prepare customer responses, and understand customer sentiment without leaving the ticket workspace.
Helena uses the available ticket context, including the summary, description, conversation history, ticket properties, previous tickets, and connected documentation, to provide relevant assistance.
When Helena is opened, technicians can quickly:
Analyse the issue and review recommended next steps.
Find similar tickets and previous resolutions.
Review relevant knowledge base and vendor documentation.
Generate or refine a customer response.
Understand the customer’s tone and urgency.
AI-generated suggestions should always be reviewed by a technician before they are used for troubleshooting or customer communication.
Why use Helena
Helena helps technicians reduce repetitive work and avoid switching between multiple tools while handling a ticket.
It can help technicians:
Draft clear and empathetic customer responses.
Identify possible root causes and troubleshooting steps.
Surface relevant DeskDay and Hudu knowledge articles.
Find similar tickets and previous resolutions.
Locate official vendor documentation.
Understand customer sentiment before replying.
Adjust the tone and detail of a response based on the situation.
Helena supports technicians with context and recommendations. It does not replace technician judgement or technical validation.
Turn on Helena
To enable Helena:
Go to Control Center > AI & automation > Helena AI assistant.
Enable Helena for the account.
Configure the required AI and knowledge settings.
Connect Hudu when Hudu documentation should be included in Helena’s knowledge suggestions.
Connecting Hudu is optional. Without a Hudu connection, Helena can still use available ticket context, DeskDay knowledge base articles, similar tickets, and supported vendor documentation.
Once enabled, Helena becomes available from the ticket workspace.
Where Helena appears
Helena appears in the right-side Ticket tools panel of each ticket.
The Ticket tools panel also provides access to:
Notes & time
Knowledge base
Checklist
Billing
Products & expenses
Open Helena to access the following tabs:
Solution
Compose
Sentiment
Solution
The Solution tab analyses the ticket summary, description, conversation history, ticket properties, and available support information.
Helena can provide:
Possible root cause
Identifies the most likely cause of the reported issue based on the available ticket context.
The suggestion may consider information such as:
Affected product or service
Error messages
Reported symptoms
Troubleshooting already completed
Similar previous tickets
Available knowledge and vendor documentation
Recommended next steps
Provides a structured list of troubleshooting actions the technician can follow.
The recommendations may be based on:
Similar ticket resolutions
DeskDay knowledge base articles
Connected Hudu documentation
Official vendor documentation
Information already available in the ticket
Recommended steps will include references to the source used by Helena.
Confidence score
Indicates how confident Helena is in the suggested diagnosis or resolution.
A confidence score helps the technician understand how strongly the available ticket information supports the recommendation. It should not be treated as confirmation that the suggested solution is correct.
Similar tickets
Finds previous tickets with related:
Symptoms
Products or services
Error messages
Troubleshooting steps
Resolutions
Technicians can use similar tickets to understand how related issues were investigated and resolved previously.
Knowledge base articles
Suggests relevant documentation from:
The DeskDay global knowledge base
The corresponding customer knowledge base folder
Connected Hudu documentation
Technicians can review the suggested article before using it as part of the resolution or customer response.
Vendor documents
Finds relevant official vendor documentation for the product or service associated with the ticket.
Vendor documentation may include:
Troubleshooting guides
Configuration instructions
Known issue articles
Product support documentation
Recommended remediation steps
Before applying a suggestion, verify that the documentation matches the customer’s product, version, platform, environment, and configuration.
Compose
Use Compose to prepare a customer response based on the ticket context.
Technicians can:
Generate an AI-suggested reply.
Enter a custom prompt describing what the response should include.
Generate a response based on the proposed solution.
Review and edit the generated response.
Copy or insert the response into the ticket conversation.
Compose with a prompt
Use a prompt when the response needs to include specific information or follow a particular direction.
Refine a response
After generating a response, technicians can use the available refinements:
Make it shorter: Reduces the length while preserving the main message.
Make it more formal: Adjusts the response to use a more professional tone.
Make it more casual: Makes the response more conversational.
Add empathy: Adds acknowledgement of the customer’s concern or inconvenience.
Refinements update the generated response without changing the original ticket information.
Before sending the response, verify that it:
Is technically accurate.
Uses the correct public or private visibility.
Does not expose internal notes or sensitive information.
Matches the current ticket status and agreed next steps.
Sentiment
The Sentiment tab analyses the customer’s messages and provides information about the tone and urgency of the conversation.
Overall sentiment
Shows whether the overall conversation is:
Positive
Neutral
Negative
The overall sentiment may change as new customer messages are added to the ticket.
Sentiment score
Provides a numerical indication of the detected sentiment.
The score helps technicians understand the strength of the detected tone but should be reviewed together with the actual conversation.
Sentiment breakdown
Shows the proportion of:
Positive sentiment
Neutral sentiment
Negative sentiment
This provides more detail when the conversation contains mixed signals.
Detected signals
Highlights characteristics found in the customer’s messages, such as:
Clear or factual issue descriptions
Concise wording
Troubleshooting already attempted
Device or environment details
Repeated follow-ups
Frustration or dissatisfaction
Positive acknowledgement
Business-impact information
Urgency indicator
Identifies language suggesting that the issue is urgent or causing significant business impact.
Examples may include references to:
A complete outage
Multiple affected users
Business operations being blocked
Security concerns
A deadline or time-sensitive requirement
The urgency indicator supports prioritisation but does not automatically replace the ticket’s configured priority, impact, or urgency values.
Key phrases
Highlights important statements from the customer’s messages that influenced the sentiment analysis.
Key phrases help technicians quickly identify:
The main concern
Business impact
Customer expectations
Signs of frustration
Important troubleshooting details
Sentiment information helps technicians adjust the tone, urgency, and level of detail in their response. It should be used as supporting context rather than as a replacement for technician judgement.