Inbound calls
The call queue, triaged.Operators, freed up.
An AI voice agent for inbound calls is the first line of a call centre or support line: it identifies the request, checks the information in your systems, opens the ticket and transfers complex cases to an operator, along with all the context.
The queue grows, and operators repeat the same steps
At busy times, callers wait for minutes on end for questions that can be resolved in a few seconds: where is my order, what is the status of my ticket, which documents do I need to send. Operators lose time on identification and note-taking, while the genuinely difficult cases wait in line.
- A large share of calls ask for information that already exists in the system
- Every call starts with the same identification questions, asked manually
- Details noted in a hurry reach the ticket incomplete and have to be requested again
- A transferred caller repeats their story from scratch
Who it makes sense for
- Support departments and call centres with predictable call peaks
- Online stores and distributors that receive many questions about order status
- Service providers (utilities, internet, maintenance) with repetitive “I have a problem” requests
- Teams that already use a ticketing system and want calls to enter it in a structured way
What the agent can take over from support calls
- 01
Caller identification
Asks for the order, contract or ticket number and checks the details in the system, following the agreed security rules.
- 02
Order or ticket status
Reads the status from your systems and explains it in terms the caller understands.
- 03
Triage by reason and urgency
Classifies the request (complaint, fault, return, information) and sends it to the right queue.
- 04
Opening the ticket
Creates the ticket with the problem description, contact details and category, so the operator no longer takes notes by hand.
- 05
Answers from the knowledge base
Answers frequently asked questions only from the articles and procedures approved by the support team.
- 06
Transfer with a summary
When the case needs a person, the operator receives the call together with a summary and the details already collected.
How it works
How a support call is handled
The steps marked in yellow are approved by a person.
- Input
- AI
- Action
- Human in the loop
- Result
- 01
Input
Call in the queue
The customer calls the support or orders line.
- 02
AI
Identification and reason
The agent says it is automated, then finds out who is calling and why.
- 03
Action
System lookup
Checks the order or ticket in the connected systems.
- 04
Action
Ticket created
Records the request in a structured way, in the right category.
- 05
Human in the loop
The operator takes over
Complex cases reach a person, with a summary of the call.
- 06
Result
Case documented
The ticket holds the full history for follow-up.
What information and access the voice agent uses
- Controlled access, read-only where possible, to order or ticket status
- The support team's knowledge base, with approved and up-to-date articles
- The ticket categories and prioritisation rules you use today
- Identification rules: what details the agent may ask for and what information it is allowed to share
- Operators' schedules and the queue transfer rules
- The disclosure texts about the automated assistant and about call recording
Possible integrations
- Zendesk
- Freshdesk
- Jira Service Management
- Salesforce Service Cloud
- Cloud call centre platforms
- SIP trunks
- Twilio
- WooCommerce
- Shopify
- ERPs via API
- Zendesk
- Freshdesk
- Jira Service Management
- Salesforce Service Cloud
- Cloud call centre platforms
- SIP trunks
- Twilio
- WooCommerce
- Shopify
- ERPs via API
Each integration's compatibility is checked during the analysis phase, for the systems and versions you use.
Control and transparency
Where a person decides
- Complaints, compensation claims and policy exceptions are handled exclusively by operators
- Any promise of a refund, deadline or compensation is made by a person, not the agent
- Knowledge base articles are approved by the support team before they are used
- Supervisors periodically review samples of calls and the categories the agent chose
- The caller can ask to speak to an operator at any time
Limits we state from the outset
- The voice is synthetic, and some calls may be only partly understood; in those cases the agent clarifies or transfers
- Dictated order numbers, codes and addresses can be misrecognised; the agent repeats them for confirmation
- It works best when the data in your systems is up to date: the agent reports exactly the status it finds there
- Upset callers or those with complex problems are better served directly by a person, and the agent transfers them quickly
- Transfers depend on operator availability; if none is available, the agent takes the request for a callback
How we measure the agent on inbound calls
We agree the indicators together before launch and track them afterwards. The values depend on the process, the data and the volume.
- Calls resolved without transfer
- From the call log, confirmed through samples checked by supervisors
- Ticket category accuracy
- Tickets reviewed weekly by the support team: was the chosen category the right one?
- Quality of the handover summary
- Operators flag incomplete or incorrect summaries directly in the ticket
- Waiting time until an operator
- Compared with the period before, from the telephony platform's reports
- Non-compliant answers
- Transcripts checked on a set of real questions against the knowledge base
How we implement the agent in your call centre
- 01
Analysis of call reasons
We start from existing tickets and calls to see which reasons recur and what can be handled automatically.
- 02
Connecting to systems
We set up access to ticketing and orders, with minimal permissions and clear identification rules.
- 03
Pilot on a single reason
We launch the agent on a well-defined call type, for example order status, and monitor quality.
- 04
Controlled expansion
We add new reasons only after the support team validates the pilot results.
Use cases
The scenarios below are conceptual examples, built to illustrate what is possible. They do not describe implementations delivered by WEB-AZ.
- Online store
“Where is my order?”
After identification with the order number, the agent reads the delivery status, and if the caller wants to make a return, it opens the ticket and transfers them to a colleague.
Conceptual example - Internet provider
Reporting an outage
The agent checks whether there is a known outage in the area, records the details and creates the technical ticket, which the field team picks up.
Conceptual example - Parts distributor
Repeat orders from B2B customers
The customer dictates the codes, the agent confirms them one by one and creates an order request, which a sales representative checks before processing.
Conceptual example
Frequently asked questions
What is an AI voice agent for inbound calls?
It is an automated assistant that answers the support or orders line, identifies the caller, checks the status in the connected systems, creates the ticket and transfers cases that need a person to an operator, together with a summary. For the general number of a smaller company, an AI receptionist is the better fit.
How does the agent verify the caller's identity?
It uses only the identification steps you set, for example the order number plus an additional piece of information. It does not share sensitive data without this check.
What happens if the agent is not sure what the caller wants?
It asks a clarifying question, and if it is still unsure, it transfers the call to an operator with a summary of what it has understood so far, rather than guessing.
How are customer data and recordings protected?
The caller is told they are speaking to an automated assistant and whether the call is recorded. Access to systems is limited to what is necessary, and recordings and transcripts have a retention period and restricted access, agreed together.
Does it work with our ticketing system?
If the system has an API or an available integration, it can usually be connected. At the start of the project we check exactly which operations it allows.
Are operators still needed?
Yes. The agent takes on the repetitive part of calls, while operators remain for cases that need judgement, empathy or decisions on behalf of the company.
Can’t find the answer? Write to us and we’ll reply directly.
Want your operators to focus only on the cases that matter?
Send us the main reasons your customers call, and we will propose a pilot on the most suitable call type.
Related solutions
- AI receptionistYour company's main line answered politely: simple questions handled, messages taken and calls routed to the right person.
- Phone conversation analysisCalls transcribed, summarised and grouped by topic, so you can see why customers call and where the service can improve.
- AI agent for customer supportAnswers customers from approved information, checks order status in your systems and hands over to colleagues the cases that need a person.