AI receptionist setup should happen before you forward live customer calls. Start by defining the receptionist's job, approved knowledge, common call types, actions, human handoffs, failure paths, test scenarios, and one owner for updates. This checklist turns those decisions into a launch plan your team can review and verify.
Last updated: August 7, 2026. By the Telvana team.
What should AI receptionist setup include?
A complete AI receptionist setup includes eight operating decisions:
The job the receptionist owns
The business information it may use
The call types it must recognize
The details it needs for each call type
The action it may take next
The point where a person takes over
The fallback when an answer, transfer, or connected tool is unavailable
The tests and measures used to verify performance
This is broader than choosing a voice and writing a greeting. Those choices matter, but they do not tell the receptionist what to do when a caller changes topics, asks an unknown question, requests a person, or tries to book a time that is no longer available.
Start with one clear receptionist job
Write the job in one sentence before configuring anything else. A useful starting point is:
"Answer routine calls, identify why the person is calling, provide approved information, and move the caller to the right next step."
Then define what is outside the job. The receptionist might answer questions about hours and service areas, but not make a judgment that belongs to a technician, attorney, clinician, claims professional, or owner. It might collect details for an urgent request, but only a person or approved workflow should decide what happens next.
A narrow first release is easier to test. Google Cloud's general agent design guidance recommends starting with top level requests, establishing the basic structure, and then expanding the conversation paths. That approach keeps the first call flow understandable while your team learns from real calls.
Build a call flow launch card
Use one launch card for every call type the receptionist will handle. The card turns a vague goal into decisions your team can inspect.
| Field | Decision to record | Example |
|---|---|---|
| Business outcome | What useful result should this call produce? | Capture a qualified service request |
| Call type | What is the caller trying to do? | Request a new service appointment |
| Source of truth | Where does the approved answer come from? | Current service and hours knowledge base |
| Required details | What is the minimum information needed? | Name, callback number, service need, location, timing |
| Primary action | What should happen when the flow succeeds? | Offer an approved appointment path |
| Human handoff | When should a person take over? | Caller requests a person or the request needs judgment |
| Failure path | What happens if the preferred action is unavailable? | Take a detailed message and confirm the next step |
| Owner | Who approves and maintains this flow? | Office manager |
| Success measure | What will show that the flow works? | Calls reach the correct approved next step |
Complete the card with the people who handle calls today. The owner often knows the exceptions, while the office manager or dispatcher knows which details make the follow up useful.
If you already have a greeting and behavior draft, use the AI receptionist script template for the wording. Keep this setup card focused on the operating decisions around that script.
Decide what the receptionist can answer
A knowledge base should contain current, approved business facts. Common categories include:
Business hours and holiday exceptions
Service areas or locations
Services the business currently offers
Appointment types and booking rules
Basic process questions
Transfer destinations and availability windows
The approved response when an answer is not available
Assign one owner to each information source. A polished answer based on an outdated page is still wrong. Review website pages, documents, calendars, and internal instructions before importing or connecting them.
Telvana's current call handling features include FAQ and knowledge base handling, smart call routing, appointment scheduling, call visibility, CRM and calendar sync, bilingual support, and post call SMS notifications. Your setup still needs to define which of those capabilities belongs in each call flow.
Map every call type to one primary action
Do not give every caller the same sequence of questions. Create a small set of call types based on the calls your business actually receives, then map each one to one preferred action and one fallback.
| Call type | Useful details to collect | Primary action | Fallback |
|---|---|---|---|
| New lead or service request | Contact details, need, location, timing | Book, route, or create an approved follow up | Detailed message with confirmed callback details |
| Existing customer question | Identity details allowed by your process, reason for call | Answer from approved information or route | Human handoff or callback request |
| Appointment request | Appointment type, requested timing, required details | Use the approved scheduling path | Offer a permitted alternative or take a message |
| Billing or account question | Minimum details needed for routing | Send to the approved person or workflow | Capture a message without guessing |
| Defined urgent request | Location, callback details, approved urgency fields | Follow the business's human escalation rule | Approved after hours or callback path |
| Vendor or partner call | Organization, reason, intended contact | Route to the right destination | Detailed message |
OpenAI's current voice agent guidance treats tools, handoffs, guardrails, human review, and observability as core workflow building blocks. For a small business, the practical question is simple: which action is allowed for this call type, and what should happen when that action cannot complete?
Define handoffs and fallbacks before launch
A human handoff is not an admission that the receptionist failed. It is a designed outcome for calls that need judgment, authority, sensitivity, or information the system does not have.
Define these handoff conditions:
The caller asks for a person
The request is outside the receptionist's approved scope
The knowledge source does not contain a reliable answer
A connected calendar, CRM, or other tool is unavailable
The requested action requires a person to approve or decide
The business has marked the call type for immediate human handling
Then define the failure path for each handoff. What should the receptionist say if nobody answers? Which details should it collect? Who receives the message? What next step may it truthfully confirm?
Telvana's FAQ describes configurable transfers, detailed messages, callbacks, greetings, knowledge bases, call flows, and escalation rules. The safest setup is the one that makes the preferred action and the fallback equally clear.
Connect actions only after the rules exist
Calendar and CRM connections can make a receptionist more useful, but a connection does not define the business rule.
Before enabling appointment scheduling, decide:
Which appointment types may be booked
Which calendar or system is authoritative
Which days and times are eligible
Which caller details are required
What happens when the requested time is unavailable
What the receptionist may confirm after a successful booking
What happens when the scheduling connection fails
Before enabling CRM updates, decide which record should be created or updated, which fields are required, and who owns follow up. Keep the collected information limited to what the next action needs.
The Telvana general receptionist page describes a three part execution framework: a customer calls, the AI handles the approved request, and a person receives the call when escalation is needed. Your setup card supplies the business rules inside those steps.
Test with a scenario matrix
Test the workflow as a customer would use it, not only as the person who configured it. Google Cloud recommends defining test cases and using them to prevent regressions as an agent changes. Its guidance also calls for event handlers that manage unexpected input and connected service failures.
Use this scenario matrix before forwarding live calls:
| Scenario group | Test case | Pass condition |
|---|---|---|
| Normal | Caller asks a common approved question | The answer matches the current source |
| Normal | Caller requests an approved appointment | The receptionist follows the correct booking rule |
| Normal | Caller needs the standard human destination | The transfer follows the configured rule |
| Conversation | Caller gives details out of order | The receptionist uses the details without repeating every question |
| Conversation | Caller changes or corrects an important detail | The corrected detail controls the next step |
| Conversation | Caller interrupts or changes topics | The receptionist returns to a useful next step |
| Boundary | Caller asks an unknown question | The receptionist does not invent an answer |
| Boundary | Caller requests an action outside scope | The receptionist uses the approved human or message path |
| Failure | Transfer destination does not answer | The fallback message or callback path completes |
| Failure | Calendar or connected tool is unavailable | The receptionist does not claim the action succeeded |
| Timing | Caller reaches the business after hours | The correct after hours path runs |
| Regression | A knowledge or routing rule changes | Previously approved scenarios still pass |
Record the expected result before each test. Save the result, the date, and the person who approved it. A test is useful only when the team knows what passing means.
Use a go live readiness scorecard
Score each setup item from zero to two:
0 means the decision is missing
1 means the decision is documented but not verified
2 means the decision is documented and passed a test
| Readiness item | Score from 0 to 2 |
|---|---|
| Receptionist job and scope | |
| Approved knowledge sources and owners | |
| Call types and required details | |
| Primary action for each call type | |
| Human handoff rules | |
| Failure and after hours paths | |
| Calendar, CRM, or tool rules | |
| Scenario test evidence | |
| Change owner and review cadence | |
| Success measure and review process |
The maximum is 20. As a planning heuristic, not a validated benchmark, use these bands:
18 to 20: ready for a limited, monitored launch
14 to 17: close the documented gaps before routing live calls
0 to 13: keep the receptionist in testing
A high score does not remove the need for monitoring. It shows that the team has made and tested the main operating decisions.
The NIST AI Risk Management Framework Playbook organizes voluntary suggestions around Govern, Map, Measure, and Manage. NIST explicitly says its playbook is not a checklist to follow in full. The scorecard above is a narrower editorial tool for one receptionist launch, not a substitute for a broader risk program.
Watch the first calls for setup gaps
A monitored launch should answer one question: where does the real call differ from the setup assumptions?
Review:
Call types the team did not anticipate
Questions missing from the knowledge source
Details callers give in unexpected language or order
Handoffs that reach the wrong destination
Transfers or connected actions that fail
Cases where the receptionist confirmed too much or too little
Repeated corrections from callers
Outcomes that are difficult for staff to act on
Fix the rule or source, then rerun the affected test and the nearby regression tests. Do not solve every problem by adding more instructions. Sometimes the better change is a narrower scope, a clearer source, or an earlier human handoff.
Common AI receptionist setup mistakes
Starting with every possible call type
A broad first release creates more rules, more edge cases, and more ways for the workflow to become unclear. Start with the top level requests and expand after the core paths work.
Importing business information without reviewing it
Website pages and documents may disagree about hours, services, or policies. Choose an approved source and an owner before using the content.
Treating the greeting as the whole script
The greeting starts the conversation. It does not define information collection, actions, handoffs, failure paths, or confirmation.
Connecting a calendar before defining booking rules
A working connection can still produce the wrong outcome if the allowed appointment types, durations, destinations, or fallback behavior are unclear.
Testing only the happy path
Unknown questions, unavailable people, failed tools, corrections, interruptions, and after hours calls reveal whether the workflow is ready.
Launching without a review owner
Call flows change when hours, services, staff, systems, or customer questions change. One person needs to own the update and regression process.
Frequently asked questions
How long does AI receptionist setup take?
The setup time depends on the number of call types, information sources, connected tools, handoff destinations, and tests. A narrow flow can be ready sooner than a receptionist responsible for several departments or complex scheduling. Use the readiness scorecard instead of relying only on a promised setup time.
Do I need special phone equipment?
Telvana's FAQ says it works with an existing business phone number and does not require special phone equipment. The exact routing plan should still be confirmed for the business before live calls are forwarded.
What information should I prepare?
Prepare current business hours, services, locations, common questions, call types, required caller details, appointment rules, transfer destinations, after hours behavior, and the person who owns each source or workflow.
How many call types should I launch first?
There is no universal number. Start with the smallest group that covers the top level requests your business receives and that your team can test thoroughly. Add another call type only after its source, action, handoff, fallback, and tests are clear.
How often should I update the setup?
Review it whenever hours, services, staffing, routing, appointment rules, connected systems, or customer questions change. Also review repeated unknown questions, failed actions, and caller corrections from real calls.
Turn the checklist into a working call flow
A useful AI receptionist setup is not a collection of settings. It is a documented operating decision for every common call: what the receptionist knows, what it collects, what it may do, when a person takes over, and how the team verifies the result.
Book a Telvana demo to see how an AI receptionist could fit your business's call flow.