Configure a tool yourself
Plan time for your own setup, integrations, testing and ongoing updates.
Choosing an approach
Compare Managed AI Receptionists
The right approach depends on your tools, internal technical time and how much implementation support you want.
Your options
What to consider.
Compare the scope and total operating costs of each option.
Use a managed implementation
Agree who handles configuration, integration work, reviews and ongoing support.
Commission a custom system
Define ownership, maintenance, documentation and the budget for more specialised requirements.
Start with the task that costs you the most time.
Tell us how enquiries arrive and what should happen next. We’ll help you scope a practical first step.
Compare Managed AI Receptionists FAQs
What is included in the setup?
We agree the call types, approved business information, routing, and supported integrations before implementation. Your team reviews the configuration and tests the handoff before launch.
What are the published voice plan allowances?
General receptionist plans list $29 for 80 minutes, $99 for 280 minutes, and $199 for 650 minutes per month. Confirm features and top-ups during onboarding. WhatsApp and custom automation are quoted separately.
Can appointments and transfers be configured?
Supported calendar booking, appointment requests, and transfers are configured according to the selected plan and integration. If a request cannot be confirmed, it should be routed to staff for follow-up.
How are sensitive workflows handled?
Medical arrangements list $199 and $349 tiers with agreed BAA and data-handling scope. Review the actual services, access, retention, and contracts. Administrative assistants do not provide clinical, legal, tax, or other professional advice.
How can we evaluate the service?
Review a live demo and agree a pilot with realistic calls, staff ownership, and acceptance criteria. A seven-day trial is advertised for receptionist packages; activation and account terms are confirmed during onboarding.
For an independent reference on evaluating AI risks, see the NIST AI Risk Management Framework.