AI Voice Agents
Answer calls, qualify enquiries and book appointments by connecting a voice agent to the calendar, CRM and booking tools your business already runs on — not a script that breaks the moment a caller asks something unexpected.
Inbound and outbound calling, connected to your calendar, CRM and booking workflow.
The problem
For many service businesses, the phone is still where enquiries turn into bookings. When a call isn't picked up — because the team is on-site, mid-appointment, or it's outside office hours — the caller doesn't always leave a voicemail. A noticeable share simply call the next business on the list.
The cost isn't limited to the calls that go unanswered. Front-of-house staff also spend a meaningful part of the day answering the same handful of questions on repeat: opening hours, pricing ranges, appointment availability, where to park. That's time taken away from the calls and tasks that actually need a person's judgement.
A voice agent doesn't replace a trained team member's judgement. What it can do is make sure every call gets answered, routine questions get a consistent answer, and the details that matter — name, number, reason for calling, preferred time — are captured and passed into the right system before anyone calls back.
What this actually is
A scripted bot follows a fixed decision tree — useful for simple, predictable flows like confirming an appointment time, but it breaks down the moment a caller phrases something unexpectedly. A conversational voice agent uses a language model to understand intent and hold a more natural exchange, while still working within boundaries you define: what it can answer, what it must collect, and when it hands off. An agentic setup goes further still, allowed to take actions — checking calendar availability, creating a booking, updating a CRM record — within rules you set. Which approach fits depends on call volume, how varied the conversations are, and how much risk sits behind a wrong answer.
A voice agent is not a replacement for a receptionist who knows your regular customers, and it isn't suited to calls involving judgement calls, complaints, or sensitive situations. It won't reliably handle every accent, every noisy line, or a heavily non-standard request. We scope conversation flows around what the system can answer with confidence, and route everything else — by design — to a person. Any provider claiming it can handle any call, every time, is describing the technology inaccurately.
The same underlying technology is configured differently depending on the industry and the calls it needs to handle.
Capture job details, address and urgency for call-outs, then push qualified leads straight into the scheduling system.
Answer appointment enquiries, check live availability and confirm bookings against the calendar already in use.
Field initial enquiries on listings, screen basic criteria and route viewing requests to the right person.
Handle after-hours enquiries, take messages with full context, and flag anything time-sensitive for follow-up.
Answer order status and common policy questions, escalating anything account-specific to a human agent.
Take inbound calls from field staff or suppliers and log updates directly into internal systems.
Under the hood
A voice agent is only as useful as the systems it's connected to. In practice, a call comes in through a telephony provider, is routed to a voice/LLM layer that handles speech-to-text, intent understanding and text-to-speech, and that layer is wired into the systems the business already runs on: calendar for availability, CRM for lead and contact records, and a booking or scheduling tool to confirm appointments. Conversation logic — what to ask, what to confirm, when to stop and hand off — is built around your actual processes rather than a generic template. Depending on requirements, this can be built on a dedicated voice platform such as Vapi, assembled from telephony and language-model building blocks directly, or a mix of both. The right choice depends on call volume, latency requirements, and how much custom logic sits around the conversation — something we assess upfront rather than defaulting to one platform for every project.
A voice agent earns its place by writing into systems that already exist, not by creating a parallel process to manage.
Voice agents are built with clear boundaries, not left to improvise.
How we build it
Each stage is scoped around your actual call volume and systems, not a generic template.
01
Review current call types, volumes and the questions most often asked, and agree what the agent should and shouldn't handle.
02
Script the flows, handoff triggers and fallback responses, grounded in how your team already talks to customers.
03
Wire the agent into your calendar, CRM and booking tools so it reads live data and writes outcomes back in.
04
Run the agent through recorded or simulated calls, including edge cases, before any live traffic reaches it.
05
Go live on a defined number or call path, then review transcripts and outcomes to refine the flows.
FAQ
No. A text chatbot and a voice agent process input differently — speech involves pauses, interruptions and ambiguity that text doesn't. We design conversation flows specifically for spoken interaction, rather than repurposing a script built for a web chat widget.
Call quality depends on the voice platform and configuration used. Modern conversational voice models sound considerably more natural than older interactive voice response systems, though there are still limits — we're upfront about what to expect for your specific use case before building anything.
The agent is built to recognise when a question is outside its scope and hand off to a person, or take a message with the right context, rather than guessing.
Yes, for use cases like appointment reminders, confirmation calls or follow-ups — though outbound calling has additional considerations around consent and timing, which we factor into the design.
No. Platforms like Vapi are a good fit for some projects, but we also build on telephony and language-model infrastructure directly where that suits the call volume, latency needs or budget better. We scope this based on your requirements.
This depends on how many integrations are involved and how varied the call types are. A narrowly scoped use case with one or two integrations moves faster than a system covering several departments and tools.
Access to the calendar, CRM or booking tool you want connected, and clarity on which calls the agent should handle versus route to a person. We can help define the latter during scoping.
Capabilities
Deeper detail on the underlying services this work draws on.
Related services
Related implementation paths that often sit alongside this work.
AI Workflow Automation
Connect the tools you already use and automate the manual steps between them — leads, bookings, documents and approvals.
Custom Web Applications
Custom web applications — dashboards, portals, booking systems and internal tools — built and supported beyond initial launch.
Managed Application Services
Domain, hosting, deployment and ongoing maintenance for web applications, handled by one technical partner instead of several disconnected providers.
Tell us about your call volume and the systems you use, and we'll scope what's realistic before any build work starts.
