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AI Voice Agents

AI voice agents that answer on the first ring

Voice agents that take real calls: answering, qualifying, booking, resolving. Built to respond in about a second, to survive being interrupted, and to hand a caller to a person with the full context when they need one.

Years of Industry Experience
10+
Global Clients
350+
Projects Delivered
420+
Tech Engineers
35+

The calls worth handing over

Start with the call type that repeats. Breadth comes later, if the numbers earn it.

Answering the calls nobody gets to

The after-hours calls, the overflow when two people are already on the phone, the third caller asking the same question about opening times. The agent picks up on the first ring and handles it end to end.

Qualifying inbound leads

It asks the qualifying questions your team asks, writes the answers into the CRM, and books the ones worth a call back. A lead that gets a response in under a minute converts very differently to one chased the next morning.

Booking and rescheduling

Reads live availability, offers real slots, writes the booking, sends the confirmation. Reschedules and cancellations go through the same path instead of a voicemail nobody clears.

Resolving the repeat tickets

Order status, delivery windows, balance checks, password resets. The agent looks the answer up in your systems rather than reciting a script, and escalates the moment it cannot.

What separates a voice agent from a phone menu

Every vendor demo sounds good. These are the four things that decide whether it holds up on real calls.

Latency is the product

A voice agent lives or dies on the pause before it answers. Past roughly a second, callers start talking over it and the illusion collapses. We build to a sub-second target end to end, which constrains model choice, streaming, and how much work happens per turn.

It has to survive interruption

Real callers cut in, change their mind mid-sentence, and talk over the agent. Barge-in handling and endpointing are the difference between a system people use and a system people hang up on.

Handoff that carries context

When it escalates, the human receives the transcript, what was already tried, and the caller's details. Making someone repeat everything to a person is worse than never automating the call.

Failure modes decided in advance

What happens when the model is unsure, the API times out, or the caller is angry. Each one routes to a human or a callback, chosen deliberately, because the default failure of a voice system is silence on the line.

What comes with it, and what we decline

Included

  • Inbound and outbound calling, or both
  • Telephony via your existing number and provider
  • Live lookups into your CRM, help desk, calendar and order systems
  • Multilingual handling where your callers need it
  • Call recording, transcripts and searchable history
  • Escalation rules and warm transfer to your team
  • Dashboards for containment rate, handle time and cost per call

We will not build

  • Voice cloning of a real person's voice
  • Cold-call campaigns to purchased lists
  • Anything that hides from the caller that it is an AI

Undisclosed AI and cloned voices are a legal problem in a growing number of states, and a trust problem everywhere. Our agents say what they are.

Recorded calls are regulated data

A voice agent records people, often without them thinking about it. That pulls in consent, retention and disclosure rules before it pulls in anything clever.

  • Disclosure that the caller is speaking to an AI, by default
  • Two-party consent handling for the states that require it
  • HIPAA or PCI DSS where the call touches that data
  • EU AI Act transparency duties for voice interaction
  • Retention windows you set, and deletion that actually deletes

How the build runs

  1. 01

    Listen to your actual calls

    We start from recordings or transcripts, not a workshop. Which calls repeat, which ones need a human, and what percentage could genuinely be contained. If that number is small, we say so before you spend anything.

  2. 02

    One call type, in production

    The narrowest useful scope, live and taking real calls with a human safety net. A voice agent that handles one call type well beats a broad one that mishandles everything.

  3. 03

    Tune on real transcripts

    Every week we read what actually happened, fix the turns that went wrong, and widen the scope only where the numbers support it. Containment and escalation rates are measured, not assumed.

AI We've Actually Shipped

Conversational, agentic and machine learning work running in production. Each card opens the full case study.

AI voice agent questions

What teams ask before putting an AI on their phone line.

Software that answers or places phone calls, understands speech in real time, looks things up in your systems, and completes the task before hanging up. It is different from an IVR phone menu, which only routes, and from a chatbot, which is text. The hard part is not understanding the words; it is doing it fast enough that the conversation still feels like one.

Around a second, end to end, from the caller finishing to the agent starting. Past that, people assume the line has dropped or start talking over it. That target drives the entire architecture: streaming speech recognition, a model fast enough to answer inside the budget, and streamed audio back. We treat it as an engineering constraint rather than something to tune later.

Yes, and it will tell them. Disclosure is required in a growing number of US states and under EU transparency rules, and hiding it destroys trust the first time someone works it out. In practice callers do not mind an AI that resolves the call quickly; they mind one that traps them.

Two costs: the build, which we scope and fix in writing after listening to your calls, and the running cost, which is billed per connected minute across telephony, speech and model usage. We size the running cost against the call volume you actually have so you can compare it to what those calls cost you today, before you commit.

Yes. The agent sits behind your current number and provider, so nothing changes for callers, and it reads and writes to your CRM, help desk and calendar through their APIs. We build into what you already run rather than asking you to move.

Where HIPAA or PCI DSS apply, we build to those requirements: minimum necessary access, encrypted recordings, retention rules you set, and audit logging on every lookup. Under the EU AI Act a voice agent carries transparency obligations, which the disclosure covers. We will tell you plainly which requirements bite on your use case before we build.

It transfers to a person and passes the transcript with it, so the caller does not start again. Escalation triggers are set deliberately, including caller frustration, repeated misunderstanding, and any topic you mark as human-only.

Start with the calls you already get

Bring a week of call volume and what the repeat questions are. Thirty minutes is enough to tell whether a voice agent pays for itself here, and we will say if it does not.