AI employees that work the way your business actually runs.
We design and build custom AI employees: voice agents that answer the phone, chat and SMS fronts, and the automations that connect them to your calendar, CRM, and payments. Off-the-shelf tools recite generic prompts; we build yours around your real flows, your data, and your edge cases. And we are not guessing at how this goes: our own AI employees answer calls for service businesses every day, so every decision in this discipline is load-tested on our own phone lines first.
This is not a service we only sell. Our own AI employees answer calls for service businesses every day: hear one at work before you scope yours.
What we build, concretely.
Voice agents that sound like your front desk
An agent that answers every call in under a second, qualifies, routes, and escalates to a human when it matters. Built on your scripts and your tone, not a stock persona.
Chat and SMS, same brain
One AI employee across web chat and text messages, with the full conversation history in one place. Missed calls get an instant text back, every time.
Automations behind the employee
The agent is only useful if it can act: calendars booked, CRMs updated, invoices raised, follow-ups scheduled. We wire it into your systems, not around them.
Escalation with judgment
Every AI employee knows what it does not know. Edge cases hand off to a human with the full transcript attached, before the caller ever notices the seam.
Your data, your guardrails
Prompt design, retrieval over your own docs, and limits tested against the ways real callers try to break things. Nothing depends on a black box you cannot inspect.
Measured like software
Answer rates, containment, booking rates, and cost per call, all instrumented from day one. An AI employee is a system you operate, not a feature you flip on.
The stack, and why.
Voice pipeline
WebRTC and Twilio Media Streams with sub-second first word. Streaming ASR and TTS so the caller hears a human rhythm, not a walkie-talkie.
LLM orchestration
OpenAI and Anthropic models behind an explicit decision layer: intents, tools, and guardrails you can read, diff, and audit.
Retrieval & memory
Vector and keyword search over your docs, with per-caller memory scoped to what the conversation actually needs, and nothing more.
Integrations
Google Calendar, HubSpot, Salesforce, and Stripe, wired through idempotent webhooks and background jobs so no booking happens twice.
Guardrails & evals
An eval suite that runs before any prompt change ships. An AI employee is regression-tested like any other code we deliver.
Observability
Dashboards for answer rate, latency, containment, and cost per call, so operating the employee is a number, not a vibe.
How a project runs.
Shadow the real flow
Before any code: we listen to how the job is actually done today. The scripts, the edge cases, and the calls your team hates taking, all written down.
Prototype the hard call
A working agent on your hardest scenario, live on a test line, fast. If it cannot handle that call, the easy ones do not matter.
Wire it into your stack
Calendar, CRM, payments, escalation: the employee joins your systems with a human always one transfer away.
Run and tune
Real calls come in, the dashboards fill up, and the team that built it tunes weekly. Containment climbs, cost per call drops.
Before you ask.
Same engineering, two shapes. The product is the ready-to-use AI receptionist for service businesses. This discipline is the custom build: AI employees designed around your flows, your systems, and your data.
Everything else we build.
Have a job an AI employee should take over?
Talk to the engineers who would actually do the work. No account managers, no sales deck. One call, then a written scope and a fixed price.
Book a scoping call