implemented by Trusted Partners
A custom orchestration layer built for telephony, not adapted from a chat framework. Turn-taking, barge-in and packet loss are handled at the core.
Sub-second responses on a real phone line, not just in a browser demo.
Domain agents for scheduling, verification, collections and support, routed by a master intent layer.
One queue's logic can change without touching the rest of the deployment.
ASR, TTS and LLM sit behind connectors, so any one can be replaced per language or use case.
No vendor lock-in. Adopt a better or cheaper model without a rebuild.
Balances, order status and availability are fetched through your APIs at call time, and scope limits are written into every agent.
The agent quotes your system of record, and hands to a human the moment it is out of scope.
Every call is recorded, transcribed and scored against that agent's own criteria. The grading is identical whichever model placed the call.
Quality becomes a number you can filter on, not a sample someone listened to on Monday.
We Helped a Global IT Management Services Firm Build an Al-Powered Voice Service Desk for Enterprise ITSM
We Helped a Healthcare Staffing Company Build a Voice Al Recruiter for Al-Led Hiring at Scale
We connect to the numbers and trunks you already pay for, so nothing is ported and no hardware changes. A single queue is usually live within days, running alongside your team rather than replacing it.
Bounded, repeatable calls: appointment booking, order and delivery confirmation, payment reminders, renewals, lead qualification and status checks. Anything needing judgement is passed to a person.
It reads and writes through your APIs during the call, so account details and order status come from your records. Every call event fires a webhook, so your CRM stays current without manual entry.
The full rate is shown while you build the agent, split across the AI model, telephony and platform, so you see it before you spend it. You pay per minute of conversation, with no per seat licence.
Every call is recorded, transcribed and scored against criteria you define for that agent, identically whichever model placed it. You can filter your whole history by any criterion instead of sampling.
