AIVA — AI agent for business, voice AI

Aiva

Inbound call handling without queues or losses

We receive inbound requests, resolve common questions, qualify the customer, and route them through the right path without overloading the frontline.

This service is most valuable for businesses with a high inbound flow: clinics, service centers, e-commerce, support teams, and distributed sales organizations.

The goal is not only to answer the call, but to give the customer a clear next step quickly, capture context, and avoid losing the request between systems and shifts.

24/7

Line availability and first response

SLA

Speed and quality control

CRM sync

Automatic call data logging

Escalation

Complex cases passed to humans

Why it works

The service is built around the real customer journey

Why it works

24/7 inbound availability

The line stays available outside working hours, during peaks, and when operator load is uneven.

Why it works

Context-based routing

Typical questions are handled automatically while complex cases are sent to the right team with a short call summary.

Why it works

Stable customer experience

The same answer standard, one qualification logic, and clean result logging after every call.

What we automate

Frontline without queues

The AI operator greets the customer immediately, answers routine questions, and prevents drop-off during the first minute.

What we automate

Escalation to staff

When a call requires a human, we pass it on with collected context and request classification.

What we automate

CRM and calendar integrations

Call data, request status, and agreements automatically land in your operating system.

Outcome

Fewer missed calls

The number of lost requests and first-line bottlenecks drops even when team workload is uneven.

Outcome

Fast initial response

Customers get a clear reaction sooner without the need to constantly scale the support frontline for every peak.

Outcome

Predictable request handling

Requests are handed off cleanly into sales, support, or booking while service remains stable at any time.

How launch works

From common requests to production

01

Review real customer questions

We collect frequent requests, routing rules, and inbound SLA requirements.

02

Build the first-line scenario

We configure responses, clarifying questions, transfers to staff, and post-call data capture.

03

Validate with live cases

We run test scenarios and refine tone, routing accuracy, and data completeness.

04

Launch and improve from analytics

We review misses, transfer reasons, and handling quality, then iterate on the scenario.

Discuss implementation

We will review the task, propose a launch architecture and show where automation will pay off fastest.