AI Agents and Voice AI: How Artificial Intelligence Is Transforming Sales and Customer Support

Contact centers are among the most expensive, yet most critical, touchpoints with customers. Each call costs a company roughly €3 to €15. Long wait times translate directly into lost opportunities — and often lost customers.

Today, artificial intelligence offers a solution that was nearly out of reach just a few years ago: AI agents that can speak, understand, and resolve customer inquiries independently — 24/7.

In this guide, you will learn how AI agents and Voice AI work, why Kinetara — FrodX’s conversational AI platform — is leading this shift, and how companies across the region are already achieving measurable cost savings and improved customer satisfaction. 

An AI agent is a software-based agent that communicates with customers in natural language — either text or voice — while performing specific tasks.

Modern AI agents, powered by large language models (LLMs), understand conversational context, ask clarifying questions, and take action: checking order status, booking appointments, creating support tickets, or completing transactions.

The difference between first-generation chatbots and modern AI agents becomes clear when conversations move beyond predefined scripts. Chatbots relied on rules and decision trees; AI agents are generative — they understand varied phrasing, maintain context, and adapt dynamically.

Core components of an AI agent:
• Natural Language Understanding (NLU): identifying intent and key data.
• Response generation (LLM): contextual, human-like replies.
• Backend integrations: CRM, ERP, knowledge bases, ticketing systems.
• Orchestration: managing multi-step workflows and human handoff.

Voice AI brings conversational intelligence to the phone channel. Voice agents understand speech in real time (speech-to-text), process requests, and respond with natural-sounding voices (text-to-speech).

When implemented well, the experience is seamless — without awkward pauses or the feeling of speaking to a machine.

Voice AI does not replace teams. It augments them. Routine inquiries are handled by AI, while complex cases are routed to human agents — complete with summaries and context.

Common use cases:
• Inbound calls: handling multiple conversations simultaneously.
• Outbound campaigns: reminders and confirmations.
• Bookings: scheduling, changes, cancellations.
• Customer support: order status, returns, complaints.
• Lead qualification: initial screening and routing to sales.

Kinetara is a conversational AI platform designed for mid-sized and enterprise businesses in the region. Its key advantage lies in localization for Slovenian, Croatian, and English — going beyond “good enough” toward real operational use.

Kinetara works as a layer on top of existing systems (CRM, ERP, contact center, telephony), enhancing them with AI capabilities where they matter most.

Typical implementation takes 6–10 weeks.

Why Kinetara
• Multilingual support out of the box.
• No forced system replacement.
• Integrations with HubSpot, Salesforce, SAP, and more.
• Brand customization: voice, tone, personality.
• Analytics and control: insights into conversations and outcomes.

Kinetara is most often deployed where repetition is highest and response time matters most.

In sales, voice agents handle initial interactions, collect key information, and qualify leads before passing them to sales teams with full context.

In customer support, agents resolve a large share of standard inquiries without human involvement, escalating complex cases with full conversation history.

In booking scenarios (healthcare, services, hospitality), Voice AI enables 24/7 scheduling, reduces no-shows through reminders, and improves capacity utilization. 

An AI agent without integration is often just a compelling demo. Real value emerges when it connects to your systems and gains context: who is calling, what they purchased, which issues are open, and what was agreed previously.

This leads to faster, more relevant, and highly personalized interactions.

Kinetara integrates via standard APIs with most CRM and CDP platforms (e.g., HubSpot, Salesforce, SAP, Emarsys), as well as ticketing systems and contact center solutions when needed.

With Voice AI, success is highly measurable because it directly impacts cost and availability.

The most common KPIs include cost per call, first contact resolution (FCR), average handling time (AHT), NPS, and the share of calls resolved without escalation.

Typical results with Kinetara include: 
40–65% reduction in cost per call 
15–25% improvement in FCR 
Reduced AHT 
10–20 point increase in NPS within six months

Kinetara’s dashboard provides real-time insights and enables faster optimization. 

1. Process analysis: identify the most frequent and repetitive inquiries.
2. Use case definition: inbound support, outbound communication, or hybrid?
3. Integration: CRM, ticketing, telephony, knowledge bases.
4. Content preparation: responses, rules, scenarios, and constraints.
5. Testing and refinement: simulations, shadow mode, human review.
6. Gradual rollout: start with 10–20% of traffic, then scale.
7. Monitoring and optimization: continuous quality improvement. 

Companies adopting AI agents are not replacing teams. They are augmenting them. Routine tasks are handled by technology, while people focus on high-value work: complex cases, relationship building, and situations that require judgment and empathy.

Kinetara and FrodX act as partners in this transformation — from initial use case to full production deployment.