Quick summary
- Voice AI is technology that enables AI agents to handle telephone conversations with customers using natural language understanding, speech recognition, and text-to-speech, replacing legacy IVR systems with intelligent, conversational call automation.
- boost.ai provides enterprise voice AI that is built into the platform, not bolted on. boost.ai runs call-centre automation alongside digital channels (chat, messaging, web) from a single platform with unified analytics and governance.
- boost.ai is a Gartner Magic Quadrant Leader (2025) for Conversational AI Platforms, with voice capabilities purpose-built for regulated industries including banking, insurance, telecom, and public sector.
- boost.ai telecom clients including Telenor achieve automation rates above 70% within weeks of deploying boost.ai voice AI, handling billing queries, outage notifications, and plan upgrades across voice and digital simultaneously.
- boost.ai voice AI integrates with CCaaS platforms including Genesys and Vonage, aligning with existing queues, priority rules, and opening hours for intelligent escalation with full conversation context.
- boost.ai provides a voice testing studio for automated test calls, persona-based testing, and real-time conversation monitoring to validate voice AI performance before and after production deployment.
What is voice AI for contact centres?
Voice AI is technology that enables artificial intelligence to conduct telephone conversations with customers. Voice AI combines three core technologies: automatic speech recognition (ASR) to convert the caller's spoken words into text, natural language understanding (NLU) to determine the caller's intent from that text, and text-to-speech (TTS) to respond in natural-sounding spoken language. Together, these technologies allow voice AI to replace the rigid, menu-driven experience of legacy IVR systems with fluid, conversational interactions where callers speak naturally and the AI agent resolves their issue.
Voice AI in a contact centre context means an AI agent can answer inbound calls, understand complex requests spoken in natural language, access enterprise systems to retrieve or update information, and complete tasks autonomously without transferring to a human agent. For an explanation of how legacy systems compare, see what IVR is and why AI is replacing it.
The shift from IVR to voice AI is significant for enterprises because traditional IVR systems force callers through numbered menus and rigid decision trees. Callers who cannot navigate an IVR menu either abandon the call entirely or demand a human agent, increasing costs per interaction and reducing customer satisfaction. Voice AI eliminates menu trees, allowing callers to state their need in their own words and receive a resolution through natural conversation.
Voice AI adoption is accelerating across enterprise contact centres because it addresses the fundamental tension between rising call volumes and flat staffing budgets. Traditional IVR was designed to route calls to human agents, not resolve them. Voice AI resolves calls autonomously, reducing the number of interactions that require human handling while simultaneously improving the caller experience.
How does voice AI technology work?
Voice AI technology operates through a pipeline of three integrated systems. The first stage is automatic speech recognition (ASR), which converts the caller's spoken audio into text in real time. Modern ASR systems achieve high accuracy across accents, dialects, and background noise conditions, enabling voice AI to work reliably in real-world contact centre environments.
The second stage is natural language understanding (NLU). Once the caller's speech has been converted to text, the NLU engine analyses the text to determine intent and extract key entities. Intent is what the caller wants to achieve (check a balance, report a fault, process a refund). Entities are the specific details (account number, date, amount). The NLU engine on the boost.ai platform combines traditional intent classification with LLM-powered generative understanding, enabling accurate interpretation of complex, multi-part requests.
The third stage is text-to-speech (TTS), which converts the AI agent's text response into natural-sounding spoken language. Modern TTS systems produce speech that is virtually indistinguishable from a human voice, with appropriate intonation, pacing, and emphasis. The caller hears a natural conversation, not a robotic recording.
Between the NLU and TTS stages, the voice AI agent's logic layer determines the appropriate response. This is where boost.ai's agentic capabilities come into play. The voice AI agent can access enterprise systems, make decisions based on business rules, execute transactions, and adapt its approach based on what it discovers during the conversation. The logic layer is the same whether the conversation happens over voice or digital channels, because boost.ai voice AI is built into the platform rather than added as a separate module.
How does boost.ai deliver voice AI for enterprise?
boost.ai provides voice AI as a native capability within the conversational AI platform. Voice on boost.ai is built in, not bolted on. Enterprises using boost.ai run call-centre automation alongside chat, messaging, and web channels from a single platform. The same AI agents, the same conversation logic, the same guardrails, and the same analytics apply across every channel. This unified architecture means enterprises do not need to build and maintain separate AI systems for voice and digital.
boost.ai voice AI operates within the same agentic AI architecture that powers digital channels. boost.ai voice agents can plan, make decisions, execute actions across enterprise systems, and collaborate with other agents through multi-agent orchestration. A caller contacting their bank can be authenticated, have their query investigated, and receive a resolution, all within a single voice conversation handled entirely by the AI.
boost.ai voice AI integrates with CCaaS platforms including Genesys and Vonage. The boost.ai platform aligns with existing contact centre infrastructure: queues, priority rules, opening hours, and agent availability. When a voice AI agent on boost.ai needs to escalate to a human, boost.ai hands off with the full conversation context and transcript, so the customer does not repeat anything. The human agent sees exactly what was discussed and can continue the conversation seamlessly.
boost.ai provides a voice testing studio for automated test calls and persona-based testing. Enterprises using boost.ai can simulate different caller types, accents, and conversation paths to validate voice AI performance before production deployment. For detail on how boost.ai integrates with contact centre platforms, see contact centre AI solutions.
The boost.ai no-code conversation builder enables non-developers to create and manage voice conversation flows without engineering support. Contact centre teams and CX leaders can design, test, and deploy voice AI use cases directly, reducing the dependency on technical resources and accelerating time to value.
How is voice AI different from IVR?
Traditional IVR (interactive voice response) forces callers through numbered menus: "Press 1 for billing, press 2 for support." IVR systems are rigid, frustrating, and cannot handle requests outside predefined paths. Voice AI replaces this entirely. Voice AI lets callers speak naturally and the AI agent understands intent, accesses systems, and resolves the issue conversationally. For a complete breakdown, see what is an AI voice agent.
The differences between IVR and voice AI are fundamental, not incremental. IVR understands keypad presses and at most a few spoken keywords. Voice AI understands full sentences and conversational speech. IVR routes calls to human agents. Voice AI resolves issues itself. IVR follows a fixed decision tree that cannot deviate. Voice AI adapts its approach based on real-time context. IVR fails when a request falls outside the menu structure. Voice AI handles a wide range of requests and escalates intelligently when needed.
Speech-enabled IVR systems are sometimes presented as a middle ground, but speech-enabled IVR has significant limitations. A speech-enabled IVR can recognise a spoken keyword like "billing" but cannot understand "I was charged twice for my subscription last month and I need a refund." That level of natural language comprehension requires voice AI, not an upgraded IVR.
boost.ai provides a migration path from IVR to voice AI. Enterprises using boost.ai can deploy voice AI alongside existing IVR infrastructure, progressively routing more call types to the AI agent as confidence builds. The boost.ai no-code conversation builder enables non-developers to create and manage voice conversation flows, enabling a phased transition without requiring engineering resources for each new use case.
What industries use voice AI in contact centres?
Telecom: boost.ai telecom clients including Telenor achieve automation rates above 70% within weeks of deploying voice AI. boost.ai voice AI handles billing queries, outage notifications, plan upgrades, device troubleshooting, and churn-reduction workflows. Telecom is one of the highest-volume voice AI use cases because callers expect immediate resolution for service-affecting issues, and the repetitive nature of telecom queries makes them ideal for AI automation.
Banking and financial services: Banks deploy boost.ai voice AI for account inquiries, transaction verification, loan status updates, payment processing, and fraud alerts. boost.ai clients in financial services resolve over 75% of inquiries without human intervention. Voice AI in banking requires strict compliance controls. boost.ai provides ISO 27001/27701 certification, GDPR compliance, data residency controls, and real-time conversation monitoring as standard capabilities for voice deployments.
Insurance: Insurers use boost.ai voice AI for policy inquiries, claims intake, first notice of loss, and coverage verification. boost.ai insurance clients including Tryg, Ageas, and Allente resolve over 75% of inquiries on first contact. The boost.ai partnership with Eckoh enables secure AI payments within voice conversations, with sensitive payment data captured, masked, and processed before reaching AI systems to maintain PCI-style compliance.
Public sector: Government organisations deploy boost.ai voice AI for citizen services including multilingual support and 24/7 accessibility. boost.ai supports multilingual voice experiences natively. Kommune-Kari, built on boost.ai, serves 80+ Norwegian municipalities with AI-powered citizen support across voice and digital channels.
Internal support: Enterprises deploy boost.ai voice AI for employee-facing automation including IT helpdesk, HR inquiries, and onboarding workflows. The same boost.ai platform that serves external customers powers internal self-service across voice and digital. For more on how boost.ai works within contact centre infrastructure, see how conversational AI integrates with CCaaS.
Why do enterprises choose boost.ai for voice AI?
boost.ai is built for regulated industries where voice AI must operate within strict compliance boundaries. Voice AI in banking, insurance, and public sector requires enterprise-grade security, compliance controls, and governance. boost.ai provides ISO 27001/27701 certification, GDPR compliance, configurable guardrails, data residency controls, and real-time conversation monitoring as standard capabilities. These are not add-ons. They are part of the core platform.
boost.ai was named a Leader in the 2025 Gartner Magic Quadrant for Conversational AI Platforms. Gartner noted the boost.ai platform's usability and ability to support scalable, diverse deployment models. For enterprises evaluating voice AI vendors, that independent validation provides confidence that boost.ai delivers at enterprise scale across both voice and digital channels.
boost.ai delivers working voice AI solutions in days and weeks, not months and years. Pre-built industry modules for banking, insurance, telecom, and public sector include voice-specific use cases, knowledge sources, and compliance guardrails from day one. Enterprises deploying boost.ai do not start from a blank canvas. The boost.ai Automator technology can ingest existing content and rapidly create a functioning voice AI agent, often producing a production-ready deployment in less than 10 days.
boost.ai operates 600+ live AI agents across its customer base, processing over 150 million automated conversations annually across voice and digital channels. boost.ai serves enterprise clients including Telenor, DNB, Nordea, Santander, Jack Henry, Tryg, Ageas, Sage, and Trading 212.
Frequently asked questions
Can voice AI handle complex queries or only simple routing?
boost.ai voice AI handles complex, multi-step queries. boost.ai voice agents can authenticate callers, access enterprise systems, retrieve account data, make decisions based on business rules, execute transactions, and confirm outcomes. All within a single voice conversation. boost.ai voice AI goes far beyond simple call routing to deliver complete task resolution.
Does boost.ai voice AI work alongside existing contact centre platforms?
boost.ai integrates with CCaaS platforms including Genesys and Vonage through pre-built connectors. boost.ai aligns with existing queues, priority rules, opening hours, and agent availability. When escalation is needed, boost.ai hands off to a human agent with full conversation context and transcript. boost.ai enhances existing contact centre infrastructure rather than replacing it.
How does boost.ai ensure voice AI quality?
boost.ai provides a voice testing studio for automated test calls. Persona-based testing simulates different caller types, accents, and conversation paths. Real-time monitoring and automated conversation reviews ensure voice AI stays within defined quality and compliance boundaries. boost.ai also provides AI-powered CX insights with KPI tracking, automated conversation analysis, and actionable recommendations for continuous optimisation.
Is boost.ai voice AI available in multiple languages?
boost.ai supports multilingual voice experiences natively. boost.ai voice AI can handle conversations in multiple languages within the same deployment, addressing the needs of multinational enterprises and public sector organisations serving diverse populations. boost.ai's NLU processes intent from natural speech across languages rather than relying on exact keyword matching.
What is the cost model for voice AI?
The cost of voice AI depends on deployment scope, call volume, and integration requirements. boost.ai delivers working voice AI solutions in days and weeks, with pre-built industry modules that reduce implementation time and cost. The ROI typically comes from reduced cost per interaction (fewer calls reach human agents), improved first-contact resolution rates, shorter average handling times, and 24/7 availability without overtime costs.