Popular Voice Assistant in Customer Support include Vapi, Telnyx, SoundHound AI, Notevibes, smallest.ai, Bolna, Cekura, Presto, Regal, and Phonely, helping you work more efficiently.
Phonely is an AI-powered phone answering platform that provides businesses with intelligent voice agents. It automates customer support, schedules appointments, and qualifies leads 24/7. Featuring human-like conversations in over 100 languages, seamless CRM integration, and advanced analytics, Phonely helps companies reduce costs and enhance customer satisfaction without missing a single call.
Voice Assistant
Presto is an AI-driven automation platform designed for the restaurant industry, specializing in revolutionizing drive-thru operations. Its flagship product, Presto Voice™, uses advanced voice AI to automate order-taking, improve staff efficiency, increase sales through consistent upselling, and enhance the overall guest experience with fast, accurate service.
Restaurant Management
SoundHound AI is a leading independent voice AI platform for enterprises, enabling the creation of advanced conversational agents. Leveraging decades of expertise, it offers custom solutions for automotive, restaurants, customer service, and more, focusing on high accuracy, data sovereignty, and enhanced user experiences.
In Car Entertainment
Smallest.ai provides enterprise-grade AI voice agents for contact centers, designed to automate and enhance customer interactions. It offers high-quality, low-latency Text-to-Speech (TTS), voice cloning, and a no-code builder to create human-like conversational AI for various industries like finance, real estate, and logistics.
Voice Assistant
Automaticall is an AI-powered voice assistant that answers your phone calls 24/7. It uses a human-like voice to handle customer inquiries, book appointments directly into your calendar, and filter spam calls. Ideal for businesses looking to capture every lead, improve customer service, and increase efficiency without hiring additional staff. It also offers a website widget to convert visitors into qualified leads through real-time voice interaction.
Voice Assistant
foreva (Eva AI) is an AI agent system designed for restaurants to automate phone calls, orders, and reservations 24/7. It captures every caller as a customer, sends personalized follow-ups, and integrates with POS systems like Square to increase revenue and operational efficiency without requiring extra staff effort.
Restaurant Management
Cekura is an AI-powered platform for testing and observability of conversational AI agents. It enables developers to automate the testing of voice and chat agents across thousands of scenarios, using various personas and real-world conditions to ensure reliability, prevent failures, and accelerate deployment.
Voice AssistantVoice Assistants are AI-powered tools designed to automate and manage voice-based customer interactions. Leveraging technologies like Automatic Speech Recognition (ASR) and Natural Language Understanding (NLU), these assistants can comprehend and respond to spoken queries in a human-like manner. Their primary value lies in providing 24/7, scalable customer support over the phone, handling routine inquiries, and routing complex issues to human agents. This significantly reduces wait times and operational costs within a customer support framework.
Voice Assistants are widely adopted in industries with high call volumes, such as telecommunications, banking, and e-commerce. They are used in call centers to automate Tier-1 support, handle appointment scheduling for healthcare providers, and manage outbound notification campaigns for logistics companies. Any business looking to modernize its Interactive Voice Response (IVR) system and improve call center efficiency can benefit.
When selecting a Voice Assistant, evaluate the accuracy of its speech recognition and NLU across different accents and languages. Assess its integration capabilities with your current tech stack, particularly your CRM and telephony systems. Consider the platform's scalability to handle fluctuating call volumes and the level of customization available for conversation flows. Finally, ensure it complies with industry-specific security and data privacy standards like GDPR or HIPAA.
A call center manager for an e-commerce company uses a Voice Assistant to handle the high volume of inbound calls regarding order status and returns. The AI authenticates callers, accesses order information from the CRM, and provides real-time updates. For complex issues like damaged goods, it gathers initial information and intelligently routes the call to a specialized human agent. This frees up agents to focus on high-value interactions, reducing average handling time by 40% and improving customer satisfaction by providing instant answers 24/7.
A healthcare clinic's operations manager implements a Voice Assistant to automate appointment reminders. The system calls patients two days before their scheduled visit, confirms the appointment time, and offers options to reschedule or cancel directly during the call. The AI updates the clinic's scheduling software in real-time based on the patient's response. This proactive approach reduces no-show rates by over 30%, optimizes the clinic's schedule, and frees up administrative staff from making hundreds of manual reminder calls each week.
An IT support lead for a software company deploys a Voice Assistant as the first point of contact for technical support calls. The assistant greets the user, asks for their account details, and uses natural language to understand the technical issue. It can resolve common problems like password resets or basic configuration issues by guiding the user through steps. For more complex issues, it creates a support ticket with all the gathered information and escalates it to the correct Tier-2 support team, providing the human agent with full context before they even speak to the customer.
A customer experience (CX) officer at a large bank replaces their outdated touch-tone IVR with a conversational Voice Assistant. Instead of navigating complex menus ('Press 1 for...'), customers can now state their needs in their own words, such as 'I want to check my account balance' or 'I lost my credit card'. The AI understands the intent and either provides the information directly after secure verification or routes the call to the fraud department. This dramatically improves the user experience, reduces call duration, and lowers call abandonment rates.
A sales development representative (SDR) team uses a Voice Assistant to make initial contact with inbound leads from web forms. The AI calls the lead, introduces the company, and asks a series of qualifying questions (e.g., budget, timeline, decision-making authority). Based on the responses, the assistant scores the lead and, if qualified, automatically schedules a demo with a human sales executive in their calendar. This ensures rapid lead follow-up and allows SDRs to spend their time on highly qualified prospects rather than initial screening calls.
A quality assurance manager at a telecommunications company uses a Voice Assistant to automatically conduct customer satisfaction (CSAT) surveys. Shortly after a customer interacts with support, the AI calls them to ask a few short questions about their experience, such as rating the service on a scale of 1 to 5 and providing open-ended feedback. The assistant uses sentiment analysis on the spoken feedback to identify highly dissatisfied customers for immediate follow-up by a manager. This automates the feedback collection process and provides real-time insights into service quality.
An AI Voice Assistant is a conversational AI program designed to handle customer phone calls automatically. It uses technologies like speech recognition and natural language understanding to interpret what a customer is saying and respond appropriately. Unlike basic automated systems, it can manage complex, multi-turn conversations, provide personalized information by integrating with business systems, and route calls to human agents only when necessary. Its main purpose is to provide instant, 24/7 support and improve call center efficiency.
The key difference lies in intelligence and flexibility. A traditional Interactive Voice Response (IVR) system uses a rigid, touch-tone menu ('Press 1 for sales, Press 2 for support'). It cannot understand natural language. An AI Voice Assistant, however, uses conversational AI to allow callers to state their needs in their own words. It understands intent, can ask clarifying questions, and handles complex queries, creating a much more natural and efficient user experience. Essentially, it replaces a frustrating menu tree with a real conversation.
Choosing the right Voice Assistant involves evaluating several key factors. First, assess its core technology: how accurate is its speech recognition and natural language understanding, especially with industry-specific jargon or diverse accents? Second, check its integration capabilities with your existing CRM, helpdesk, and telephony systems. Third, consider scalability and customization options to ensure it can grow with your business and adapt to your specific workflows. Finally, verify its security and compliance credentials to ensure it meets data protection standards relevant to your industry.
A robust customer support Voice Assistant should have several key features. High-accuracy Automatic Speech Recognition (ASR) and Natural Language Understanding (NLU) are fundamental. It needs seamless integration capabilities with CRM and helpdesk software to personalize interactions. Intelligent call routing is crucial for escalating complex issues to the right human agent. Additionally, features like sentiment analysis to detect customer frustration, voice biometrics for security, and multilingual support to serve a global audience are highly valuable.
Industries with high call volumes and repetitive customer inquiries benefit the most. This includes:
