Daniel Saks
Chief Executive Officer
Voice AI funding surged 8x in 2024 to $2.1 billion as enterprises race to automate customer interactions and developers build the next generation of conversational experiences. The global voice and speech recognition market was valued at $15.46 billion in 2024 and is projected to reach $81.59 billion by 2032, representing a fundamental shift in how businesses and consumers interact with technology. From ElevenLabs' $3.3B valuation to emerging platforms like Sesame raising $250M, these companies are defining the future of voice-first AI. For go-to-market teams leveraging AI to find and engage ideal customers, platforms like Landbase's agentic AI now complement these voice technologies by enabling natural-language audience discovery and qualification without requiring complex technical infrastructure.
ElevenLabs is the market-leading voice synthesis platform that provides industry-leading text-to-speech (TTS) with emotional expressiveness and voice cloning capabilities in 30+ languages. The platform offers real-time voice synthesis API that powers millions of conversations monthly through partners and direct customers. ElevenLabs is expanding beyond voice to become a multimodal AI agents platform capable of talking, typing, and executing actions.
ElevenLabs pioneered emotionally expressive text-to-speech technology with voice cloning capabilities across 30+ languages, setting the industry standard for natural-sounding AI voices. The platform powers millions of conversations monthly and is expanding from pure voice synthesis into a comprehensive multimodal AI agents platform. Market recognition includes achieving a $3.3 billion valuation in January 2025, making it one of the most valuable pure-play voice AI companies globally.
Deepgram provides enterprise-grade speech recognition infrastructure with industry-leading accuracy and sub-300ms real-time streaming latency. The company's Nova-2 model achieves significant word error rate improvements compared to competitors, and its Voice Agent API enables enterprise deployments with HIPAA/GDPR compliance. Deepgram processes billions of minutes of audio annually for thousands of organizations including major tech platforms.
Deepgram pioneered real-time speech-to-text infrastructure with enterprise-grade accuracy and sub-300ms latency that enables responsive voice AI applications. The Nova-2 model delivers a 36.4% relative Word Error Rate improvement over OpenAI's Whisper model, setting new accuracy benchmarks. Enterprise adoption is demonstrated through HIPAA/GDPR compliance and processing billions of audio minutes annually for thousands of global organizations.
PolyAI specializes in enterprise voice AI agents for contact center automation, supporting 45 languages across 25+ countries. The company's Agent Studio platform provides enterprise governance capabilities, and it has deployed thousands of live implementations for enterprise customers across hospitality, banking, and retail sectors.
PolyAI pioneered purpose-built voice AI specifically for contact center automation with multilingual support across 45 languages in 25+ countries. The Agent Studio platform provides enterprise governance and customization capabilities that traditional IVR systems lack. Proven ROI is demonstrated through a Forrester Total Economic Impact study commissioned by PolyAI showing 391% return and $10.3M average customer savings.
Retell AI provides a complete IVR replacement platform that supports voice, chat, email, and SMS omnichannel communication. The platform features call monitoring capabilities with quality assurance tools and powers millions of real-time AI phone calls monthly. Retell AI offers complete automation across all communication channels for enterprises.
Retell AI pioneered the first complete IVR replacement spanning voice, chat, email, and SMS in a unified platform. The platform includes built-in quality assurance with comprehensive call monitoring capabilities that ensure consistent customer experiences. Rapid growth is demonstrated through processing millions of AI-powered phone calls monthly with expanding enterprise adoption.
Funding details not publicly disclosed; company demonstrates strong growth metrics and enterprise adoption.
Speechmatics provides real-time speech recognition platform with sub-250ms partial transcript delivery and support for 50+ languages including Nordic and Arabic dialects. The company offers specialized medical models with high keyword recall and powers live captioning for major global broadcasters. Speechmatics serves healthcare, media, and enterprise customers with accurate multilingual transcription.
Speechmatics delivers real-time speech-to-text with sub-250ms latency enabling responsive voice applications across 50+ languages including underserved dialects. Specialized medical models achieve 96% keyword recall for healthcare documentation and clinical workflows. The platform powers mission-critical applications including live broadcast captioning for the world's largest media organizations.
Company is backed by Susquehanna Growth Equity and other investors; specific recent funding details not publicly disclosed.
SoundHound AI provides a comprehensive voice AI and conversational intelligence platform featuring the Houndify independent voice AI platform and proprietary Speech-to-Meaning® technology for instant interpretation. The company serves major automotive, restaurant, and enterprise clients and recently acquired Amelia AI to expand its enterprise capabilities. SoundHound is a publicly-traded pure-play voice AI company.
SoundHound AI is the only major publicly-traded pure-play voice AI company, providing market transparency and investment access. The proprietary Speech-to-Meaning® technology enables instant query interpretation without intermediate speech-to-text conversion, reducing latency. The Houndify platform powers voice experiences across automotive, IoT, hospitality, and enterprise applications with a significant bookings backlog.
SoundHound AI is publicly traded (NASDAQ: SOUN) and raises capital through public equity markets rather than venture funding rounds.
Speechify is a consumer-focused voice AI application that provides text-to-speech reading across documents and web content, voice AI assistant for iOS with multi-turn conversations, and voice typing dictation that's significantly faster than manual typing. The platform has achieved millions of users with hundreds of thousands of five-star reviews and won the 2024 Apple Design Award, demonstrating voice AI's consumer market potential.
Speechify achieved rare consumer-scale adoption with millions of users, demonstrating voice AI's mainstream appeal beyond enterprise applications. The platform won the 2024 Apple Design Award for innovation and design excellence. Speechify is expanding into agentic voice workflows for task automation while maintaining accessibility through freemium pricing across Mac, iOS, and Chrome extension platforms.
Company operates on freemium model with premium subscriptions; specific funding details not publicly disclosed.
Vapi provides a developer-first voice AI platform positioned as the "Twilio for AI agents" with granular control over voice agent components and sub-400ms real-time latency. The platform enables technical teams to build custom voice AI solutions with maximum flexibility, supporting custom model integration and component swapping. Vapi offers API-based access for developers building voice-enabled applications.
Vapi pioneered a developer-first platform offering maximum flexibility and granular control over voice AI components, unlike higher-level no-code alternatives. The "Twilio for AI agents" positioning provides API-based access that technical teams prefer for custom integrations. Sub-400ms real-time latency enables responsive conversational experiences while supporting custom model integration and component-level customization.
Company is venture-backed; specific funding details not publicly disclosed but recognized as a leading developer platform.
Bland AI provides an enterprise voice AI platform built for massive scale deployments, supporting high-concurrency voice operations for millions of calls. The platform offers custom voice model training and cloning, multi-region hosting with enterprise APIs, and is built as a full-stack platform from the ground up without relying on third-party components. Bland AI's programmer-friendly API enables automated phone calls at enterprise scale.
Bland AI pioneered a full-stack voice AI platform built from the ground up for massive scale without reliance on third-party infrastructure components. The platform supports high-concurrency operations enabling millions of simultaneous calls for enterprise deployments. Custom voice model training, multi-region hosting, and enterprise-grade APIs deliver the reliability and performance large organizations require.
Company is venture-backed and rapidly growing; specific funding details not publicly disclosed.
Synthflow AI provides a no-code voice AI platform with drag-and-drop builder that enables non-technical teams to create voice AI solutions. The platform supports inbound/outbound calls with batch calling capabilities and offers native CRM and SIP integration. Starting at $29/month, Synthflow makes voice AI accessible to mid to large businesses without requiring technical expertise.
Synthflow AI democratizes voice AI access through a no-code drag-and-drop builder enabling non-technical teams to deploy voice agents. Native CRM and SIP integration eliminates custom development work for common enterprise systems. Accessible pricing starting at $29/month with real-time analytics and performance monitoring brings enterprise-grade voice AI to businesses of all sizes.
Company is venture-backed; specific funding details not publicly disclosed.
Rime AI specializes in ultra-realistic voice synthesis using its proprietary Arcana model that includes natural laughs, sighs, and breathing patterns for the most realistic spoken language. The company powers millions of monthly phone conversations for enterprise customers including major restaurant chains. Rime AI has open-sourced its Rimecaster speaker representation model and uses a proprietary dataset of real conversations rather than audiobooks.
Rime AI pioneered ultra-realistic voice synthesis with natural paralinguistic features including laughs, sighs, and breathing patterns that previous models lacked. The proprietary Arcana model is trained on real conversations rather than audiobook narration, capturing authentic conversational dynamics. Enterprise adoption by major restaurant brands demonstrates the model's effectiveness for customer-facing applications requiring natural-sounding voices.
The voice AI landscape represents a fundamental shift in human-computer interaction, moving from text-based interfaces to natural voice conversations. This transformation is being driven by three key factors: improved speech recognition accuracy, reduced latency in voice processing, and more natural-sounding synthetic voices. As Chris McCann of Race Capital notes, "Voice is how people naturally communicate – but most voice AI systems still sound robotic or have high latency in their responses. Fast, expressive voice tech is critical to making AI feel human and useful in the enterprise."
Within this ecosystem, companies are specializing in different layers: infrastructure providers like Deepgram and Speechmatics offer the foundational speech-to-text and text-to-speech capabilities; enterprise platforms like PolyAI and Retell AI build complete solutions for specific use cases like contact center automation; and developer-first platforms like Vapi and Bland AI enable technical teams to build custom voice applications.
For B2B go-to-market teams, these voice AI capabilities can be complemented by AI-powered audience discovery platforms like Landbase's company data, which includes 1,500+ unique signals across firmographic, technographic, intent, hiring, and funding data. By first identifying high-intent prospects through natural-language queries and then engaging them through voice AI channels, organizations can create a complete end-to-end AI-powered go-to-market strategy.
This list highlights the 12 fastest-growing voice AI companies based on:
All companies included demonstrate significant momentum in the voice AI space, with quantifiable metrics supporting their growth trajectory. The list represents a balanced mix of infrastructure providers, enterprise platforms, developer tools, consumer applications, and emerging innovators.
While voice AI platforms focus on the conversation layer, successful go-to-market strategies require identifying the right prospects before initiating contact. This is where AI-powered audience discovery platforms become essential. Instead of manually querying databases or using complex filter builders, modern GTM teams can use natural-language interfaces like Landbase's VibeGTM to describe their ideal customer profile in plain English.
For example, a voice AI platform targeting enterprise contact centers could use a prompt like: "Contact center directors at companies with 1,000+ employees that use legacy IVR systems and have hiring managers posting for AI roles." Landbase's GTM-2 Omni AI model would then interpret this natural-language query, evaluate prospects using 1,500+ signals, and return an AI-qualified audience ready for immediate activation through voice AI outreach.
This combination of AI-powered audience discovery and voice AI engagement creates a powerful end-to-end go-to-market workflow that dramatically reduces time-to-value while improving targeting precision and engagement rates.
Voice AI platforms are primarily used for contact center automation, customer service virtual agents, voice-enabled enterprise applications, and voice commerce. The technology is particularly valuable for automating routine customer interactions, reducing operational costs, and improving customer experience through 24/7 availability. Healthcare applications include clinical documentation and patient engagement, while broadcasting uses voice AI for live captioning and accessibility. Enterprise adoption is accelerating as companies recognize the ROI potential, with some deployments achieving 391% returns according to commissioned Forrester research.
Voice AI startups secure funding through traditional venture capital channels, with funding surging significantly in recent years to reach $2.1 billion in 2024. Typical funding stages include seed rounds like Rime AI's $5.5M, Series A/B for product development and early customer acquisition like Sesame's $250M Series B, and later-stage rounds for scaling like ElevenLabs' $180M Series C and Deepgram's $130M round. Investor interest is driven by market growth projections showing the voice and speech recognition market expanding from $15.46B in 2024 to $81.59B by 2032 at a 23.1% compound annual growth rate.
Speech recognition (also called speech-to-text or STT) converts spoken audio into written text, while voice generators (also called text-to-speech or TTS) convert written text into spoken audio. Companies like Deepgram and Speechmatics specialize in speech recognition with industry-leading accuracy and low latency, while ElevenLabs leads in voice generation with emotional expressiveness and voice cloning capabilities. Both technologies are essential components of complete voice AI systems, with speech recognition enabling the system to understand what users say and voice generation enabling the system to respond naturally. Some platforms like SoundHound use proprietary Speech-to-Meaning® technology that bypasses intermediate text conversion for faster processing.
Contact centers and customer service are experiencing the most significant impact, with companies like PolyAI delivering proven ROI through automation. Healthcare is another major beneficiary, with specialized medical models achieving 96% keyword recall for clinical documentation and returning significant time to healthcare workforces. Broadcasting and media organizations use voice AI for live captioning and accessibility features at global scale. The automotive and restaurant industries have also seen substantial adoption, with platforms like SoundHound serving major clients in these sectors for voice-enabled ordering and in-vehicle experiences.
Companies like Landbase leverage AI for go-to-market by focusing on the audience discovery and qualification layer rather than the conversation layer. Landbase's GTM-2 Omni AI model interprets natural-language queries to build and qualify audiences instantly using 1,500+ signals across firmographic, technographic, intent, hiring, and funding data. This enables sales and marketing teams to identify high-intent prospects before engaging them through voice AI or other channels. The platform allows users to export AI-qualified contacts instantly without complex database queries, dramatically reducing the time and complexity of traditional prospecting workflows.
Tool and strategies modern teams need to help their companies grow.
