Best voice agents for customer support in 2025

Best voice agents for customer support in 2025

Legacy IVR systems are driving customers away. With 70% of CX leaders now believing generative AI makes every digital interaction more efficient, it's clear that the push for better voice agents is happening now. In fact, 42% see voice-based interactions as the next frontier for AI transformation.

The shift from rigid phone trees to conversational voice agents isn't just about technology, it's about economics. Budget-conscious teams need transparent per-minute costs, proven latency benchmarks, and seamless CRM integration before committing to production deployments.

This guide evaluates the leading voice agents for customer support based on what matters for enterprise rollouts: accuracy, latency, telephony integration, compliance readiness, and total cost of ownership.

What to evaluate when choosing a voice agent

Not all voice AI platforms deliver production-grade performance. Companies building with voice represented 22% of the most recent YC class, but integration gaps and hidden costs separate pilot projects from scalable deployments.

Evaluate providers on these criteria:

1. Telnyx Voice AI Agents

Telnyx delivers the only platform that unifies carrier-grade telephony infrastructure with voice AI on a single stack. By colocating dedicated GPUs directly with global telecom points of presence, Telnyx eliminates the latency and integration headaches that plague multi-vendor deployments.

Why Telnyx leads for customer support:

Full-stack control from PSTN to inference: Most voice AI providers lack telephony networks, forcing teams to integrate third-party SIP trunking and number provisioning. Telnyx operates as a licensed telecom provider in 30+ markets with PSTN calling in 100+ countries. Provision numbers, configure SIP trunks, and deploy AI agents in one platform.

Ultra-low latency through infrastructure colocation: Physics limits voice quality when data travels between distant data centers. Telnyx colocates GPU infrastructure at telecom PoPs, minimizing round-trip delays to under 200ms.

$0.09 per minute all-in pricing: While competitors charge separately for STT, TTS, LLM inference, and telephony, Telnyx bundles everything at $0.09/min, 10x cheaper than cloud-based AI solutions. No surprise bills, no hidden carrier fees.

Open-source AI flexibility: Run leading open-source models or bring your own fine-tuned LLMs. Telnyx maintains a continuously updated library of models, letting teams experiment without vendor lock-in.

Enterprise compliance and support: SOC 2, HIPAA, and GDPR compliance built in, with regional deployments for data sovereignty. Free 24/7 engineering support means faster issue resolution than competitors charging for premium support tiers.

Best for: Organizations needing production-grade voice AI with predictable economics and full infrastructure control. Especially valuable for healthcare, finance, and contact centers handling sensitive data or high call volumes.

2. ElevenLabs

ElevenLabs built its reputation on high-quality voice synthesis. Their conversational AI product extends TTS capabilities into full voice agents, with particular strength in voice cloning and multilingual support.

Strengths: Best-in-class voice quality and natural prosody. Strong support for voice cloning and brand-specific voice creation. Growing library of pre-made voices.

Limitations: No native telephony infrastructure—requires third-party integrations for PSTN connectivity. Higher pricing for production deployments. See how alternatives like Telnyx compare on telephony integration and total cost.

Best for: Marketing and content teams prioritizing voice quality over telephony infrastructure. Less ideal for contact centers needing carrier-grade reliability.

3. Vapi

Vapi focuses on rapid voice AI deployment with pre-built templates and low-code tools. Their platform targets developers who want to ship voice agents quickly without deep telephony expertise.

Strengths: Fast time-to-market with pre-configured workflows. Developer-friendly API design. Growing template library for common use cases.

Limitations: Limited infrastructure control compared to full-stack platforms. Pricing can escalate at scale. Compare Telnyx, ElevenLabs, and Vapi on performance and control tradeoffs.

Best for: Startups and SMBs prioritizing speed over customization. Teams comfortable with template-based approaches.

4. Retell AI

Retell AI specializes in voice agents for appointment scheduling and qualification calls. Their platform emphasizes turn-key deployment with minimal technical setup.

Strengths: Simple setup for common customer support workflows. Focus on scheduling and qualification reduces scope creep. Pre-built integrations with popular calendar tools.

Limitations: Less flexibility for complex conversational flows. Limited customization options may not fit unique business requirements.

Best for: Small teams with straightforward scheduling and qualification needs. Not ideal for nuanced customer support requiring deep context.

5. Bland AI

Bland AI targets outbound calling with a focus on appointment reminders, follow-ups, and proactive customer engagement.

Strengths: Outbound-focused features like automatic retry logic and time-zone handling. Competitive pricing for simple outbound campaigns.

Limitations: Primarily designed for outbound, with fewer features for complex inbound support. Limited advanced conversational AI capabilities.

Best for: Teams running high-volume outbound campaigns. Less suited for inbound customer support requiring sophisticated NLU.

Why support teams are betting on voice AI

The business case for voice agents extends beyond deflection rates. Employees and customers alike are warming up to AI-powered interactions, especially in support settings where speed and clarity matter most. While only 29% of workers using AI say it has significantly improved the quality of their work, most see clear efficiency gains, around 80% report higher productivity thanks to AI-driven tools

As one support professional told HubSpot: "What I've found is that AI helps me actually do my job better. With the help of AI, I'm able to deliver more white glove treatment to customers."

Voice agents handle routine inquiries while human agents focus on complex issues requiring empathy and judgment. 71% of customers believe AI can make service more empathetic, and 67% want AI that adjusts its tone depending on how they feel. Another 68% of customers believe chatbots should match highly skilled human agents in expertise.

Building vs. buying voice AI infrastructure

Organizations face a build-or-buy decision when deploying voice agents. Buying managed solutions offers faster deployment but less control. Building on platforms like Telnyx provides infrastructure flexibility without starting from scratch.

Managed solutions work when:

• Use cases fit pre-built templates
• Small teams lack engineering resources
• Speed matters more than customization

Full-stack platforms work when:

• Unique workflows require custom logic
• Compliance demands data sovereignty
• Scale requires predictable per-minute economics
• Integration with existing CRM and telephony is critical

Telnyx makes building voice agents straightforward with carrier-grade infrastructure, streaming APIs, and transparent documentation. Teams control the entire voice pipeline without managing telephony backend complexity.

Implementation checklist for production deployments

Moving from pilot to production requires more than choosing a vendor. Successful deployments hinge on stress-tested infrastructure, compliance audits, and clear escalation protocols, areas where rushed implementations typically fail.

Before deploying voice agents:

Test latency benchmarks under load: Pilot performance rarely matches production. Run stress tests simulating peak call volumes across geographies. Review latency comparisons to set realistic SLAs.

Audit compliance requirements early: HIPAA, PCI-DSS, and GDPR compliance can't be retrofitted. Healthcare organizations especially need certified infrastructure from day one.

Map integration complexity: Native CRM connectors reduce development time, but custom workflows may require API work. Evaluate webhook support, rate limits, and observability tools.

Model TCO beyond per-minute rates: Factor in support costs, integration hours, and scaling economics. Platforms bundling STT, TTS, and inference simplify budgeting.

Plan agent training and escalation paths: Voice AI augments human agents but doesn't replace training. Build handoff protocols for complex scenarios.

What's next for voice AI in customer support

70% of CX leaders plan to integrate generative AI into many customer touchpoints within two years, and voice is leading adoption. 57% anticipate chat-based support being heavily influenced by AI, but voice channels offer higher engagement and faster resolution.

The customer experience management market is expected to grow at 15.8% CAGR through 2030, driven by AI automation and personalization demands. Voice agents will capture an increasing share as latency improves and costs drop.

Organizations evaluating voice AI today have a window to build competitive advantages before voice becomes table stakes. The platforms offering full-stack control, transparent pricing, and carrier-grade reliability will define the next generation of customer support.

*Ready to deploy voice agents that scale? Telnyx unifies carrier-grade telephony with low-latency AI on a single platform, no third-party integrations, no surprise costs. Get predictable $0.09/min pricing, sub-200ms RTT latency, and 24/7 engineering support. Start building on Telnyx's global network or compare the top voice AI providers to see how unified infrastructure delivers better outcomes at lower cost.*