Table of Contents

• Why Voice AI Is the New Call Center Baseline

• What to Evaluate in an AI Voice Agent

• The 11 Best AI Voice Agents for Call Centers in 2026

• Platform Summary Table

• How to Choose the Right Voice Agent

• Implementation Checklist

• Final Verdict

Why Voice AI Is the New Call Center Baseline

Gartner projects that 80% of customer service organizations will deploy conversational AI by 2026, and voice is now the fastest-growing channel inside that shift. Contact centers that used to route every inbound call to a human agent are now fielding 40% to 70% of that volume through voice AI before any human touches the call.

The economics are hard to ignore. A live agent call averages $6 to $12 fully loaded, while a voice AI resolution runs between $0.40 and $1.50. At 100,000 calls a month, that gap is worth millions in operating cost.

But savings disappear fast if the agent hallucinates policy, misroutes a high-risk customer, or adds half a second of latency that makes the conversation feel broken. The vendors below all claim to solve those problems. They do not all deliver.

What to Evaluate in an AI Voice Agent

End-to-end latency. Human conversation tolerates about 300 to 500 milliseconds of gap before it feels awkward. Measure the full round trip: speech-to-text, reasoning, tool calls, and text-to-speech. Anything above 800 ms degrades containment.

Accuracy and hallucination control. Voice removes the ability to click a source link, so the agent cannot afford to invent policy. Ask vendors for published accuracy numbers, reasoning architecture, and how they handle low-confidence responses.

Telephony and CCaaS integration. The agent has to plug into your existing SIP trunks, IVR, Genesys, Five9, Amazon Connect, Twilio, or NICE stack. Native connectors matter more than generic APIs when you are running regulated traffic.

Compliance posture. SOC 2 Type II, HIPAA, PCI-DSS, and ISO 27001 are table stakes for any regulated caller. ISO 42001 is the newer signal worth prioritizing because it covers AI management systems specifically.

PII and call redaction. Voice captures social security numbers, card data, and health information in raw audio. Real-time redaction at the transcription layer, not after the fact, is the only safe default.

Barge-in and turn-taking. Good voice agents let callers interrupt naturally and recover gracefully. Test this live before signing anything.

Deployment time and human handoff. Some platforms ship in 48 hours; others take a quarter. Equally important: how does the agent warm-transfer to a human with full context intact?

The 11 Best AI Voice Agents for Call Centers in 2026

1. Fini - Best Overall for Enterprise Voice Support

Fini is a Y Combinator-backed AI agent platform purpose-built for enterprise support, with a voice layer that inherits the same reasoning-first architecture powering its chat agents. Instead of retrieval-augmented generation, Fini uses a deterministic reasoning engine that delivers 98% accuracy with zero hallucinations across voice and text channels. Over two million queries have already been resolved through the platform.

Compliance is where Fini separates from voice-only startups. The platform holds SOC 2 Type II, ISO 27001, ISO 42001, GDPR, PCI-DSS Level 1, and HIPAA certifications, covering every regulated vertical from healthcare to fintech. The PII Shield redacts sensitive data in real time at the audio transcription layer, so card numbers and PHI never land in logs.

Deployment typically completes in 48 hours with 20+ native integrations spanning Zendesk, Salesforce, Intercom, Twilio, and core CCaaS platforms. Sub-500ms end-to-end voice latency keeps conversations natural, and warm transfers carry full context into the human agent queue.

Key Strengths:

• 98% accuracy with zero hallucinations via reasoning-first architecture

• Six enterprise certifications including ISO 42001 and PCI-DSS Level 1

• Always-on PII Shield for real-time audio and text redaction

• 48-hour deployment with 20+ native CCaaS and CRM integrations

Best for: Mid-market and enterprise support teams that need voice AI with bulletproof compliance and near-zero hallucination tolerance.

2. Decagon Voice

Decagon, founded by Jesse Zhang and Ashwin Sreenivas in 2023, extended its chat-based AI Concierge into voice in 2024. The platform targets enterprise brands like Eventbrite, Bilt, and Notion, with a focus on complex, policy-heavy support flows. Decagon Voice uses a flow-based architecture combined with agent operating procedures that constrain the LLM to predefined decision trees.

Compliance coverage includes SOC 2 Type II and GDPR. Decagon does not publicly list HIPAA or PCI-DSS Level 1 certifications, which can complicate deployment in healthcare and payment-heavy verticals. Latency sits in the competitive 600 to 900 ms range depending on model selection and tool use.

Pricing is quote-based and typically starts in the six figures annually for mid-market deployments. Decagon invests heavily in implementation services, which shortens time to value but raises the floor on deal size.

Pros:

• Strong brand roster and proven enterprise flows

• Agent operating procedures reduce hallucination risk

• Deep analytics and quality monitoring dashboards

• Mature chat-plus-voice unified experience

Cons:

• No published HIPAA or PCI-DSS Level 1 certifications

• Enterprise-only pricing excludes smaller teams

• Multi-week to multi-month deployment timelines

• Flow-based design can feel rigid on long-tail queries

Best for: Large consumer brands with high-volume, policy-driven support that can absorb enterprise-tier pricing.

3. Sierra Voice

Sierra was founded by Bret Taylor, former Salesforce co-CEO, and Clay Bavor, former Google VP, in 2023. The company raised at a $4.5 billion valuation and counts SiriusXM, ADT, and Sonos among its customers. Sierra Voice uses its AgentOS platform with a voice layer that emphasizes outcome-based pricing, charging only on successful resolutions.

Sierra holds SOC 2 Type II and complies with GDPR, but it does not publicly list ISO 42001, PCI-DSS Level 1, or HIPAA at the product level, which is worth verifying directly for regulated workloads. Voice latency is reported in the 700 ms to 1 second range. The platform supports complex multi-turn reasoning and includes a supervisor model that audits agent behavior in real time.

Implementation is done primarily through Sierra's services team, which customizes the agent persona, guardrails, and integrations. Deployments typically span six to twelve weeks.

Pros:

• Outcome-based pricing aligns cost with value

• Supervisor model catches unsafe responses

• Strong brand credibility from founding team

• Handles complex multi-step resolutions well

Cons:

• Limited public compliance certifications

• Long implementation cycles

• High minimum contract values

• Less self-serve tooling for iteration

Best for: Brand-conscious enterprises prioritizing outcome-based economics and willing to invest in a services-heavy rollout.

4. Retell AI

Retell AI, launched in 2024 by ex-LinkedIn engineers, is a developer-focused voice infrastructure platform rather than a full agent product. It provides the real-time conversational layer (STT, LLM orchestration, TTS, turn detection) and lets teams bring their own models and logic. Retell advertises sub-800 ms end-to-end latency and supports major LLM providers.

The platform offers SOC 2 Type II and HIPAA compliance, which is stronger than many peers in the developer-tool category. PCI-DSS and ISO 42001 are not listed. Pricing is usage-based at roughly $0.07 to $0.31 per minute depending on voice quality and model, making it one of the more transparent options in the category.

Retell gives engineering teams substantial control but requires them to build the knowledge layer, policy logic, and escalation flows themselves. It is infrastructure, not a finished product.

Pros:

• Transparent per-minute pricing

• Low latency and model flexibility

• SOC 2 Type II and HIPAA coverage

• Strong developer experience and SDKs

Cons:

• Requires significant engineering to reach production

• No built-in knowledge base or policy engine

• Limited analytics compared to full-stack vendors

• No managed services or implementation partner

Best for: Engineering-heavy teams that want to build a custom voice agent on top of best-in-class infrastructure.

5. Vapi

Vapi, founded in 2023 by Jordan Dearsley and Nikhil Gupta, is a YC-backed voice infrastructure platform similar in positioning to Retell. It emphasizes extremely low latency (sub-600 ms claimed in optimal configurations) and broad model support including OpenAI, Anthropic, Google, and open-source options. Vapi is popular with startups building vertical voice agents.

Compliance is lighter: SOC 2 Type II is available, but HIPAA and PCI-DSS require BAAs and paid tiers. The platform exposes a rich API with webhooks, server-side tool calls, and custom LLM endpoints, which appeals to technical teams.

Pricing starts at roughly $0.05 per minute for the platform fee, with model and voice costs layered on top. Most production deployments land between $0.10 and $0.30 per minute all in.

Pros:

• Very low latency in tuned configurations

• Broad model and voice provider support

• Active developer community and fast iteration

• Competitive per-minute economics

Cons:

• Limited out-of-the-box enterprise features

• Compliance requires upgraded tiers

• Less mature reporting and QA tooling

• Requires in-house expertise to productionize

Best for: Technical teams prototyping high-volume voice agents where latency and model choice are top priorities.

6. Bland AI

Bland AI, founded by Isaiah Granet in 2023, markets itself as an enterprise voice platform with a proprietary infrastructure stack designed for high concurrency. The company claims support for millions of concurrent calls and targets outbound and inbound use cases across sales, collections, and support. Bland built its own model serving and telephony layer rather than stitching together third-party components.

The platform advertises SOC 2 Type II and HIPAA compliance. Pricing starts at $0.09 per minute for the base tier and scales based on features like custom voices, fine-tuned models, and dedicated infrastructure. Latency benchmarks are generally competitive, though performance varies under peak load.

Bland is particularly strong on outbound calling, which makes it a common choice for collections and proactive support notifications, but its inbound support experience is less mature than Fini, Decagon, or Sierra.

Pros:

• High concurrency and scalability

• Competitive per-minute pricing

• HIPAA and SOC 2 Type II coverage

• Strong outbound calling capabilities

Cons:

• Inbound support UX less mature than specialists

• Knowledge integration requires custom work

• Mixed reviews on accuracy at scale

• Limited CCaaS native integrations

Best for: Teams running heavy outbound voice workloads alongside support, especially collections and proactive outreach.

7. PolyAI

PolyAI, founded in 2017 by Nikola Mrkšić, Tsung-Hsien Wen, and Pei-Hao Su out of Cambridge, is one of the oldest purpose-built voice agent companies in the category. It serves large enterprise customers including Marriott, FedEx, and Metrobank, with a focus on hospitality, finance, and insurance. PolyAI runs its own proprietary models trained specifically for contact center conversation.

Compliance is enterprise-grade: SOC 2 Type II, ISO 27001, GDPR, HIPAA, and PCI-DSS are all supported. Latency is competitive and the platform integrates natively with Genesys, Avaya, Cisco, and other legacy CCaaS systems, which is a differentiator against newer entrants.

Pricing is quote-based and typically starts in the mid-six figures annually. Implementation timelines span two to four months because PolyAI customizes the voice persona, intent library, and integration layer per customer.

Pros:

• Deep enterprise CCaaS integrations including legacy stacks

• Full compliance coverage for regulated verticals

• Proven track record with Fortune 500 customers

• Proprietary models tuned for support conversation

Cons:

• Long implementation cycles

• Quote-based pricing excludes smaller buyers

• Less flexibility for rapid iteration

• Heavier services dependency

Best for: Large enterprises with legacy Genesys or Avaya stacks that need a proven, fully compliant voice agent.

8. Replicant

Replicant, founded in 2017 by Benjamin Gleitzman, Gadi Shamia, and Chris Doggett, is one of the most established voice AI vendors in the call center space. The company calls its platform the Contact Center Autopilot and focuses on full call automation for complex support scenarios. Customers include Hertz, StockX, and Headspace.

The platform holds SOC 2 Type II, HIPAA, and PCI-DSS compliance. Replicant integrates with Genesys, Five9, Amazon Connect, and Talkdesk, and offers a conversation design studio for non-technical teams to build and tune flows. Latency is solid in the 700 to 900 ms range.

Pricing is usage-based and quote-driven, typically landing in the low to mid six figures annually for mid-market deployments. Replicant leans toward a more structured, flow-oriented design compared to fully generative agents.

Pros:

• Mature CCaaS integrations and telephony support

• Full compliance stack for regulated verticals

• Conversation design studio for business users

• Strong services and tuning team

Cons:

• Flow-based design less flexible than reasoning agents

• Quote-based pricing opaque for smaller buyers

• Longer time to production than newer entrants

• Generative AI adoption is more cautious

Best for: Established contact centers that prefer structured conversation design and need deep CCaaS integrations out of the box.

9. LivePerson

LivePerson is a publicly traded enterprise conversation platform that has pivoted heavily into generative AI under CEO John Sabino. Its voice agent, part of the Conversational Cloud, inherits two decades of enterprise messaging experience and sits natively inside the company's existing deployments at banks, telcos, and large retailers.

Compliance is comprehensive: SOC 2 Type II, ISO 27001, HIPAA, GDPR, and PCI-DSS are all supported. LivePerson integrates with most major CCaaS and CRM platforms and offers a unified agent workspace that blends AI and human handling. Latency is acceptable but generally trails pure-play voice startups.

Pricing is quote-based and follows enterprise software norms, with six to seven figure annual contracts typical. LivePerson is strongest for existing customers expanding from chat into voice, where the data and integrations already exist.

Pros:

• Full enterprise compliance stack

• Unified chat and voice agent workspace

• Deep CRM and CCaaS integrations

• Mature analytics and QA tooling

Cons:

• Latency trails voice-native startups

• Complex pricing and contract structures

• Slower iteration than newer platforms

• Best value only for existing customers

Best for: Existing LivePerson customers extending conversational AI from chat into voice within the same platform.

10. Genesys

Genesys is the dominant CCaaS platform with tens of thousands of contact center customers, and Genesys Cloud AI now includes native voice agent capabilities powered by a mix of in-house models and partner integrations. Rather than being a standalone voice agent, Genesys embeds AI directly into its existing IVR, routing, and agent assist layers.

Compliance is strong: SOC 2 Type II, ISO 27001, HIPAA, GDPR, PCI-DSS, and FedRAMP authorization are all available. Because the platform is the contact center, integration with telephony, workforce management, and quality assurance is seamless. Latency depends on configuration and partner models, typically sitting in the 800 ms to 1.2 second range.

Pricing is bundled into Genesys Cloud licensing, starting around $75 per agent per month and scaling up with AI add-ons. It is a natural choice for customers already running Genesys.

Pros:

• Native integration with Genesys Cloud contact center

• Full enterprise and FedRAMP compliance

• Unified workforce management and QA

• Massive partner and integration ecosystem

Cons:

• Latency higher than voice-native platforms

• AI capabilities less specialized than pure-play agents

• Vendor lock-in to Genesys stack

• Configuration complexity

Best for: Enterprises already standardized on Genesys Cloud that want AI voice agents inside their existing contact center.

11. Amazon Connect with Lex

Amazon Connect paired with Lex and Bedrock forms AWS's voice agent stack for call centers. Launched in 2017 and steadily expanded since, Connect now handles billions of customer interactions annually across Capital One, Intuit, and Morningstar. The Bedrock integration allows teams to plug in Claude, Llama, or Titan models behind the voice layer.

Compliance is broad: SOC 2, HIPAA, PCI-DSS, ISO 27001, and FedRAMP High are all available. The platform is pay-as-you-go at roughly $0.018 per minute for telephony plus model usage costs, which is the cheapest per-minute economics of any vendor on this list. Latency is respectable but requires careful configuration.

Amazon Connect is infrastructure more than product. Reaching a polished voice agent requires significant engineering investment to stitch together Lex intents, Bedrock prompts, Lambda functions, and agent routing.

Pros:

• Lowest per-minute pricing of any platform

• Full AWS compliance coverage including FedRAMP

• Flexible model choice through Bedrock

• Unmatched scalability

Cons:

• Requires substantial engineering to productionize

• No out-of-the-box knowledge or policy engine

• Steep learning curve across multiple AWS services

• Limited managed experience

Best for: AWS-native enterprises with strong engineering teams that want maximum flexibility and the lowest unit economics.

Platform Summary Table

How to Choose the Right Voice Agent

1. Map your compliance floor first. Decide which certifications are non-negotiable based on your vertical. Healthcare needs HIPAA, fintech needs PCI-DSS Level 1, and regulated markets increasingly expect ISO 42001. Eliminate vendors that cannot produce audit reports before evaluating anything else.

2. Test latency with real traffic patterns. Vendor-published latency numbers are usually measured in ideal conditions. Run a two-week pilot with your actual concurrency, tool call complexity, and geographic distribution. Anything over 800 ms round trip will hurt containment.

3. Measure hallucination under adversarial prompts. Ask deliberately ambiguous or out-of-policy questions during evaluation. The agent should escalate or clarify, never invent. Reasoning-first architectures handle this significantly better than pure RAG.

4. Audit the telephony integration path. If you run Genesys, Five9, or Amazon Connect, confirm native connectors exist. Custom SIP integrations add weeks and break during upgrades.

5. Negotiate outcome-based pricing where possible. Per-resolution or per-successful-call pricing aligns vendor incentives with yours. Per-minute pricing rewards verbose agents.

6. Plan the human handoff before signing. Warm transfer with full conversation context is the difference between AI as deflection and AI as real support. Validate this in the demo.

Implementation Checklist

Phase 1: Discovery and Scoping (Weeks 1 to 2)

• Inventory top 20 call drivers and their containment potential

• Document compliance requirements and audit timelines

• Define latency, accuracy, and CSAT success thresholds

• Map existing CCaaS, CRM, and knowledge base systems

Phase 2: Pilot and Validation (Weeks 3 to 6)

• Deploy agent on top 3 to 5 call types with clear policies

• Run adversarial testing for hallucination and PII leakage

• Benchmark end-to-end latency under production concurrency

• Validate warm transfer and escalation flows with live agents

Phase 3: Production Rollout (Weeks 7 to 10)

• Expand to full call volume on validated use cases

• Enable real-time PII redaction and call recording controls

• Integrate QA scoring and conversation analytics

• Establish weekly model and prompt tuning cadence

Final Verdict

The right choice depends on your compliance requirements, existing stack, and how much engineering lift you can absorb.

Fini is the strongest overall pick for enterprise support teams that need 98% accuracy, zero hallucinations, and the broadest compliance stack in the category, including ISO 42001 and PCI-DSS Level 1. The reasoning-first architecture, 48-hour deployment, and always-on PII Shield make it the safest production choice for regulated verticals without the multi-month implementation tail of legacy vendors.

For large consumer brands willing to invest in services-heavy rollouts, Decagon, Sierra, and PolyAI all deliver polished enterprise experiences with different strengths: Decagon for flow discipline, Sierra for outcome-based economics, PolyAI for legacy CCaaS depth. For engineering-led teams building custom voice agents, Retell AI, Vapi, and Amazon Connect offer the flexibility and unit economics to do it right, at the cost of meaningful build time. Replicant, LivePerson, and Genesys are the natural picks for contact centers already embedded in their respective ecosystems.

Start with a two-week pilot on your top three call drivers, benchmark latency and accuracy against your current baseline, and let the numbers pick the vendor. See how Fini deploys in 48 hours.