Best AI Voice Agents (2026): Top 10 Compared

Sierra is an agent platform built by the company founded by Bret Taylor and Clay Bavor, aimed at consumer-facing brands that want a single AI agent handling customer conversations across channels. The company states that agents deploy across chat, SMS, WhatsApp, email, voice and ChatGPT, so the phone channel is one surface of a shared agent rather than a separate product with its own knowledge base.

The build tooling centres on Ghostwriter, which assembles a production-ready multilingual agent from source material such as standard operating procedures and past transcripts, and Agent Studio, the dashboard used to configure, monitor and version agents. Horizon handles long-running planning across multi-step interactions, while the Context Engine connects customer records across systems so the agent can act rather than only answer. Insights and Explorer analyse conversation logs to show where agents fail. Listed platform integrations include Google Cloud, AWS, Databricks, Snowflake and Redis, and the company publishes SOC 2, ISO 27001, ISO 42001, HIPAA, GDPR, FedRAMP and PCI DSS certifications.

Pricing is the most distinctive part of the product. Sierra publishes no price list and no self-serve tier; instead it describes an outcome-based model in which the customer pays when the agent completes a defined outcome such as a resolved support conversation, a saved cancellation or an upsell. The company states that unresolved conversations in most cases carry no charge and that escalated cases usually cost nothing, with blended consumption pricing offered for lighter interactions such as routing and greeting. Named customers include Rocket Mortgage, Gap, SoftBank, Uber, Vanguard, Wayfair, CarMax and SoFi.

The fit is a brand with high call and message volume, existing systems worth integrating, and a procurement process that can absorb a negotiated contract. Small teams that want a phone agent running the same week should look at the self-serve products further down this list. Evaluation also depends on agreeing what counts as a resolution before the contract is signed, because that definition determines the invoice.

PolyAI is a voice-first agent company whose product centres on Dialog-RSN-1, a proprietary dialog model the company describes as trained on more than a billion enterprise conversations. The positioning is narrower than the general agent platforms: the target deployment is a contact centre phone line where the AI agent replaces a touch-tone menu and handles the call to completion, escalating to a human when it cannot.

The platform offers two build paths. A visual agent builder covers teams without engineering support, and an agent development kit covers developers who want to define behaviour in code. Multi-language support, real-time analytics into why an agent made a given decision, and consistent brand voice across channels are the features the company foregrounds. Compliance certifications listed include SOC 2, HIPAA, GDPR and PCI DSS, which matters for the regulated sectors PolyAI sells into. Named customers span healthcare, utilities, banking, restaurants and hospitality, including PG&E, UniCredit, Quicken, Fogo de Chão, Golden Nugget and Howard Brown Health.

The pricing page states that ongoing use of a voice agent is priced per minute and that the per-minute rate includes proactive performance improvements, maintenance and 24/7 support through a web portal and an emergency phone line. Every engagement is described as including a 99.9% uptime SLA, system monitoring, automatic feature upgrades and enterprise data security. No dollar figure appears on the page, so the effective cost depends on negotiated volume.

This suits an organisation that already runs a contact centre, measures containment and average handle time, and wants a vendor accountable for tuning the agent after launch rather than shipping a builder and stepping back. It is a poor fit for a business with a few dozen calls a week or one that wants to own the prompt engineering itself. Because the rate is per minute, the cost of a deployment tracks call duration, so containment and average handle time are the figures to model before committing.

Cognigy, now part of NiCE and marketed as NiCE Cognigy, sells Cognigy.AI, an enterprise agentic AI platform for customer service. The product handles voice, chat and messaging from one agent design surface, and its distinguishing component is Voice Gateway, which provides turnkey telephony connectivity into an existing contact centre rather than requiring the business to move its phone estate to a new provider.

Capability claims on the product page include support for more than 100 languages, more than 25,000 concurrent interactions, over 30 omnichannel connectors and more than 110 prebuilt tools that agents can call. Integrations cover NiCE CXone, Genesys, Amazon Connect, Avaya, Microsoft and 8x8, which is the main reason large contact centres shortlist the product: the AI layer slots into the routing and reporting stack already in place. Alongside the customer-facing agents, the platform includes Agent Copilot for human advisors, AI Ops and orchestration tooling, Knowledge AI for grounding answers in documentation, and an insights and analytics module. It is delivered as a SaaS platform on a microservices architecture.

Cognigy does not publish prices. The product page routes visitors to a demo request, and contracts are negotiated per deployment, typically covering voice, chat and model usage separately along with add-ons such as Agent Copilot. Reference customers named on the site include Lufthansa, Toyota, DHL, Henkel, Nestlé, Bosch, Frontier Airlines and Mercedes-Benz, with the company reporting more than a billion annual interactions across its base.

The buyer profile is a multinational running a mature contact centre, with a team able to own conversation design and an integration budget. Businesses that simply want their phone answered will find the platform disproportionate to the problem, and the absence of a self-serve tier makes evaluation slow. The acquisition by NiCE also means roadmap decisions now sit inside a larger contact centre portfolio, which is worth weighing for buyers standardised on a competing platform.

Five9 is a cloud contact centre provider that has added voice AI agents to an established CCaaS platform serving more than 3,000 customers. The pitch differs from the pure-play voice vendors: the AI agent is one part of a stack that already includes routing, digital channels, workforce engagement management, quality management and reporting, so an existing Five9 customer adds automation without adding a supplier.

The AI agent architecture uses an orchestrator agent that interprets the caller's request and plans a path to resolution, delegating to specialised sub-agents for identity verification, system lookups and transactional actions. Five9 emphasises multi-step requests where the caller's intent shifts mid-call, natural-language configuration so new use cases can be added in days, low-latency turn-taking that tolerates interruptions, and escalation that carries full conversation context to a human advisor. Governance features include custom guardrails, real-time monitoring and data redaction. A live demo line for a sample pharmacy agent is published on the product page. Integrations cover CRM systems, UCaaS platforms, open APIs and SDKs, and a partner marketplace.

Published pricing lists a Digital plan at $119 per seat per month for chat, email, SMS and social, and a Core plan at $159 per seat per month covering all channels with essential AI. The Plus, Pro and Enterprise tiers, which add advanced AI and workforce engagement management, are quoted by sales. Prices are per concurrent user with a stated minimum of 50 seats, and usage-based charges may apply on top. AI agent consumption is bundled into the tier structure rather than priced as a separate line.

The fit is an established contact centre of at least fifty seats that wants automation and human agents governed together. Businesses below that seat threshold are effectively excluded from the published pricing, and because AI consumption is folded into the tier rather than itemised, comparing the true cost per automated call against a per-minute vendor requires a quote.

CloudTalk is a cloud call centre platform that has extended a conventional business phone system with AI voice agents. The company reports more than 40,000 customers and over a billion calls processed. The product is aimed at sales and support teams that need working telephony first, with automation layered on the same numbers, routing rules and reporting rather than provisioned separately.

Two AI agent variants are sold. The AI Receptionist answers and routes inbound calls and books meetings around the clock. The AI Specialist covers after-hours coverage, lead qualification, appointment scheduling and payment reminders. Around them sits the core platform: local numbers in more than 160 countries, IVR and call menus, queuing, recording, real-time monitoring, SMS and WhatsApp, and outbound tooling including power and parallel dialling, answering machine detection and voicemail drop. Call intelligence features add automatic summaries, tagging, call scoring, sentiment analysis, topic extraction and transcription across more than 70 languages. Integrations number over 100 and include HubSpot, Salesforce, Pipedrive and Zendesk.

Pricing is published in euros. Seat plans run from Lite at €19 per user per month billed annually, through Starter at €25 and Essential at €29, to Expert at €49 per user per month billed annually with a three-user minimum; monthly billing is roughly thirty percent higher. The AI Receptionist starts at €99 per month for 200 minutes, with 50 minutes free in the first month, while the AI Specialist is €349 per month with 1,000 minutes included. Volume above 10,000 minutes a month starts from €0.15 per minute. Add-ons such as power dialler, parallel dialler and conversation intelligence are billed per user.

This suits a team that wants one vendor for both the phone system and the agent. Businesses that only want an answering service will pay for telephony features they do not need, and the modest included minute allowances mean a high-volume line moves quickly into overage or a custom volume rate.

Synthflow is a voice AI platform for automating inbound and outbound phone calls. It sits between the developer platforms and the packaged answering services: the customer designs the agent, but the vendor supplies telephony, testing tooling and launch support rather than only an API. The company reports more than 65 million customer calls processed and a 99.99% uptime figure.

Deployment follows a four-stage framework the company calls BELL: build the conversation in a visual flow designer, evaluate it with automated testing in a sandbox, launch it over proprietary telephony, and learn from production through automated quality assurance. The architecture is multi-agent and modular, so a single phone number can route between specialised agents. Feature coverage includes natural language understanding, sentiment analysis, call routing, voicemail detection, multi-language support and fine-tuning on historical call recordings. Latency over the native telephony layer is stated at under 100 milliseconds. More than 200 integrations are supported, including HubSpot, Salesforce, Cal.com and Zapier, along with existing SIP and PBX infrastructure. Named use cases cover customer service, receptionist duties, appointment booking, lead qualification and call routing across healthcare, financial services, retail, telecoms, real estate and BPO.

The pricing page shows a single publicly detailed tier: an Enterprise plan starting at $30,000 annually, with the final figure set by call volume, concurrency, telephony setup, integrations, security requirements and launch support. That contract includes an enterprise SLA, custom concurrency and escalation planning, CRM and contact centre integrations, MSA and DPA support, security review, implementation, training and ongoing optimisation.

The product fits a company with defined call flows, integration requirements and an annual budget in five figures. Businesses testing whether a voice agent works at all will find the entry commitment steep relative to the packaged alternatives listed below. The compensating benefit is that telephony, testing and post-launch optimisation arrive in the same contract rather than as separate procurement exercises.

Kore.ai sells an enterprise agentic AI platform used to build, deploy and operate AI agents across both customer-facing and internal use cases. The core runtime is marketed as Agent Platform Artemis, described as a programmable foundation for building, scaling and optimising agents in production. Two application suites sit on top: AI for Service, covering contact centre agents, quality assurance and outbound campaigns, and AI for Work, covering enterprise search, orchestration and prebuilt departmental agents for HR, IT, finance and recruiting.

The voice story runs through AI for Service, where agents are deployed omnichannel across digital and telephony channels and billed by conversation session. Prebuilt industry applications are published for banking, healthcare, retail, HR, IT and recruiting, which shortens the build for common flows such as balance enquiries or benefits questions. A marketplace distributes prebuilt agents, templates and integrations. Strategic partnerships are listed with Microsoft, spanning Azure AI Foundry, Teams and Copilot Studio, and with AWS, spanning Bedrock, Amazon Q and Amazon Connect, so the platform can run adjacent to whichever cloud the enterprise already uses. Named customers include Morgan Stanley, Pfizer, Deutsche Bank, Johnson & Johnson, Eli Lilly and AMD.

The pricing page carries no rate card. It presents capabilities and routes visitors to schedule a call, request a demo or submit an RFP, so both the standard and enterprise plans are quoted. Product documentation describes conversation-session billing for service workloads, but the applicable unit price is set in the contract rather than published.

Kore.ai suits a large regulated organisation that wants one vendor and one governance model for customer voice agents and internal employee agents alike. A business whose entire requirement is answering inbound calls will find the platform broader and slower to deploy than a packaged voice product, and the lack of published pricing makes early budgeting difficult. Buyers already committed to Azure or Amazon Connect will get the most from the partnerships, since much of the integration work is prebuilt.

Goodcall is a packaged AI phone agent aimed at businesses that lose revenue to unanswered calls. Setup is deliberately short: the agent is trained by pointing it at an existing website or Google Business listing, and no engineering work is required. The company reports more than 60 million voice agent interactions across 306 local area codes, and states that it serves customers ranging from sole traders to public companies, including enterprises that want CRM integration on an in-house call centre line.

Functionally the agent answers inbound calls, captures lead details, books appointments against a connected calendar or CRM, transfers complex calls to staff, and distributes captured information by SMS, email, Google Sheets or CRM record. Greetings, responses and escalation logic are configurable, and an analytics view reports automation rate, call duration, caller behaviour and outcomes. Integrations cover CRM and calendar systems, Google Sheets, email, SMS, Zapier, GoHighLevel and vertical tools for segments such as salons and schools.

Pricing is published per agent and per month. Starter is $79, Growth is $129 and Scale is $249, each including unlimited minutes and tokens; annual billing cuts these to $66, $108 and $208 respectively, a 15% discount. The tiers are separated by logic flows, from one on Starter to 25 on Scale, by team members from three to 50, by directory contacts from three to 500, by data retention from seven days to unlimited, and by the number of unique monthly customers included, from 100 to 500, with $0.50 charged per additional customer. An Enterprise tier adds custom limits, an account manager, API integrations, SLA support and enterprise security controls.

Goodcall suits a single-location service business with steady call volume. Franchise groups should model the per-agent charge across sites before committing, and any business with a wide customer base should check the monthly unique-caller allowance, since that cap rather than call minutes is what drives overage on this product.

Rosie is an AI call answering service for small businesses that cannot reliably pick up the phone. It answers around the clock, responds to caller questions, takes messages, books appointments, filters spam and robocalls, and delivers summaries and transcripts afterwards. The target buyer is explicit: home services, plumbing, automotive, law firms, real estate, salons and property management, generally owner-operated.

The agent is trained automatically from an existing website and Google Business Profile, which removes most of the configuration work. Capabilities include caller routing, AI-generated message summaries, appointment scheduling with calendar integration and texted booking links, bilingual English and Spanish handling, warm and cold transfers to team members, more than ten voice options and a website chat widget for capturing leads outside call hours. Notifications arrive through native iOS and Android apps. Integration is handled through calendar services, CRM connections and Zapier, which the company states reaches more than a thousand applications.

Three plans are published. Professional is $49 per month for 250 minutes, two custom message-taking scenarios, texted appointment links, spam detection and the chat widget. Scale is $149 per month for 1,000 minutes and adds direct calendar booking, warm and live transfers, five message scenarios and outbound texts during calls. Growth is $299 per month for 2,000 minutes and adds unlimited scenarios, waterfall transfers with multiple backup paths, custom agent training and priority onboarding. Website chat is free on every plan and website texting is a $50 monthly add-on covering 25 conversations. A seven-day free trial is offered.

Rosie is a sensible first purchase for a business whose alternative is voicemail. Companies with high call volumes should compare the metered minutes against the unlimited-minute plans elsewhere in this comparison, and firms that rely on transferring live callers to staff should note that transfers begin on the Scale plan rather than the entry tier.

Smith.ai operates a virtual front office that combines AI voice agents with a network of human receptionists. The company describes AI-first, hybrid and human-first service tiers, so a business can automate routine calls and route the rest to staffed agents on the same account. It reports more than 5,000 business customers, with law firms making up roughly 80% of the base, followed by home services contractors, healthcare providers, managed IT services and marketing agencies.

The AI receptionist answers 24/7, screens callers by matter type, qualifies leads, schedules appointments and follows up with prospects. Supporting features include call recording, transcription, spam blocking, warm transfers and bilingual English and Spanish handling, with native integrations into case management and CRM systems such as Clio, Salesforce and HubSpot. The differentiator is Quality Studio, which lets a business train and test the agent against custom scenarios before it takes live calls and scores it against a published AI Quality Index. A human review loop is used to improve agent performance over time.

The AI receptionist is sold on three plans. A free tier covers 25 calls a month with $3 per additional call. Pro is $150 per month and Enterprise is $500 per month, with per-call rates of $2 and $1.67 respectively above the included allowance. All three include Quality Studio, 24/7 answering, recording and transcription, lead qualification, warm transfers and native integrations, with no setup fee or contract on self-serve plans. The separate human-first receptionist plans are priced from $300 per month for 30 calls, rising to $2,100 for 300 calls, with per-call add-ons for booking, notifications, conflict checks and payment collection.

This is the strongest option where calls sometimes need a person. Businesses wanting pure automation will find cheaper minutes elsewhere. The free tier makes the AI product unusually easy to trial, but the hybrid model is what justifies the price for firms where a missed intake call carries real cost.