The 11 best conversational AI platforms in 2026

Updated October 2026

Conversational AI platforms, also referred to as conversational AI software or solutions, are products for building AI agents that interact with customers, prospects, or employees over phone calls, chat, and messaging.

During the interaction, the agents may also take actions such as booking an appointment, issuing a refund, or routing a request. The best conversational AI platforms cover different use cases, such as the channels one agent covers, how they connect to phone lines, and pricing structure:

1. Telnyx: best for phone and messaging agents with telephony built in
2. Vapi: best for developers assembling their own voice agent stack
3. ElevenAgents: best for agents built on a large library of clonable voices
4. Bland: best for regulated-industry phone agents on in-house speech models
5. Kore.ai: best for customer and employee agents on one governed platform
6. SoundHound: best for front desks and contact centers
7. NiCE Cognigy: best for large contact centers on NiCE CXone or any SIP carrier
8. Sierra: best for large enterprises running service and sales agents
9. Fin: best for outcome-priced support agents on existing help desks
10. Decagon: best for support teams that write and A/B test agent workflows
11. Parloa: best for multilingual voice agents layered onto existing contact centers

Let's highlight a common example: A customer texts on Monday to start a return, then calls on Tuesday to ask where the refund is. On a platform that keeps one record across texts and calls, the agent answers the call with pre-existing context on the return.

Otherwise, the customer has to explain it all again. All 11 platforms in this list run agents over both calls and text, but only three publicly verify that agent memory can travel between channels. There's a deeper dive in each individual vendor section.

What is a conversational AI platform?

A conversational AI platform combines four jobs in one product: understanding what a person says or types, determining what to do next via an LLM, acting on business systems through integrations, and handing the conversation to a human when an autonomous agent should not finish it.

The practical difference between conversational AI and voice AI is exactly that: in conversational AI, the same agent runs on every channel the platform supports, such as phone calls, SMS, WhatsApp, web chat or email. A voice AI product is built for calls and voice surfaces specifically, and does not cross-pollinate into text and chat like conversational AI does.

Covering several channels does not mean the agent automatically remembers a customer between them. That depends on whether the platform shares each customer's conversation history across channels.

Earlier platforms sold intent models, dialog trees, and entity extraction as advanced conversational AI. Most of the platforms on this list use large language models for retrieval and extraction, instead.

Evaluating the conversational AI platforms on this list

I evaluated the 11 conversational AI platforms on this list against six buyer questions:

1. Which channels does one agent cover: phone, SMS, WhatsApp, RCS, email or web chat?
2. How do phone calls reach the agent: through the vendor's own carrier, a third-party provider such as Twilio, a SIP trunk from the buyer's existing carrier, or a contact-center connector?
3. Which business systems can the agent act on, and how does it hand a conversation to a person?
4. Do developers build the agent in code, or do operations teams configure it without code?
5. Is a price published, and what unit does it charge for: minutes, outcomes, conversations, sessions or seats?
6. Which certifications are public, and can the platform run in the buyer's own cloud or data center?

I weighted channels and phone connectivity most. Together they decide whether one agent can reach a customer on both a text thread and a phone call.

Those questions shaped each vendor's key strengths and description.

The order in this guide is not a ranking: Telnyx is listed first because it publishes this guide. Every vendor has a unique label and job it's suited for, explained clearly. The platforms mentioned converge on popular ways they're deployed: customer support, sales and outbound, front desk, employee and IT help, and ecommerce.

The consumer figures mentioned come from a survey Telnyx ran itself via SurveyMonkey in December 2025. It is an opt-in online sample and unweighted, so its percentages are directional. Each figure is labeled as a Telnyx survey where it appears.

The 11 conversational AI platforms compared

Best fit and key trade-off by platform

1. Telnyx: Best for phone and messaging agents with telephony built in

One Telnyx agent handles both phone calls and messages. It runs on the Telnyx Voice AI agent platform, which combines telephony, speech-to-text, text-to-speech and Telnyx-hosted language models, with Telnyx operating both the phone network and the GPUs. Telnyx originates calls as a licensed carrier rather than through a third party and sells numbers in 100+ countries, thereby lowering latency.

Best for: Teams that want calls and messages on one agent and one contract covering number, carrier and speech.

Channels and phone: Inbound and outbound calls, SMS, WhatsApp, RCS, web chat through the API, and an embeddable voice and chat widget. Calls arrive on Telnyx numbers, including ported ones, or from an existing PBX over SIP.

Key features:

• Calls transfer to named people, and in warm transfer the agent briefs the person first and connects the caller only after they accept.
• Teams build in a no-code builder or through the Assistants API and Telnyx's Voice API, bring any OpenAI-compatible LLM, and connect Salesforce, HubSpot or Zendesk natively.
• Compliance covers SOC 2 Type II, HIPAA, PCI DSS Compliant, ISO 27001 and GDPR, and outbound calls from owned numbers receive A-level STIR/SHAKEN attestation (the top US caller-ID grade).

Limits:

• Voice gets the deepest features, such as warm transfer and voicemail detection; text channels are documented more thinly.
• Business associate agreements require meeting Telnyx's commercial thresholds. Calls that use OpenAI, Anthropic or custom LLMs send the conversation outside the Telnyx network.

Pricing: Telnyx costs $0.05 per minute for its voice engine: orchestration plus Telnyx-hosted speech-to-text and text-to-speech. Language model and telephony costs are separate: Telnyx estimates about $0.006 per minute for a hosted open-weight model and lists US inbound SIP from $0.0032 per minute plus a $0.002 per minute Voice API fee. Each call bills in 60-second increments.

Choose Telnyx if: the team will configure its own tools and wants one vendor accountable for the call path.

2. Vapi: Best for developers assembling their own voice agent stack

Vapi describes itself as the developer platform for building voice AI agents, and it treats every layer as swappable: the language model, the voice, the transcriber and the carrier. Engineers pick a provider for each layer, and Vapi passes model costs through with no additional fees.

Best for: Engineering teams that want to choose each model and carrier and are ready to own the integration work that choice creates.

Channels and phone: Phone calls, web voice, web chat and SMS, where SMS needs a 10DLC-approved Twilio number (a US registration for business texting) and only the customer can start the conversation. Calls arrive on a free Vapi number, an imported Twilio or Telnyx number, or a SIP trunk from any provider.

Key features:

• Blind and warm transfer modes hand calls to people, and a handoff tool moves a call between assistants in a multi-agent squad.
• Assistants reach external systems through API request tools, MCP servers and functions, with setup guides for Make and n8n.
• The Vapi trust center lists SOC 2 Type II, HIPAA, PCI DSS v4.0.1 and GDPR, and a per-assistant PCI mode is documented.

Limits:

• The headline rate covers one layer of the bill. Hosting, model, voice, transcriber and telephony are each charged separately.
• Free Vapi numbers are US-only and inbound-only and cannot be ported out, and ISO 27001 is not publicly documented.

Pricing: Vapi lists $0.05 per minute for hosting, with the model, voice, transcriber and telephony billed on top at provider cost. New accounts start with $5 in credits, and a HIPAA business associate agreement is a $2,000 per month add-on.

Choose Vapi if: the team would rather assemble and tune every layer itself than accept one vendor's defaults.

3. ElevenAgents: Best for agents built on a large library of clonable voices

ElevenAgents is the agent platform from ElevenLabs, the voice model company; it launched as Conversational AI, became ElevenLabs Agents in September 2025 and took its current name in February 2026. ElevenLabs lists more than 11,000 voices across 70+ languages, and its Business plan includes 10 Professional Voice Clones.

Best for: Brands that want a custom or cloned voice on phone, web and messaging agents.

Channels and phone: Phone, a web widget, mobile SDKs, SMS through a Twilio number, WhatsApp and Slack. Calls connect through a native Twilio integration, a SIP trunk to an existing carrier, or connectors for Amazon Connect, Genesys and Five9.

Key features:

• Built-in system tools transfer calls to a phone number or to another agent and detect voicemail.
• Teams configure agents in ElevenLabs or through React, Swift, Kotlin and React Native SDKs, and ElevenAgents can run inside the customer's own cloud account or on its own hardware.
• ElevenLabs lists SOC 2 Type II, ISO 27001:2022, PCI DSS 4.0.1 Level 1 and GDPR, and ElevenAgents is a HIPAA-eligible service.

Limits:

• Calls above the plan's concurrency limit get lower processing priority for speech, and business associate agreements require the Enterprise plan.
• Email is listed on the product page but has no channel guide in the documentation.

Pricing: ElevenLabs publishes plans from a free tier with 15 call minutes a month to $990 per month for 12,375 minutes, with extra minutes at $0.08 each. LLM usage is billed on top, based on the model chosen, and the carrier bills its own charges.

Choose ElevenAgents if: the agent's voice is part of the brand and the team already runs its own carrier or Twilio account.

4. Bland: Best for regulated-industry phone agents on in-house speech models

Bland runs speech recognition, reasoning and speech synthesis on its own models instead of wrapping third-party providers, and it aims the platform at healthcare, insurance, financial services and logistics. Bland reports FedRAMP 20x Class A certification, a US government cloud security authorization, since August 2026, covering voice agents, SMS and chat with no outside frontier-model provider in the certified system.

Best for: Regulated enterprises that want the speech and language models in the call path to come from one vendor.

Channels and phone: Phone calls, plus SMS, RCS, iMessage and web chat on the Enterprise plan. Numbers bought from Bland run on Twilio, and teams can connect their own Twilio account or, on Enterprise, a SIP trunk, with connectors for Genesys, Five9, NICE CXone, Talkdesk and Amazon Connect.

Key features:

• Calls transfer to people and bill the transferred portion as separate transfer time, and outbound agents qualify leads and confirm appointments.
• Teams build through the API or with Norm, an assistant that builds voice agents from a prompt, and deploy on the Bland-managed cloud, a customer VPC, on-premises or air-gapped.
• Bland lists SOC 2 Type II and PCI DSS v4.0, and its trust page lists HIPAA as self-attested with a BAA.

Limits:

• Messaging, the BAA, SSO and on-premises deployment sit behind the Enterprise plan.

Pricing: The Start plan is free to begin, with talk time at $0.14 per minute, and the Build plan costs $299 per month at $0.12 per minute, with the language model and speech included. The pricing FAQ says telephony is billed separately, while the homepage says the per-minute rate covers it.

Choose Bland if: the organization works in a regulated industry and would rather approve one vendor's models than a chain of providers.

5. Kore.ai: Best for customer and employee agents on one governed platform

Kore.ai builds customer service and employee agents on one platform, relaunched as the Artemis edition in May 2026. Kore.ai says it is a Leader in the 2026 Gartner Magic Quadrant for Conversational AI Platforms for the fourth time, and a Leader in Forrester's 2026 conversational AI evaluations for both customer service and employee services.

Best for: Large organizations that want customer-facing and internal agents under one set of governance controls.

Channels and phone: Voice, web, SMS through Twilio, WhatsApp, email, Slack, Microsoft Teams and more, out of the 40+ channels Kore.ai claims. Calls run through the Kore.ai Voice Gateway on numbers bought through Twilio or over a SIP connection the customer brings, with Genesys and AudioCodes connectors.

Key features:

• Agent transfer moves sessions to people, and a Contact Center AI app runs outbound voice campaigns.
• Teams build with Arch (a built-in AI solution architect), the Agent Blueprint Language and web and mobile SDKs, and dedicated IT and HR applications sit next to the customer service ones.
• The Kore.ai trust center lists SOC 2 Type 2, PCI DSS, ISO 27001:2022 and GDPR, with SaaS, on-premises and dedicated VPC deployment.

Limits:

• HIPAA appears on the customer experience page but not in the trust center's compliance list.
• Artemis launched on Microsoft Azure first, and in-platform phone numbers come only through Twilio.

Pricing: Kore.ai publishes plan types without prices: a free tier with unstated usage limits, per-seat Team and Business plans (Business adds charges for tokens and messages), and custom Enterprise contracts.

Choose Kore.ai if: one platform team has to govern both customer and employee agents and needs analyst evidence for procurement.

6. SoundHound: Best for voice agents for ordering, front desks, cars and contact centers

SoundHound AI runs voice agents in places the other platforms here do not document: drive-thrus, kiosks and cars, alongside phone, chat, SMS and email. Its OASYS platform, launched in May 2026, consolidates the company's earlier products, including those from its Amelia and Interactions acquisitions.

Best for: Restaurants, retailers, franchises and contact centers that need voice agents built for loud, real-world settings.

Channels and phone: Calls, chat, in-app voice, SMS, email, social, kiosks, drive-thru lanes and cars. Contact-center connectors include Genesys and a certified Five9 integration, and how other calls reach OASYS is not publicly documented.

Key features:

• A human-assisted resolution feature brings people into conversations, and outbound calls can shift to SMS or a web link midway.
• The same platform runs IT service desk, HR and employee-assist agents, with a prebuilt ServiceNow integration.
• OASYS Edge runs agents fully embedded on devices, and SoundHound says its Polaris speech model is built for noisy environments.

Limits:

• Pricing, developer documentation and the call path are not public, and the trust center shows compliance as badges (SOC 2, ISO 27001, HIPAA, PCI DSS) with no SOC 2 type stated.
• SoundHound says the combined LivePerson products will roll out "in the coming quarters", so the merged platform is still in progress.

Pricing: SoundHound publishes no pricing. Engagements start with a scoping exercise led by a SoundHound solutions architect.

Choose SoundHound if: the agent has to take orders or answer calls where background noise is part of the job, from a drive-thru lane to a franchise front desk.

7. NiCE Cognigy: Best for large contact centers on NiCE CXone or any SIP carrier

NiCE Cognigy is the conversational AI platform NiCE bought in September 2025, and it is still sold both inside the CXone contact center suite and as a standalone product. Its Voice Gateway works with any SIP trunk provider, and Forrester named it a Leader in its Q2 2026 evaluation of conversational AI platforms for customer service.

Best for: Enterprise contact centers that run NiCE CXone or want voice agents on the SIP carrier they already use.

Channels and phone: Voice, web chat, WhatsApp, SMS through Twilio, Facebook Messenger, LINE, Microsoft Teams and Slack. Calls connect through the Voice Gateway on any SIP trunk, with preconfigured templates for carriers such as Twilio and Voxbone, or through endpoints for NiCE CXone, Genesys, 8x8, RingCentral and Zoom Contact Center.

Key features:

• Live Agent and Agent Copilot cover the handoff to people, and outbound calls include answering machine detection.
• Developers connect over REST, Socket.IO, webhooks, MCP and A2A, and deployment runs as SaaS or on-premises on Kubernetes.
• The Cognigy trust center lists SOC 2 Type II, ISO 27001, PCI DSS, HIPAA and GDPR, plus Germany's BSI C5 and the automotive TISAX framework.

Limits:

• Voice Gateway is licensed separately and cannot be used on its own.
• No rates, free tier or trial are published.

Pricing: Cognigy bills per conversation, where one billable conversation covers up to 50 user inputs within 24 hours, and sells voice capacity as packages of concurrent lines. No rates are published.

Choose NiCE Cognigy if: the contact center already runs on NiCE, or compliance requires an on-premises deployment.

8. Sierra: Best for large enterprises running service and sales agents

Sierra sells customer experience agents to large enterprises and says its customers include more than 40% of the Fortune 50. Its pricing is outcome-based, and its Horizon agents, launched in July 2026, work toward revenue goals such as closing a sale or upgrading a subscription.

Best for: Large enterprises that want one agent across service and sales conversations and prefer to pay for outcomes.

Channels and phone: Inbound and outbound voice, web and in-app chat, SMS, WhatsApp, email, Apple Business Chat and ChatGPT. Sierra does not publicly document how calls reach its platform, and its trust center lists Twilio as a telecommunications subprocessor.

Key features:

• Conversations escalate to care representatives with full context and history, and Live Assist brings the agent's help to human representatives.
• Agent Studio generates conversation flows from existing operating procedures, an Agent SDK defines agents in code, and agents switch between LLM providers automatically during an outage.
• Sierra lists SOC 2 Type II, HIPAA, ISO 27001, GDPR and FedRAMP High, and holds PCI DSS Level 1 Service Provider certification for payments in voice and chat.

Limits:

• No public prices or free tier are available, the Agent SDK has no public documentation, and every evaluation goes through sales.
• Sierra pages give three different language counts: over 55, 58 and 60+.

Pricing: Sierra publishes no rates. Under its outcome-based model, customers pay when the agent achieves an agreed outcome, and Sierra says an unresolved conversation usually carries no charge.

Choose Sierra if: the enterprise wants the vendor's fee tied to resolved conversations and completed sales, and accepts a sales-led evaluation.

9. Fin: Best for outcome-priced support agents on existing help desks

Fin, formerly Intercom (still the name of its help desk product), became part of Salesforce in September 2026. Fin adds an AI agent to the help desk a team already runs, with native connectors for Salesforce Service Cloud, HubSpot Service Hub and Freshdesk, and any others via its API. Fin reports a 76% average resolution rate across more than 12,000 businesses.

Best for: Support teams that want an agent on their current help desk and a bill tied to resolved conversations.

Channels and phone: Web and mobile messenger, email, SMS, WhatsApp, Instagram, Facebook Messenger, Slack and Discord, plus Fin Voice. Voice runs on the customer's existing phone provider through call forwarding or SIP, and Fin does not name the carrier behind numbers bought in Intercom.

Key features:

• Conversations pass to people inside the help desk, and passing one on without an outcome is free.
• Teams configure Fin inside Intercom or on their own help desk, and the Fin Agent API embeds the agent in custom apps and self-service portals.
• Fin lists SOC 2 Type II, HIPAA, ISO 27001 and GDPR, with data hosted in the US, the EU or Australia.

Limits:

• Fin Voice is limited to select customers working with the Fin sales team, on custom pricing.
• PCI DSS is not publicly documented.

Pricing: Fin lists $0.99 per outcome with a 50-outcome monthly minimum, where an outcome is a resolution, a procedure handoff, a disqualification or self-serve routing. A qualified sales lead costs $9.99, and a 14-day trial is free.

Choose Fin if: the help desk stays where it is and the support team wants the bill to rise only when the agent finishes the job.

10. Decagon: Best for support teams that write and A/B test agent workflows

Decagon lets customer experience teams define agent behavior in plain-language procedures it calls Agent Operating Procedures (AOPs), written the way teams write operating procedures for human agents. Teams then test changes on live traffic against a control group, and Decagon says more than 80% of its model traffic runs on models it trained itself. Its own voice model, Chord, powers the Voice 3 release launched on October 1, 2026.

Best for: Support organizations whose CX team, not engineering, owns the agent's logic and its changes.

Channels and phone: Inbound and outbound voice, web and in-app chat, SMS, WhatsApp and email. Calls connect over SIP trunking, through Amazon Connect or RingCentral, or by call forwarding, and Twilio appears on the Decagon subprocessor list.

Key features:

• Voice agents transfer calls to human agents with a summary of the conversation, and outbound voice handles callbacks, reminders and scheduling confirmations.
• Duet generates AOPs from real customer conversations, and technical teams version agents with Git-based tracking.
• Decagon lists SOC 2 Type II, HIPAA, PCI DSS 4.0.1, ISO 27001:2022 and GDPR.

Limits:

• Pricing is sales-only, and API documentation sits behind a login.
• No Decagon phone numbers are documented, so calls rely on the buyer's telephony, and FedRAMP is not listed.

Pricing: Decagon publishes no rates. It offers a fixed price per conversation or a higher price per resolution with no charge for escalations, and says most customers choose per conversation.

Choose Decagon if: the CX team wants to change agent behavior and measure the result itself, without an engineering ticket for each edit.

11. Parloa: Best for multilingual voice agents layered onto existing contact centers

Parloa puts voice-first AI agents in front of the contact center software a company already runs, so the existing platform stays in place. Parloa says its agents converse in more than 140 languages and variants, and its AI Agent Management Platform is an SAP Endorsed App on the SAP Store.

Best for: Enterprise contact centers on Genesys, Five9 or similar platforms that serve callers in many languages.

Channels and phone: Voice and web chat, with WhatsApp shown in one customer case study. Calls connect over SIP to the customer's telephony, CCaaS or PBX, with named integrations for Genesys, Amazon Connect, Cisco, Avaya, Five9, Talkdesk, Zoom Contact Center, RingCentral, Vonage and UJET.

Key features:

• Contact-center integrations such as Five9 carry inbound and outbound calls, with warm transfer back to people.
• A collections product adds controls built around the US Telephone Consumer Protection Act (TCPA), consent management and audit-ready records for outbound calls.
• Parloa lists SOC 2 Type 1 and Type 2, ISO 27001:2022 and PCI DSS and states compliance with HIPAA and GDPR, and card data runs through a separate process with no language model in it.

Limits:

• Teams build agents in the Agent Builder, but its documentation sits behind a login, and no rates or trial are published.
• SMS and email are not documented as agent channels.

Pricing: Parloa prices by consumption, per minute for voice and per interaction for chat, with model token costs included and outcome-based pricing available. No rates are published.

Choose Parloa if: the contact center will keep its current platform and needs an agent fluent in many of its callers' languages.

How do conversational AI platforms connect to phone calls?

Conversational AI platforms connect to phone calls in four ways: a carrier network the vendor runs itself, a third-party provider such as Twilio, a SIP trunk from the buyer's existing carrier, or connectors into contact-center software such as Genesys or Five9. Most of the 11 platforms here support more than one route. The last column shows whether the agent on a call can see the same customer's earlier text conversation.

Call path and cross-channel memory by platform

The route decides how many companies sit between the caller and the agent. When the carrier and the speech models run on one network, the audio does not cross to another provider between the phone line and the transcription. When they belong to different vendors, each handoff adds a network hop, another contract and another support boundary to troubleshoot when a call fails.

The SIP and connector routes suit a business with a phone system it wants to keep: the existing numbers and contact center stay in place. The cost is that the business manages two vendors for every call.

“Buyers naturally evaluate voice quality, latency, model accuracy, and how good the demo sounds. Those are important. But in production, you also have to ask: did the call get answered, was it signed correctly, did the media path preserve audio quality, did the platform handle interruptions, can we inspect a bad call, and can someone explain what actually happened? A great model on a fragile call path still feels fragile.” James Whedbee VP of Engineering, Telnyx

Outbound calls add a legal layer to whichever route a platform uses. In a February 2024 ruling, the FCC confirmed that the Telephone Consumer Protection Act's limits on an "artificial or prerecorded voice" cover AI-generated voices. An AI agent's outbound call therefore needs the called party's prior express consent, and written consent when it carries telemarketing. Legal counsel should review any outbound calling program before launch.

How much do conversational AI platforms cost?

Prices for conversational AI platforms start at $0.05 per minute for Telnyx or $0.99 per outcome on Fin. Six of the 11 don't publish any figures and require a sales evaluation first. The platforms charge in five kinds of unit: per minute (Telnyx, Vapi, ElevenAgents, Bland, and Parloa for voice), per outcome (Fin and Sierra), per conversation (Cognigy and Decagon), per seat with usage (Kore.ai), or a scoped contract with no published unit (SoundHound).

The real cost of a conversation moves with rounding, separate layers, add-ons and minimums:

• Telnyx bills each call in 60-second increments, so a 15-second call bills as a full minute.
• Model, voice, transcriber and carrier charges often sit outside the headline rate.
• A HIPAA agreement on Vapi costs $2,000 a month, and the Cognigy Voice Gateway needs its own license.
• Fin bills at least 50 outcomes a month.

Per-outcome pricing ties the fee to results rather than agent runtime. This requires alignment on defining an outcome, with Fin counting resolutions, procedure handoffs, disqualifications and self-serve routing as billable.

Cost at 10,000 minutes a month

At 10,000 minutes a month, the four platforms that publish per-minute prices land between about $617 and $1,514. The figures assume 10,000 billed minutes of US inbound calls from about 4,000 calls, one phone number and each vendor's self-serve pricing on October 1, 2026.

Estimated monthly cost at 10,000 minutes, from published rates on October 1, 2026

The rows use each vendor's own published rates. The Telnyx language model figure is the Telnyx estimate for Kimi, an open-weight model it hosts; an OpenAI or Anthropic model bills at provider list rates and would raise the number. The Vapi range spans the transcriber, OpenAI model and ElevenLabs voices, and its $0 carrier case uses the free Vapi number, which is US-only and inbound-only.

The Bland Start plan is left out because its cap of 100 calls a day sits below about 4,000 calls a month.

Choosing the right conversational AI platform

The job the agent has to finish is a clear buying decision for each team:

• If you run customer support on an existing help desk, start with Fin. If the support team wants to own the agent's logic, look at Decagon, and if service and sales share one agent, look at Sierra.
• If you run a contact center, start with NiCE Cognigy, and with Parloa when callers speak many languages.
• If you run sales or outbound calling, compare Bland for regulated industries, Parloa for collections, and Telnyx for calls placed from owned numbers with A-level STIR/SHAKEN attestation.
• If you run a front desk, a franchise, or a restaurant, SoundHound covers phone ordering, drive-thru lanes, and small-business reception.
• If you run IT or HR support, Kore.ai and SoundHound both ship employee agents next to their customer agents.
• If you run e-commerce, Fin handles returns and order updates for Shopify stores, Kore.ai completes checkout inside the conversation, and SoundHound takes orders by voice.
• If one agent has to cover a help desk, a contact-center phone line and outbound calls, compare Kore.ai, NiCE Cognigy and SoundHound. Telnyx fits when the phone line can move to Telnyx numbers or route in over SIP.
• If you build agents into your own product, start with Telnyx for phone and messaging on one carrier, Vapi to choose every layer, or ElevenAgents when the voice itself is the product.

Outcomes and end-user experience matter as much as the platform's technical capabilities, too. In a Gartner survey of 3,566 customers, only 27% said they would try a chatbot again after a negative experience, with Gartner advising service leaders to prioritize reliability over reach.

A Telnyx survey points the same way. Of US adults Telnyx surveyed in December 2025, 57% would trust a voice AI only to provide information, and 25% would let it recommend next steps they approve. Another 11% would let it take simple, low-risk actions automatically, and 6% would let it take most actions unless they opt out. Only one respondent said it would give it full autonomy. Asked what would most raise their confidence in a voice AI, 55% chose one that confirms its understanding before it acts. That favors a first agent that answers questions and asks before it changes anything.

Disclosure also matters to US consumers. In the same Telnyx survey, 38% said the factor that most increases their trust in a voice AI agent is that it is open and transparent about its build, use, and purpose.

Research findings

Telnyx is the only one of the 11 that runs its own carrier network. The other 10 reach the phone network through Twilio, a SIP trunk the customer brings, or contact-center software.

Memory across channels is a niche feature: three of the 11 document memory that follows a customer between calls and text (Telnyx, Bland and Kore.ai). Sierra and Decagon have announced it without public documentation, and memory on Fin covers messenger and email only.

Pricing is documented unevenly too: five of the 11 publish a price (Telnyx, Vapi, ElevenAgents, Bland and Fin). The other six sell through sales exclusively.

How reliable are conversational AI agents in production environments?

Some conversational AI agents can perform very differently between a single demo run and a production rollout deployed with real humans on the other line. Research published in 2025 and 2026 found that agents that pass a task once often fail it on repeat runs.

In EVA-Bench, a 2026 benchmark from ServiceNow, researchers tested 12 voice agent systems on 213 enterprise scenarios. None scored above 0.5 on both accuracy and conversational experience.

The median gap between each system's best run and its reliable, every-run performance was 0.44. The authors concluded that single-trial scores "systematically overstate deployment-grade quality."

The same study pointed to speech recognition as one cause of failure. Cascade systems, which transcribe speech before the language model reads it, had task completion rates 39% lower when the transcription model powering the agent struggled to keep up.

Agents also struggle when asked to guide users through steps instead of acting alone. In τ²-Bench, a 2025 benchmark from Sierra researchers, the models tested passed between 34% and about 50% of telecom troubleshooting tasks on the first attempt.

Better customer ratings do not always mean resolved issues, either. A randomized field experiment at Alibaba covered 5,940 new chat agents and about 2.56 million chats in early 2024. Full use of a generative AI assistant cut issue identification time by 32.3% and the dissatisfaction rate by 15.4%.

It made no significant difference to how often customers came back with the same issue within three days. That study measured AI assisting human agents rather than an autonomous agent, but the lesson carries over.

A conversational AI pilot should incorporate these steps:

• Run each scenario several times, not once, and grade each run.
• Use real customer names, account numbers, accents, and background noise.
• Track repeat contacts alongside satisfaction scores.

Build conversational AI agents on Telnyx

Telnyx runs the phone number, the carrier network, speech recognition, the language model on Telnyx-hosted GPUs and the voice in one system, and the same agent answers SMS, WhatsApp and RCS. That makes Telnyx a conversational AI platform with telephony built in: one vendor for the path from the caller's phone to the agent's reply.

Andrea Mordenti Helia, LAIF

Customer story: Helia Helia, built by Italy-based LAIF, runs AI customer support inside the PBX systems its mid-market customers already have. “Telnyx became our core voice AI provider because in voice AI, the telephony layer is not a commodity. Controlling it is a competitive advantage.” Its customers keep their numbers, extensions and routing while adding AI support. Read customer story

Teams can start on that system in the no-code builder and talk to a working agent over the phone in under five minutes, or import agents already built on Vapi or ElevenLabs. Developers who run their own agent can carry its calls on Telnyx's Voice API instead.

Telnyx documents memory that spans phone and SMS conversations with the same customer, set up per conversation. For any platform on a shortlist, the test that settles the choice is one conversation that changes channel: a customer texts first and calls second, and the agent either picks up the thread or starts over.

Frequently asked questions

What is the difference between a chatbot and a conversational AI platform?

A chatbot is a single conversational interface, often scripted, while a conversational AI platform builds, runs and monitors agents that understand open-ended requests, act on business systems and work across voice and text channels. The practical test is the action: a platform's agent issues the refund or books the appointment, and hands off to a person with context when it should not finish the job.

How much technical skill does a conversational AI platform require?

Technical skill requirements range from none to a full engineering team. Decagon and Sierra let CX teams write agent logic in plain language. Telnyx offers a no-code builder and Bland offers Norm, an assistant that builds agents from a prompt; both also have APIs. Vapi assumes developers who will choose and connect each model and carrier. Every platform still needs someone who owns the integrations and tests what happens when a conversation fails.

Is there a free conversational AI platform?

Several conversational AI platforms offer a free way to start, but none is free in production. ElevenAgents has a free plan with 15 call minutes a month, Kore.ai has a free tier with unstated limits, the Bland Start plan needs no card, Vapi gives new accounts $5 in credits, and Fin offers a 14-day trial. Telnyx accounts start free, and trial accounts can run one AI assistant.

Which conversational AI platforms hand off to a live agent?

All 11 conversational AI platforms on this list document a handoff to a live agent, and customers expect one. In a Gartner survey of 3,566 customers in early 2026, 87% called an option to reach a human agent essential when a company uses GenAI for service. In a December 2025 Telnyx survey of 112 US adults, 39% said asking for a human would be their most likely reaction when a voice AI makes a mistake. The platforms differ in the context that travels with the handoff: Telnyx agents brief the person before connecting the caller, while Sierra and Decagon pass full history or a summary.

Which conversational AI platforms support multilingual deployments?

Parloa says its agents converse in more than 140 languages and variants, ElevenLabs lists 70+ languages for ElevenAgents, and Sierra cites 55 or more. The Telnyx text-to-speech catalog covers more than 200 language and locale codes across 80+ language families, and speech-to-text coverage depends on the transcription model chosen. Language counts vary even across a single vendor's own pages, so a pilot should test the languages that callers actually speak.

Which conversational AI platforms support custom or cloned voices?

ElevenAgents is built around custom voices: ElevenLabs lists more than 11,000 voices and includes 10 Professional Voice Clones on its Business plan. Decagon offers voice profiles that include custom-tuned voices matched to a brand. Telnyx agents can use ElevenLabs voices through the customer's own ElevenLabs key, alongside the voices included in the Telnyx voice engine.