Top 10 Retell Alternatives In 2026

Why Buyers Evaluate Retell AI?

Retell AI made it easy for developers to spin up a voice agent quickly. That appeals to startups and product teams that want to prototype fast. But as organizations grow and contact center volumes increase, the gaps in Retell AI's enterprise readiness start to show. There is no built-in quality assurance layer, no real-time coaching for human agents, no compliance monitoring, and limited support for regulated industries like healthcare and financial services.

This pushes enterprise buyers to look elsewhere. According to Gartner, by 2028, at least 70% of customers are expected to begin their customer service journey through conversational AI. As conversational AI becomes a primary channel for customer interactions, enterprises need platforms that can support high call volumes, complex integrations, compliance requirements, and seamless collaboration between AI and human agents—not just basic voice automation.

If you are a contact center leader evaluating voice AI for your team, the tools in this article represent the most serious alternatives to Retell AI available today. Each one approaches the problem differently, and understanding those differences is what this guide is designed to help with. You can also explore what conversational AI means for contact centers before diving into the comparisons below.

How We Compared These Tools?

We evaluated each platform across six dimensions that matter most to enterprise buyers:

1. Voice AI quality: How natural and accurate is the voice interaction? Can it handle accents, interruptions, and complex multi-turn conversations?

2. Enterprise readiness: Does the platform support SSO, role-based access, SOC 2 compliance, and dedicated SLAs?

3. Human agent support: Does the platform help human agents with real-time guidance and post-call coaching, or does it only automate calls?

4. QA and compliance: Is there built-in call quality monitoring, or do you need a separate tool for that?

5. Integration depth: How well does it connect with existing CRMs, telephony stacks, and contact center platforms?

6. Time to value: How long does it realistically take to go live in a production environment?

We looked at public documentation, G2 reviews, third-party analyst reports, and direct product experience to form these assessments.

Top Retell AI Alternatives: Comparison Table

Top Retell AI Alternatives: Detailed Descriptions

1. Level AI

Level AI is a purpose-built enterprise contact center intelligence platform that goes well beyond basic voice automation. While most tools in this list focus only on automating calls, Level AI connects the dots between your AI virtual agent, your human agents, your QA team, and your leadership. The result is a single platform where automated voice interactions and human-assisted calls are both monitored, scored, and continuously improved.

Level AI's voice AI handles inbound and outbound calls with high accuracy, and when a call needs to be escalated to a human, the handoff is smooth. Human agents then receive real-time suggestions powered by the same AI that understands the full conversation. After the call, QA teams get automated scoring, coaching recommendations, and compliance alerts without needing to manually listen to recordings. This closed-loop approach is what separates Level AI from every other platform in this comparison.

Enterprises in financial services, healthcare, retail, and BPO operations use Level AI to reduce handle time, improve first contact resolution, and cut QA labor costs. Paul Harraghty, VP of Global CARE at VistaPrint, said it directly: "With Level AI, we were able to save hundreds of thousands of dollars. But the bigger impact is we've expanded entry points with customers, and those interactions are delivering revenue through CARE to the business."

Key Features

• AI-powered virtual agent for inbound and outbound voice interactions

• Real-time agent assist with live call guidance and suggested responses

• Automated quality assurance that scores 100% of calls without manual effort

• Conversation intelligence that surfaces trends, risks, and customer sentiment across all calls

• Agent coaching tools that identify individual skill gaps and recommend targeted training

• Voice of the customer insights that connect call data to business outcomes

• Compliance monitoring with automated alerts for regulatory and script violations

• Native integrations with Salesforce, Zendesk, ServiceNow, and leading telephony platforms

Strengths

• The only platform in this list that combines voice AI, real-time assist, automated QA, and coaching in one system

• Purpose-built for enterprise contact centers with regulated industry support out of the box

• Significantly reduces QA team workload by automating 100% call scoring

• Provides actionable coaching recommendations, not just raw data

• Strong implementation support and dedicated customer success for enterprise accounts

• Conversation intelligence layer gives leadership visibility into what is happening across every call

Best For

Level AI is the right choice for enterprise contact centers that handle high call volumes, operate in regulated industries, or need their voice AI and human agents to work as a connected team. If you want a platform that improves not just call automation but the overall performance of your entire contact center, Level AI is built for that.

Ready to see Level AI in action?

Explore how enterprise contact centers use Level AI to automate quality assurance, coach agents in real time, and deploy voice AI that actually integrates with their operations.

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2. Cognigy

Cognigy is a conversational AI platform designed for large enterprises that need to automate complex, multi-channel customer interactions at scale. It supports both voice and chat channels and is widely used across telecommunications, banking, insurance, and retail. Cognigy's architecture allows enterprises to build sophisticated conversation flows using a visual design tool, and its AI Copilot feature provides some level of real-time support for human agents during live calls.

One of Cognigy's key strengths is its on-premises deployment option, which is important for enterprises with strict data residency requirements. It also supports over 100 languages, making it a viable option for global organizations. However, Cognigy does not include built-in quality assurance or post-call analytics, so teams that need those capabilities will need to integrate a separate tool. The platform also has a steep learning curve and typically requires dedicated implementation support to get up and running.

For enterprise teams evaluating Cognigy, it is worth understanding how real-time agent assist compares across platforms, since Cognigy's AI Copilot feature is more limited than what enterprise contact centers typically need.

Key Features

• Visual conversation flow builder for designing complex multi-turn interactions

• AI Copilot for live agent support during calls

• Support for 100+ languages across voice and chat

• On-premises and cloud deployment options

• Native integrations with major CRM and contact center platforms

• Advanced NLU with intent detection and entity recognition

• Analytics dashboard for conversation performance tracking

• Pre-built connectors for SAP, Salesforce, and ServiceNow

Strengths

• Strong enterprise security and compliance posture with on-premises deployment

• Excellent multi-language support for global operations

• Mature platform with a wide ecosystem of integrations and partners

• Visual flow builder makes it accessible to non-technical teams once trained

• Proven at scale with Fortune 500 customers across regulated industries

Weaknesses

• No built-in QA or automated call scoring, requiring a separate tool for quality management

• High implementation complexity with a long time to value for most enterprise deployments

• AI Copilot for agents is less mature than dedicated agent assist platforms

• Pricing is not transparent and often requires custom enterprise negotiation

Best For

Cognigy is best suited for large enterprises that need a powerful multi-channel automation platform with strict data residency requirements, global language support, and the internal technical resources to implement and maintain it over time.

3. PolyAI

PolyAI is a voice AI company focused on building AI call agents that can handle real conversations at scale. It is particularly strong in industries like hospitality, retail, and utilities, where customers typically call with structured, predictable requests. PolyAI's voice agents are known for their natural conversational quality and their ability to handle interruptions, topic changes, and heavy accents better than many competing platforms.

The company works primarily through enterprise contracts and provides a managed service model, meaning PolyAI handles the setup, tuning, and ongoing optimization of the voice agent on your behalf. This reduces the technical burden on your internal team but also means you have less direct control over the configuration. There is no built-in QA layer, no real-time agent assist for human calls, and limited self-serve capabilities.

For contact centers in retail or travel and hospitality, PolyAI can handle a large share of routine inbound volume. But teams that also need visibility into human agent performance or compliance monitoring will need to supplement PolyAI with additional tooling.

Key Features

• Enterprise-grade voice AI with high natural language accuracy

• Handles complex, multi-turn conversations with interruptions and topic switches

• Multilingual support for global customer bases

• Managed service model with ongoing optimization handled by PolyAI

• Pre-built integrations with contact center telephony systems

• Real-time call transcription and conversation logging

• Industry-specific conversation templates for hospitality, retail, and utilities

• Analytics and reporting on call volume, deflection, and resolution rates

Strengths

• Among the most natural-sounding voice AI available for enterprise inbound calls

• Managed service model reduces internal technical workload

• Strong performance in specific verticals like hospitality and retail

• Handles accent variation and background noise better than most competitors

• Proven at high call volumes with major enterprise deployments

Weaknesses

• Limited self-serve configuration, relying heavily on PolyAI's managed team for changes

• No built-in QA, coaching, or human agent assist capabilities

• Less flexibility for companies that need custom integrations or unique conversation designs

• Not well suited for outbound calling campaigns

Best For

PolyAI works best for enterprise organizations in hospitality, retail, or utilities that primarily need to automate inbound call volume and are comfortable with a managed service model where the vendor handles the technical configuration.

4. Sierra

Sierra is a customer experience AI platform built to handle complex, multi-step customer service workflows. It integrates with existing business systems to give its AI agent access to real data so it can do things like process returns, update account information, or schedule appointments during a live conversation. Sierra's strength is its ability to execute actions across integrated systems end-to-end, not just answer questions.

However, Sierra does not offer real-time agent assist for human agents, automated quality assurance, or any post-call analytics layer. It is primarily a customer-facing automation tool. Teams evaluating Sierra alongside platforms like Level AI should review what an AI customer service agent actually needs to deliver in an enterprise context before making a decision.

You can also look at how Level AI compares to Sierra directly to understand the differences in scope.

Key Features

• AI agent capable of executing multi-step transactional workflows

• Deep integrations with CRM, order management, and ticketing systems

• Natural language interface for complex customer requests

• Topic-specific AI model fine-tuning per use case

• Escalation pathways to human agents with context handoff

• Real-time action execution during live conversations

• Support for both voice and text channels

• Enterprise-grade security and data handling

Strengths

• Unique ability to complete complex multi-step actions, not just answer questions

• Deep system integrations enable true end-to-end automation

• Strong backing and rapid product development cadence

• Good fit for complex workflows like e-commerce returns or account changes

• Clean, modern interface for both setup and monitoring

Weaknesses

• No quality assurance, call scoring, or coaching features for human agents

• Limited track record at very large enterprise scale compared to more mature competitors

• Pricing is enterprise-level and not publicly available

• Primarily suited for transactional use cases rather than complex support conversations

Best For

Sierra is the right fit for companies that need an AI agent to complete multi-step customer service transactions across integrated systems, particularly in e-commerce, financial services, or SaaS businesses where customers frequently make account changes.

5. Voiceflow

Voiceflow is a design and development platform for building conversational AI experiences across voice, chat, and messaging channels. It is primarily used by product teams, designers, and developers who want a visual, collaborative environment for prototyping and deploying AI-powered interactions. Voiceflow supports rapid prototyping, has a growing library of templates, and allows non-technical team members to participate in the design process.

For teams building AI tools for customer service at enterprise scale, Voiceflow can be a useful design tool but is unlikely to meet the operational requirements of a full contact center deployment on its own. There is no quality assurance layer, no real-time agent assist, no compliance monitoring, and limited enterprise-grade support.

Key Features

• Visual no-code canvas for building voice and chat conversation flows

• Collaborative workspace with multi-user editing and version control

• API integration to connect with external data sources and business systems

• Built-in testing and simulation tools for conversation flows

• Support for multiple AI models and NLU providers

• Template library for common conversation patterns

• Analytics on conversation paths and user drop-off points

• Export and deployment to multiple channels including voice, web, and messaging

Strengths

• Fastest platform in this list for getting a prototype running without developer resources

• Strong collaborative design environment for cross-functional teams

• Growing ecosystem of integrations and community templates

• Flexible enough to support a wide range of use cases

• More affordable than enterprise platforms, with a generous free tier for experimentation

Weaknesses

• Not built for enterprise contact center operations at scale

• No QA, agent coaching, or compliance monitoring features

• Limited enterprise support and security documentation

• Teams often outgrow Voiceflow quickly as their AI deployment scales up

Best For

Voiceflow is best for product teams and developers who need to prototype, test, and iterate on conversational AI experiences quickly. It is not the right tool for enterprises that need a production-ready, compliance-aware voice AI platform for their contact center.

6. Bland AI

Bland AI is a developer-focused platform built for high-volume outbound phone call automation. It works well for scenarios where the call script is relatively simple, and the volume is high, such as sales prospecting, appointment scheduling, and survey collection. Setup is straightforward through the API, and pricing is usage-based, which keeps costs predictable at scale.

Enterprises that need to run outbound campaigns while also monitoring call center quality assurance will need a separate solution for the oversight layer. Bland AI does not provide that, and it is not designed for inbound call handling at enterprise scale or for compliance-sensitive environments.

Key Features

• High-volume outbound call automation via API

• Customizable call scripts and conversation flows

• Batch call scheduling with time zone controls

• Real-time call monitoring and transcription

• Webhook integrations for connecting call outcomes to CRM and databases

• Voice customization with multiple voice options

• Analytics on call completion rates, outcomes, and transfer rates

• Low per-minute pricing for large volume campaigns

Strengths

• Extremely fast to set up for basic outbound calling use cases

• Low cost per call makes it economical for high-volume campaigns

• API-first design works well for development teams with existing automation pipelines

• Reliable throughput for large batch calling campaigns

• Good fit for sales, outreach, and appointment reminder workflows

Weaknesses

• No enterprise-grade security, compliance, or SLA commitments

• Not designed for inbound calls or complex multi-turn conversations

• No QA, coaching, or agent assist features

• Not suitable for regulated industries without significant additional tooling

Best For

Bland AI is best for startups and growth-stage companies that need to automate outbound phone campaigns at high volume with minimal setup. It is not a fit for enterprise contact centers that need inbound coverage, compliance monitoring, or human agent support.

7. Vapi

Vapi is a developer-focused voice AI infrastructure platform that gives engineering teams the building blocks to create custom voice AI applications. It handles the infrastructure layer including WebRTC connections, speech-to-text and text-to-speech integrations, and call routing. Vapi is model-agnostic, meaning teams can connect their preferred language model and speech provider.

The platform is well-regarded for its flexibility and documentation. However, Vapi is infrastructure, not a packaged enterprise solution. Teams using Vapi need to build their own QA layer, their own compliance controls, and their own agent assist tooling from scratch. For enterprises, it is worth reading about voice of the customer insights and what gets lost when your voice platform has no conversation intelligence built in.

Key Features

• Voice AI infrastructure with WebRTC, speech-to-text, and text-to-speech integrations

• Support for multiple language models including GPT-4, Claude, and Gemini

• Inbound and outbound call handling with programmable call logic

• Phone number provisioning and call routing

• Real-time transcription and conversation logging

• Webhook support for connecting call events to external systems

• Active developer community with documentation and support

• Usage-based pricing with no minimum commitment

Strengths

• Maximum flexibility for engineering teams that want full control over the voice stack

• Model-agnostic design lets teams switch or combine language models

• Strong developer documentation and community support

• Fast to prototype and iterate for technically capable teams

• Affordable entry point with pay-as-you-go pricing

Weaknesses

• Requires significant engineering resources to build a production-ready voice application

• No built-in QA, compliance monitoring, or agent assist features

• Not suitable for non-technical teams without developer support

• Total cost of ownership increases significantly when you factor in internal development time

Best For

Vapi is the right choice for engineering teams that need flexible voice AI infrastructure and have the development resources to build a custom application on top of it. It is not the right fit for enterprise contact centers that need a packaged solution with QA and compliance built in.

8. Synthflow

Synthflow is a no-code voice AI platform designed for small and mid-sized businesses that want to deploy an AI phone agent without writing code. It offers a simple interface for building voice agents, connecting to appointment scheduling tools, and handling basic inbound and outbound calls. Synthflow targets agencies, local businesses, and SMBs that want to automate phone interactions without developer resources.

For teams exploring AI for contact centers, reviewing contact center AI solutions at enterprise scale shows how different the requirements are compared to what Synthflow offers. The platform does not offer enterprise security certifications, QA or compliance monitoring, or support for the complex integrations that large contact centers require.

Key Features

• No-code voice agent builder with a visual interface

• Inbound and outbound call handling for common business scenarios

• Appointment scheduling integration with Calendly and similar tools

• CRM integrations with HubSpot, GoHighLevel, and others

• Call recording and basic analytics dashboard

• Multilingual support for select languages

• White-label options for agency resellers

• Affordable pricing tiers for small business use cases

Strengths

• Very easy to set up without technical expertise

• Good fit for local businesses, agencies, and SMBs with simple call handling needs

• White-label capabilities make it attractive for agencies building client solutions

• Affordable pricing compared to enterprise platforms

• Integrates well with common SMB tools and CRMs

Weaknesses

• Not suitable for enterprise contact centers with high call volumes

• No QA, call scoring, compliance monitoring, or agent assist features

• Limited security documentation and no enterprise-grade SLAs

• Not designed for regulated industries like healthcare or financial services

Best For

Synthflow is best for small businesses, local service companies, and agencies that need a simple, affordable AI phone agent for basic call handling. It is not an appropriate choice for enterprise contact center operations.

9. LiveKit

LiveKit is an open-source real-time communications infrastructure platform that supports audio, video, and data streaming. It is not a voice AI product in the traditional sense but rather a foundational layer that developers use to build voice AI applications and real-time communication features. Teams that want to deploy a voice AI agent using LiveKit need to bring their own AI models, speech-to-text providers, text-to-speech engines, and application logic.

For enterprises evaluating build-versus-buy decisions in this space, reviewing a practical guide to evaluating virtual agents can help clarify where the hidden complexity lives. Contact center use cases that platforms like Level AI or PolyAI address out of the box require significant development work to build on top of LiveKit.

Key Features

• Open-source real-time audio and video infrastructure

• Self-hosting option for complete data sovereignty

• WebRTC-based architecture with low-latency audio streaming

• SDKs for JavaScript, Python, Swift, Kotlin, and other languages

• Support for connecting external AI models and speech services

• Room management, participant tracking, and session recording

• Scalable cloud-hosted option alongside the self-hosted version

• Active open-source community with strong documentation

Strengths

• Complete control and flexibility for teams with strong engineering capabilities

• Self-hosting option eliminates data residency concerns

• Open-source model means no vendor lock-in

• Strong performance for low-latency real-time audio applications

• Active community and good documentation for developers

Weaknesses

• Not a packaged voice AI solution, requires significant custom development

• No built-in AI capabilities, QA, compliance, or agent assist features

• Requires dedicated engineering resources to build and maintain

• Time to production is measured in months, not days

Best For

LiveKit is best for engineering teams at technology companies that are building a custom real-time voice application and need low-level infrastructure control, or for organizations with strict data residency requirements that need to self-host their entire voice stack.

10. Goodcall

Goodcall is an AI phone agent platform focused on helping small businesses handle inbound calls automatically. It positions itself as an AI-powered alternative to a traditional receptionist, handling tasks like answering common questions, collecting caller information, routing calls, and scheduling appointments. Goodcall integrates with Google Calendar and various CRMs to make it easy to set up a basic automated call experience.

For businesses that are just starting to explore how AI can help with customer calls, reviewing the top benefits of virtual agents for enterprise teams gives a useful sense of what mature enterprise deployments look like compared to SMB tools like Goodcall.

Key Features

• AI phone agent for answering and routing inbound calls

• Integration with Google Calendar for appointment scheduling

• Basic CRM integrations for logging call data

• Customizable greetings and call handling scripts

• Call recording and voicemail management

• Simple web-based setup without technical expertise

• Real-time call monitoring for business owners

• Affordable monthly pricing for small business budgets

Strengths

• Extremely simple to set up and manage for non-technical users

• Good fit for small businesses that need to handle basic inbound call inquiries

• Affordable pricing with no long-term contracts required

• Handles after-hours calls and overflow traffic reliably

• Quick to deploy with minimal configuration required

Weaknesses

• Not designed for contact centers or any enterprise-scale operations

• No QA, compliance, coaching, or conversation intelligence features

• Limited conversational ability for complex or multi-step interactions

• Does not support outbound calling or multi-agent workflows

Best For

Goodcall is best for small businesses like medical offices, law firms, home services companies, and local retailers that want an automated phone agent to handle basic inbound call traffic without investing in a full contact center platform.

Wrapping Up: The Enterprise Choice for Modern Contact Centers

Most platforms in this list are either built for developers who want to prototype quickly or for small businesses that need a basic phone answering tool. Retell AI itself falls into the developer category: it makes it easy to stand up a voice agent, but it does not have the quality assurance, compliance monitoring, coaching, or conversation intelligence that enterprise contact centers require.

Level AI is different. It was purpose-built for enterprise contact centers and approaches the problem from the inside out. Instead of starting with a voice bot and adding enterprise features later, Level AI starts with the full picture of what a contact center needs: a voice AI platform that automates routine calls, real-time agent assist that guides human agents during live conversations, automated QA that scores every call without manual effort, and conversation intelligence that gives leadership visibility into what is happening across the entire operation.

Enterprises in financial services, healthcare, insurance, and retail use Level AI because it solves the whole problem, not just one part of it. If you are evaluating Retell AI alternatives for your enterprise, Level AI is the only platform in this comparison that gives you a complete, integrated answer.

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