Alternatives to a hosted AI phone agent come in three shapes: finished agent platforms with telephony included, developer toolkits you build on, and speech APIs that handle only the voice. The shape decides who does the work, so ask every vendor what's included between a ringing phone and a finished call before you compare how the demo sounds.
Retell AI lets businesses put voice agents on real phone lines to answer, qualify and book callers. If you're weighing it up or already using it and want something shaped differently, there's a wide field to choose from, and the products in it are less alike than their demos suggest.
These nine are in no particular order. Some are built for Indian languages, some are open source, some are enterprise contact-centre suites, and one is a general AI assistant that happens to make calls.
Who does the work between the ring and the hang-up?
Voice agent demos all sound impressive. That's the problem: the demo tells you about the voice, and very little about who'll be doing the work once it's live.
A voice agent product can be one of three things. It can be a finished phone agent, where you build the agent in a dashboard and the platform handles phone numbers, routing and monitoring. It can be a developer toolkit, where you get the parts and assemble them. Or it can be the speech layer only, turning voice into text and back again very quickly.
LiveKit, Deepgram and the speech models from Cartesia sit towards the building-blocks end. They're strong foundations, but call routing, number setup, testing and monitoring become your job, or your developer's. That's the right trade if you've got engineers and want control. It's the wrong one if you wanted an agent answering calls by Friday.
Nine voice agent platforms to look at
Alphabetical, and nothing more.
Bolna
Best for: Businesses calling customers in Indian languages such as Hindi, Hinglish, Tamil and Telugu, with a choice of speech models and India or USA data residency.
Cartesia
Best for: Developers who want real-time text to speech and speech to text across 44 languages, with managed phone agents from the same API (vendor claims).
Deepgram
Best for: Engineering teams wanting speech to text, text to speech and LLM orchestration in one real-time API, with turn-taking handled inside and their own models allowed.
Dialpad
Best for: Companies that want a business phone and contact-centre system first, with AI recaps, call scoring, real-time assist and AI agents across calls and messages.
Lindy
Best for: Small teams that want one AI assistant connected to their other apps, with phone calls handled as one job among meetings and admin.
LiveKit
Best for: Developers who want an open source framework to build, test, deploy and observe voice agents, with turn detection and interruption handling included.
Parloa
Best for: Enterprise customer service teams building, testing and scaling voice and chat agents from one agent management platform.
PolyAI
Best for: Enterprises designing and refining dialog agents for customer calls such as booking, billing and authentication, using the vendor's own studio and dialog model.
Regal
Best for: Contact centres wanting agents on phone, SMS, chat and web, plus a journey builder, simulations, branded caller ID and a sales dialer in one platform.
The nine in one table
| Tool | Shape of product | Good for |
|---|---|---|
| Bolna | Indian-language voice agents | Calls in Hindi, Hinglish, Tamil and Telugu |
| Cartesia | Speech models plus managed agents | Speech models and managed agents through one API |
| Deepgram | Speech API with agent layer | One real-time API for a voice agent |
| Dialpad | Phone system with built-in AI | Calling, call scoring and assist in one phone system |
| Lindy | General AI assistant with phone calls | Phone calls as one job of a wider assistant |
| LiveKit | Open source developer framework | Developers building their own agent on open source |
| Parloa | Enterprise customer-service agents | Large service teams managing voice and chat agents |
| PolyAI | Enterprise call-handling agents | Booking, billing and authentication calls at enterprise scale |
| Regal | Contact-centre agent platform | Contact centres running phone, SMS and chat agents |
Six shapes of voice agent product
Built for Indian languages. Bolna builds inbound and outbound agents in 20+ languages, including Hindi, Hinglish, Tamil and Telugu, and says you can keep data in India or the USA.
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Enterprise customer service. PolyAI and Parloa are aimed at large service teams. One brings its own dialog model and studio; the other calls itself an agent management platform for both voice and chat.
Contact-centre platforms. Regal is built for contact centres, with agents across phone, SMS and chat plus tools such as branded caller ID and a sales dialer.
Phone system first. Dialpad is a business phone and contact-centre system with AI running across calls, messages and meetings. Choose this shape if you need the phone system anyway.
General assistant. Lindy is an AI assistant that connects to your other tools, with phone calls as one of many jobs. It suits small teams more than call-heavy operations.
Developer foundations. The three building-block products from the first section sit here.
Five questions for every voice agent demo
- Who sets up phone numbers and call routing, you or the vendor?
- How do you test an agent before it takes real calls, and can you replay failed calls?
- What happens when the agent can't answer: does it transfer to a person, and how?
- Which languages and accents does it handle on a live phone line, not only in the demo?
- Where is call data stored, and what compliance claims can the vendor show you in writing?
My advice for choosing a voice agent
Be honest about who'll run it. If there's no developer on your team, stick to the finished agent platforms, the phone system or the general assistant, and ask for a pilot on one real phone line. If you've got engineers and want full control, the developer foundations will give you more freedom, as long as you plan for the routing and monitoring work.
Either way, judge it on real calls with real callers, not the demo. For more context, my comparison of AI voice agents and traditional call centres sets out where agents help and where people still matter, and my guide to AI phone agents answering calls for small businesses covers the practical side of a first rollout.
When staying where you are makes sense
Switching voice platforms means rebuilding prompts, re-testing call flows and re-connecting your calendar and CRM. If your current agent handles most calls well and the problem is one missing feature, ask your vendor about it first. A move is worth it when the shape of product is wrong for you, not when one setting is.
Do you make voice agent software? Tool makers can ask to be considered for a featured place on this list.
Want your tool on this list? Featured spots and reviews here are paid partnerships. Here's how to partner with me.
Frequently asked questions
What's the difference between a voice agent platform and a speech API?
A voice agent platform gives you a working phone agent with numbers, routing and monitoring. A speech API handles the voice part only, so you or a developer build everything around it.
Do I need a developer to run an AI phone agent?
Not with every product. Finished agent platforms let you build in a dashboard. Developer frameworks and speech APIs assume someone will write and maintain code.
Can an AI voice agent transfer a call to a person?
Most voice agent products support transfers in some form. Ask how it works in practice and test it, because a clumsy handover frustrates callers more than anything.
Are AI voice agents allowed to make outbound calls?
Rules on automated and outbound calls vary by country and sector, so check your regulator's guidance before running outbound campaigns.
How should I test a voice agent before going live?
Run it on one real number with a small group of callers, listen to recordings, check the transfers and fix the failures before you add more lines.
