Top 6 of 22 researched candidates
Alternatives to Cartesia
Find a better fit for what you need. Compare alternatives to Cartesia with sourced features, strengths and trade-offs side by side.
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Evidence-backed shortlist
Closest researched alternatives to Cartesia
Ordered by the requirements met, strengths preserved, explicit trade-offs and research coverage. Sponsorship does not enter the order.
- 01
ElevenLabs Agents
Hosted platform for building voice and chat agents, with telephony, SDKs and a choice of LLM.
From FreeWhy it's on this listWrites code · PartialElevenLabs agents do not author code themselves; the Cursor integration lets an agent launch Cursor background agents that do, and needs a paid Cursor plan.Evidence ↗
Where it improves on Cartesia
- +Debugs and fixes · PartialBug fixing is delegated: the agent starts and steers a Cursor background agent, which diagnoses and lands the change; ElevenLabs itself never touches the repository.Evidence ↗
- +Done-for-you service · PartialSelf-serve software you run, but enterprises can buy ElevenLabs Forward Deployed Engineers who scope, build and stabilise the deployment; no price is published.Evidence ↗
Trade-offs against Cartesia
- −In your editor · NoThe vendor enumerates its surfaces as web widgets, mobile apps, phone systems and custom integrations; no editor or IDE extension appears in that list.Evidence ↗
35/35 researched criteria - 02
Vapi
Developer platform for building, testing and deploying voice AI agents that make and receive phone calls.
From $0.05/minuteWhy it's on this listDone-for-you service · PartialYou build and run the agent yourself; the Scale contract adds an embedded Vapi engineer for the go-live, not a done-for-you build.Evidence ↗
Where it improves on Cartesia
- +Multi-agent · YesSquads route one conversation across several specialised assistants with context-preserving handoffs.Evidence ↗
- +Open models · YesOpen-weight models reach the pipeline through Groq, Together AI, Mistral, DeepSeek and OpenRouter, or a self-hosted server.Evidence ↗
Trade-offs against Cartesia
- −Seat model · NoNothing is priced per seat: the plan table meters call minutes and concurrent lines only, and members are invited with RBAC roles.Evidence ↗
- −Certifications · PartialSOC 2 Type II and a HIPAA BAA sit in the Scale contract, and the plan table shows SOC2 only in that column; HIPAA mode is a $2,000/month add-on on either plan.Evidence ↗
35/35 researched criteria - 03
PolyAI
Enterprise platform for building voice and chat agents that resolve customer calls, priced per minute.
Why it's on this listWrites code · PartialWren generates agent configuration and the Python tool functions that call your APIs from a description; it does not author application source code.Evidence ↗
Where it improves on Cartesia
- +Debugs and fixes · PartialWren diagnoses production conversations (tool calls, latency, drop-offs) and can implement the fix on a branch; the subject is agent behaviour, not application code.Evidence ↗
- +Writes tests · PartialIt authors and maintains conversation simulation tests that run in CI; these are agent scenario tests, not unit tests for source code.Evidence ↗
Trade-offs against Cartesia
- −Self-hosted · NoRuns only as PolyAI-hosted SaaS on AWS with region-specific workspaces; no on-premise or customer-cloud deployment appears anywhere in the vendor's docs or security pages.Evidence ↗
- −Seat model · NoNo per-seat price is published; billing tracks conversation volume, and team members are added by invitation with role-based permissions.Evidence ↗
- −Pooled budget · PartialConversation volume draws on one account-level Subscription Volume of CX Tokens, but the Wren builder allowance is per person and not shared.Evidence ↗
35/35 researched criteria - 04
LiveKit Agents
Open-source Python and Node.js framework for voice AI agents, with LiveKit Cloud hosting, telephony and observability.
From FreeWhy it's on this listMulti-agent · YesMultiple agents in one session via handoffs, plus a supervisor pattern where one agent keeps control and delegates to scoped tasks.Evidence ↗
Where it improves on Cartesia
- +Open models · YesOpen-weight models are the recommended default in LiveKit Inference (Gemma 4 31B, GPT OSS 120B, DeepSeek), and the Ollama plugin runs models locally.Evidence ↗
- +Self-hosted · YesAgents are containers you can run on your own Kubernetes; the LiveKit media server and SIP service are separately self-hostable. Self-hosted agents still meter WebRTC participant minutes if they connect to LiveKit Cloud.Evidence ↗
Trade-offs against Cartesia
- −MCP server · PartialThe agent is the MCP client: it consumes tools from remote HTTP or local stdio MCP servers, Python only. LiveKit does not expose a running agent as an MCP server for another agent to query.Evidence ↗
- −Seat model · NoNot seat-priced. Plans are per project with usage allowances, and neither the plan cards nor the feature matrix publishes a seat count, floor or ceiling; dashboard users get admin, write or read roles.Evidence ↗
- −Pooled budget · PartialNo per-user balances: allowances pool inside a project. Sharing one plan across projects, and quotas managed at workspace level, are Enterprise only.Evidence ↗
35/35 researched criteria - 05
OmniDimension
No-code platform for building voice AI agents and running them on phone, web chat, WhatsApp, email and SMS.
From $15/monthWhy it's on this listDone-for-you service · PartialYou run the software yourself from a no-code dashboard, but the terms of use offer paid professional services on request, and the Enterprise tier adds a dedicated account manager, priority onboarding and live training.Evidence ↗
Where it improves on Cartesia
- +Multi-agent · PartialWorkflows chain agent actions and can call sub-workflows, so several agents run in sequence, but the docs describe no agent-to-agent handoff or shared-state orchestration.Evidence ↗
- +Open models · YesOpen-weight families are selectable through the OpenRouter and Bedrock entries in the catalogue, so you are not confined to closed frontier models.Evidence ↗
Trade-offs against Cartesia
- −Claude · NoThe pricing page publishes the full model catalogue and its alphabetical LLM list runs from Bedrock straight to Gemini with no Anthropic or Claude entry; the agent API model enum likewise names none.Evidence ↗
- −On the command line · PartialThe only terminal-run component is the local MCP server, installed and diagnosed with npx sub-commands; no CLI exists for building agents or dialling calls on its own.Evidence ↗
- −Self-hosted · NoNo self-hosted, VPC or on-premise option appears anywhere in the pricing tiers or docs; even the white-label agency product runs on the vendor's infrastructure with the customer only pointing DNS at them.Evidence ↗
35/35 researched criteria - 06
Retell AI
Pay-as-you-go platform for building, testing and running AI phone, chat and SMS agents.
From $0.07/minuteWhy it's on this listWrites tests · PartialProduces graded conversation test cases for its own agents, not software tests.Evidence ↗
Where it improves on Cartesia
- +Done-for-you service · PartialYou run the software yourself in Retell's no-code studio; hands-on implementation by Retell's people is sold only as an Enterprise add-on, not as a managed service.Evidence ↗
- +Multi-agent · YesOne call can be handed between several specialised AI agents mid-conversation, with the destination agent inheriting the full transcript, so work is split across agents rather than one monolith.Evidence ↗
Trade-offs against Cartesia
- −On the command line · NoThe docs enumerate every way to drive Retell: dashboard, REST API, Node/Python SDKs and MCP server. No command-line tool is among them.Evidence ↗
- −Self-hosted · NoThe platform runs on Retell's own infrastructure: pay-as-you-go uses shared servers and the most isolation offered is a dedicated Retell server sold as an Enterprise add-on, with no customer-infrastructure deployment documented.Evidence ↗
- −Free tier · PartialYou can sign up and run real calls without talking to sales, but the free allowance is a one-off $10 trial credit per email address rather than a standing free plan.Evidence ↗
34/35 researched criteria · 1 not established
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How the shortlist is calculated
Comparable first. We consider listings in the same category as Cartesia and alternatives previously researched for this page.
Requirements first. We prioritise your selected needs, then shared strengths, fewer documented trade-offs, more complete research and finally alphabetical order.
Unknown remains unknown. Missing evidence is never converted into a benefit or a trade-off. Every improvement shown above comes from the same sourced criterion as the listing.
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