ElevenLabs Voice Agent Alternatives for Enterprise: A Shunya Comparison

ElevenLabs has expanded well beyond text-to-speech.

Its ElevenAgents platform now brings together voice, conversation workflows, knowledge bases, tools, telephony, testing, analytics, and multimodal interactions. The platform supports 31+ languages for agents, a large professional voice catalogue, visual workflow building, RAG, custom LLMs, webhooks, MCP tools, call transfers, and both web and phone deployments.

That makes ElevenLabs an important platform to evaluate when building enterprise voice agents.

Shunya takes a different approach.

Its Voice Agent platform combines STT, knowledge-grounded reasoning, TTS, enterprise workflows, and telephonyin one architecture. Shunya’s voice agents are designed around Listen, Ground, Decide, Translate, and Speak, with responses grounded in enterprise knowledge, SOPs, business rules, and connected systems.

This creates an important architectural distinction:

ElevenLabs brings its voice-first technology into a broad agent-building platform. Shunya builds the voice agent around an enterprise intelligence layer.

For organizations evaluating ElevenLabs voice agent alternatives, the meaningful questions go beyond voice quality:

How does the agent reason?

How is enterprise knowledge grounded?

What can it do during a call?

How well does it handle multilingual conversations?

How does it work with telephony?

Where can it be deployed?

How much does a completed interaction cost?

What is ElevenAgents?

ElevenAgents is ElevenLabs’ current platform for building and deploying conversational AI agents.

It brings several pieces together:

Voice

LLMs

Workflows

Knowledge

Tools

Telephony

Testing

Analytics

The platform supports both a developer toolkit and a visual workflow builder, making it possible to create anything from relatively simple conversational agents to multi-step workflows.

ElevenLabs also positions Agents across:

Web

Mobile

Telephony

and multimodal experiences.

This is an important evolution from the company’s original TTS-focused identity.

Today, an enterprise can use ElevenAgents to build an agent that:

Answers a customer’s question

→ retrieves information

→ calls an API

→ updates a system

→ transfers the conversation

all within one interaction.

Shunya approaches the voice agent as an enterprise intelligence layer

Shunya’s Voice Agent architecture starts from the speech stack itself.

Its documented flow is:

STT + Knowledge-Grounded LLM + TTS

and each call passes through:

Listen

→ Ground

→ Decide

→ Translate

→ Speak.

The important part is Ground.

Shunya explicitly connects the agent to:

Knowledge graphs

SOPs

Business rules

Enterprise data

and backend systems.

That means a voice agent can be built around the company’s actual operating knowledge rather than relying only on a general-purpose model.

For example:

“Can I waive this late fee?”

The relevant answer might depend on:

Customer history

Account status

Product policy

Eligibility rules

Approval limits

Previous interactions

A production agent therefore needs more than natural language generation.

It needs grounded reasoning.

Voice-first platform versus enterprise intelligence platform

The architectural distinction becomes clearer when we look at the complete conversation.

ElevenLabs

A typical ElevenAgents architecture can combine:

Voice input

↓

ElevenLabs agent

↓

LLM

↓

Knowledge / RAG

↓

Tools / APIs

↓

Voice output

ElevenLabs lets teams use its own supported models or connect a custom LLM, including an externally hosted model server.

Shunya

Shunya’s architecture is more vertically integrated:

Voice input

↓

STT

↓

Knowledge graph + SOPs + business rules

↓

Reasoning

↓

Enterprise action

↓

TTS

↓

Customer

Neither approach is universally appropriate.

The important architectural question is:

How much of the intelligence layer do you want to assemble and control yourself?

ElevenLabs has an unusually strong voice layer

This is the area where ElevenLabs has a natural advantage in product history and positioning.

Its current agent builder provides access to 5,000+ professional voices, multi-voice conversations, voice selection, and voice design.

That matters for applications where the voice itself is a major part of the product.

Examples include:

Premium customer experiences

Brand assistants

Interactive media

Digital characters

Training simulations

Multilingual customer-facing agents

Shunya also provides a substantial production voice layer, with 46 documented voices across 23 Indic languages plus English, alongside broader global and Asian language synthesis.

But Shunya’s main distinction isn’t the size of the voice library.

It is multilingual enterprise voice identity plus speech infrastructure.

Multilingual voice agents

ElevenAgents currently supports 31+ languages and lets teams configure additional languages with language-specific voices. Its documentation recommends selecting voices specifically trained for each target language to improve pronunciation and regional accents.

ElevenLabs also supports language detection and language-specific first messages. However, its current documentation notes that language selection is fixed for the duration of a call once established.

Shunya’s architecture combines global, Asian, and 23 Indic language voice applications, with 46 documented TTS voices across 23 Indic languages plus English. Its ASR layer supports 216+ languages and mixed-language conversations.

That makes the evaluation particularly interesting for enterprises serving India and Asia.

A real conversation might contain:

“Sir, mera payment kal ho jayega, but I need the confirmation today.”

The system has to recognize:

Hindi

English

financial terminology

natural conversational intent

and then produce an appropriate response.

For Indian enterprise voice AI, test language switching, regional pronunciation, names, currency, numbers, and code-switching, rather than simply checking language counts.

Knowledge bases and RAG

ElevenAgents provides a dedicated Knowledge Base.

Documents can be supplied through two primary modes:

Full context

or:

RAG

With RAG, the platform retrieves only the passages relevant to the current question rather than placing the whole document into the model context. ElevenLabs says this allows significantly larger knowledge bases and can reduce hallucinations, with approximately 250 ms additional latency from the retrieval process.

This is useful for:

Product documentation

Policies

FAQs

Technical documentation

Internal knowledge

Shunya takes a different architecture.

Its Voice Agent platform uses knowledge graphs, enterprise rules and structured workflows to ground responses.

A knowledge graph can be particularly useful when relationships matter.

For example:

Customer → account → product → policy → eligibility → action

rather than treating every document as an isolated chunk of text.

The important enterprise question is therefore not:

“Does the platform have RAG?”

It is:

“Can the agent reliably retrieve the right information and apply it to the customer’s actual situation?”

Tools and enterprise actions

ElevenAgents provides several classes of tools:

Webhook tools

Code tools

MCP tools

Client tools

System tools

These allow agents to retrieve live information, execute actions, interact with applications, transfer calls, and perform other functions.

For example, a webhook can:

Look up an order

Check appointment availability

Update a database

Initiate a return

ElevenLabs also supports MCP connections to external tools and data sources.

Shunya similarly connects Voice Agents to:

CRM systems

Enterprise APIs

Telephony

E-commerce

Messaging systems

Its current documented integrations include Salesforce, Zoho, HubSpot, Shopify, WooCommerce, Odoo, Cisco, Avaya, Exotel and Knowlarity.

The important metric here is:

successful task completion

not:

number of integrations.

A good test is:

Customer asks for an address change → agent verifies identity → checks eligibility → updates backend → confirms the change.

That demonstrates actual agent capability.

Realtime latency and conversation quality

ElevenLabs currently markets ElevenAgents as providing sub-second response times for inbound and outbound calls.

Its platform also provides controls for turn-taking, interruptions and pacing.

This is important because a voice agent has to feel conversational, not like a chat interface being read aloud.

Shunya publishes a different measurement:

<1.5 second end-to-end voice-to-voice response

with a documented breakdown of approximately:

300 ms ASR

100 ms translation

400 ms synthesis

and additional pipeline headroom.

These numbers should not be presented as an audited head-to-head benchmark.

The measurement definitions may differ.

For an enterprise evaluation, measure the same workflow on both:

User stops speaking

→ ASR

→ knowledge retrieval

→ reasoning

→ tool execution

→ TTS

→ first audible response

Then test the harder case:

the user interrupts the agent halfway through its response.

That is where turn-taking quality becomes visible.

Telephony

ElevenAgents supports phone conversations through Twilio, with both inbound and outbound calls. Existing Twilio infrastructure can also be connected through its register-call approach.

For Enterprise customers, ElevenLabs also supports SIP trunking. Its current SIP infrastructure provides regional endpoints for US, EU, India and Singapore.

The platform supports human transfer through its transfer_to_number system tool, including conference transfer, blind transfer and SIP REFER in supported configurations.

Shunya’s Voice Agent platform supports enterprise telephony integrations including:

Cisco

Avaya

Exotel

Knowlarity.

Its broader speech stack also supports telephony audio formats such as μ-law and A-law.

For contact-center deployments, evaluate:

Inbound calls

Outbound calls

SIP

Call transfers

IVR

Barge-in

Human handoff

Regional routing

Audio quality

Concurrency

These are far more representative of production performance than a browser-based voice demo.

Human handoff is part of a good voice agent

A voice agent should not try to solve everything itself.

There are situations where a human should take over.

ElevenLabs supports transfer to external phone numbers or SIP URIs and can pass a summary message to the human operator in supported transfer configurations.

It also supports agent-to-agent transfers, allowing an initial agent to route the conversation to a specialist agent.

Shunya’s enterprise architecture similarly supports escalation and handoff workflows.

The benchmark should ask:

Does the agent recognize when it should escalate?

Does it transfer quickly?

Does the human receive enough context?

Does the customer have to repeat the entire conversation?

Human handoff is not a failure state.

In many enterprise workflows, it is part of the intended design.

Multimodal agents

ElevenAgents isn’t limited to phone conversations.

Its platform supports agents across:

Telephony

Web

Mobile

and multimodal interfaces.

The same agent architecture can therefore support a customer through different interaction surfaces.

ElevenLabs also provides SMS conversations through Twilio integrations.

Shunya’s broader platform is similarly designed around multiple enterprise channels, including:

Phone

Web

Contact centers

Messaging

and connected devices.

This matters for enterprises trying to create a consistent customer journey across voice and digital channels.

Testing, evaluation and observability

ElevenAgents includes built-in testing, evaluations and analytics. ElevenLabs explicitly positions monitoring and evaluation as part of its agent lifecycle, rather than something added only after deployment.

Its tools include capabilities for monitoring agent performance and evaluating conversations at scale.

Shunya’s platform similarly brings build, test, deploy and monitor into one workspace, with the ability to compare prompts, monitor latency and validate responses before and after deployment.

Shunya’s speech intelligence layer also provides:

Intent

Sentiment

Diarization

Summarization

and other transcript-level intelligence.

For production teams, the important loop is:

Build

→ Test

→ Deploy

→ Monitor

→ Identify failure

→ Fix

→ Re-test

A voice agent is not finished when the first call succeeds.

Security, data retention and enterprise controls

ElevenLabs offers enterprise controls including data residency in the US, EU and India, custom SSO, enterprise access controls, SLAs and DPA terms.

Its HIPAA-eligible setup uses Zero Retention Mode and a BAA for eligible Enterprise customers. ElevenLabs states that, under that configuration, PHI is not retained in transcripts, audio recordings, tool calls, analytics or system logs.

ElevenLabs also provides configurable retention settings. By default, conversation transcripts and recordings are retained for two years, but the retention period can be changed or data can be scheduled for deletion.

Shunya provides a more deployment-oriented enterprise model:

Cloud

Private VPC

On-premise

Edge.

Shunya states that Private VPC keeps data within the customer’s network perimeter, while on-premise deployment runs inside the customer’s own data center.

For regulated deployments, therefore, the evaluation should include both:

data governance

and:

where the actual inference runs.

Pricing

ElevenLabs currently offers several ElevenAgents plans:

Plan	Monthly price	Included minutes	Additional call minute
Free	$0	15	$0.080
Starter	$6	75	$0.080
Creator	$22	275	$0.080
Pro	$99	1,238	$0.080
Scale	$299	3,738	$0.080
Business	$990	12,375	$0.080
Enterprise	Custom	Custom	Custom

ElevenLabs states that LLM and telephony costs are billed separately, while burst pricing can reach $0.16/minutewhen calls exceed the normal concurrency limit.

Shunya currently lists Meera Voice Agents at $0.0526/minute, with the published rate including:

Speech recognition

LLM reasoning

Text-to-speech

Turn-taking

Barge-in

Orchestration.

This creates different commercial models.

ElevenLabs: platform usage + external provider costs.

Shunya: all-inclusive core voice-agent conversation rate.

For an enterprise procurement exercise, calculate:

Cost per connected call

Cost per completed task

Cost at peak concurrency

Telephony

LLM

TTS/STT

Enterprise deployment

rather than comparing only the advertised per-minute rate.

Where ElevenLabs fits

ElevenLabs is particularly relevant when you need:

High-quality expressive voices

Its voice technology remains one of the central strengths of the platform.

Large professional voice selection

ElevenAgents provides access to 5,000+ professional voices, while the wider ElevenLabs platform advertises an even larger voice ecosystem.

Flexible agent workflows

The visual workflow builder supports multi-step conversations and complex agent flows.

Knowledge-grounded conversations

Knowledge bases and RAG allow agents to use organization-specific content.

External tools

Webhooks, code, MCP and system tools allow agents to interact with external systems.

Flexible LLM architecture

Teams can use integrated models or connect a custom LLM server.

Multimodal deployment

Agents can run across web, mobile and telephony.

Where Shunya fits

Shunya is particularly relevant when the voice agent is expected to operate as part of a larger enterprise intelligence architecture.

Knowledge-grounded reasoning

Responses can be grounded in knowledge graphs, SOPs and business rules.

Global, Asian and Indic voice experiences

Shunya combines global, Asian and 23 Indic languages, with 46 documented TTS voices across 23 Indic languages plus English.

Large multilingual speech-recognition coverage

The Voice Agent platform currently documents 216+ language ASR, including multilingual and code-switched speech.

Enterprise actions

Agents can connect to enterprise systems to support workflows such as KYC, payments, appointments, customer support and collections.

Integrated speech stack

STT, TTS, speech intelligence and Voice Agents sit inside the wider Shunya platform.

Flexible deployment

Cloud, Private VPC, on-premise and edge deployment options are available.

ElevenLabs and Shunya by use case

Use case	ElevenLabs	Shunya
General voice agents	Strong fit	Strong fit
Premium voice experiences	Strong fit	Strong fit
Large professional voice catalogue	Strong fit	46 documented TTS voices
Expressive voice	Strong fit	11 styles
Visual workflows	Yes	Yes
Knowledge base	Yes	Yes
RAG	Yes	Knowledge-grounded architecture
Custom LLM	Yes	Yes / integrated architecture
Webhook tools	Yes	Yes
MCP tools	Yes	Platform-dependent
Agent-to-agent transfer	Yes	Enterprise workflows
Human phone transfer	Yes	Yes
Inbound calls	Yes	Yes
Outbound calls	Yes	Yes
Multilingual agents	31+ languages	Global + Asian + 23 Indic
Indic voice agents	Available	Core capability
Code-switched speech	Supported	Core speech capability
Telephony / SIP	Yes	Yes
Speech intelligence	Agent analytics	Integrated speech intelligence
Cloud	Yes	Yes
Private VPC	Enterprise options	Yes
On-premise	Not the standard deployment model	Yes
Edge	Not a primary deployment model	Yes
Pricing	Platform + provider costs	All-inclusive core agent rate

The table summarizes documented capabilities and current platform positioning. Actual suitability depends on implementation and enterprise requirements.

How to benchmark ElevenLabs against Shunya

The strongest evaluation uses real customer workflows.

Don’t start with:

“Hello, how can I help you?”

Build a test set around the work the agent actually needs to perform.

For example:

Customer support

Collections

KYC

Appointment booking

Order management

Renewals

Outbound qualification

Then introduce realistic complications:

Interruptions

Background noise

Hindi-English code-switching

Names

Numbers

Currency

Acronyms

Ambiguous requests

Follow-up questions

Policy exceptions

For each platform, measure:

Speech recognition

Did the agent understand the customer accurately?

Response latency

Measure:

user stops speaking → first audible response

not simply TTS generation time.

Turn-taking

Does the agent know when to speak?

Can the customer interrupt?

Does the agent stop naturally?

Knowledge accuracy

Did the agent use the correct source?

Did it apply the right business rule?

Task completion

Did the requested action actually happen?

Voice quality

Evaluate:

Naturalness

Pronunciation

Pacing

Expression

Voice consistency

Multilingual performance

Test conversations where the user changes language or mixes languages naturally.

Human handoff

Does the human operator receive the relevant context?

Telephony quality

Test the actual production call path.

Reliability

Run the same workflows at realistic concurrency.

Cost

Calculate:

cost per connected call

cost per completed task

and total cost at production scale.

The real difference is what sits behind the voice

ElevenLabs and Shunya now overlap in many areas.

Both offer:

Voice agents

Knowledge

Tools

Telephony

Workflows

Analytics

Multilingual capabilities

Enterprise controls

The distinction is the architecture underneath them.

ElevenLabs has built an increasingly complete agent platform around its voice technology, giving developers a highly capable environment for creating conversational and multimodal agents.

Shunya builds the voice agent around an enterprise intelligence layer that combines speech recognition, knowledge graphs, business rules, reasoning, speech synthesis and enterprise deployment.

That matters when the objective changes from:

“Build an AI that can talk.”

to:

“Build an AI that can understand our business, follow our rules, take the right action and talk to our customers.”

The second problem requires more than a good voice.

It requires grounding, reasoning, action and operational control.

Final words

ElevenLabs has evolved from a leading voice-generation platform into a full agent-building environment, with workflows, knowledge bases, RAG, tools, custom LLM support, telephony, evaluations and multimodal deployment.

Its biggest strengths remain closely connected to what made the company successful in the first place:

voice quality

expressiveness

voice variety

and voice-centric developer tooling.

That makes ElevenAgents highly relevant for enterprises building brand-facing assistants, customer-service agents, multimodal experiences and realtime voice applications.

Shunya approaches the same market from a different foundation.

Its Voice Agent platform combines STT, knowledge-grounded reasoning and TTS, with business knowledge, SOPs, rules, enterprise APIs and telephony connected to the same conversation architecture.

Its speech layer combines global, Asian and 23 Indic languages, with 46 documented TTS voices across 23 Indic languages plus English and 216+ language speech recognition.

The deployment story is also different.

Shunya supports cloud, Private VPC, on-premise and edge, giving enterprises more control over where their voice intelligence runs.

For organizations primarily evaluating voice quality, expressive interaction, large voice choice and a flexible agent-building environment, ElevenLabs offers a compelling platform.

For organizations evaluating enterprise-grounded voice agents, multilingual speech across global, Asian and Indic markets, business-system integration, telephony, and flexible deployment, Shunya offers a different architectural approach.

The best way to compare them is not another feature checklist.

Take a real customer workflow.

Give both agents the same knowledge.

Connect the same backend.

Use the same telephony environment.

Then measure:

Did the agent understand?

Did it use the correct knowledge?

Did it follow the business rules?

Did it complete the task?

Did it handle interruptions naturally?

Did it escalate correctly?

Did it work across the languages your customers actually use?

What did the completed interaction cost?

Because enterprise voice AI isn’t ultimately about how impressive an agent sounds in a demo.

It is about how reliably the agent can turn a conversation into the right outcome.

Frequently asked questions

What is ElevenAgents?

ElevenAgents is ElevenLabs’ platform for building and deploying conversational and multimodal AI agents, with voice, workflows, knowledge bases, tools, telephony, testing and analytics.

Is Shunya an ElevenLabs Voice Agent alternative?

Yes. Shunya provides enterprise Voice Agents combining speech recognition, knowledge-grounded reasoning, TTS, enterprise workflows and telephony, with cloud, Private VPC, on-premise and edge deployment options.

How many languages does ElevenAgents support?

ElevenLabs’ current agent-building documentation lists 31+ languages for ElevenAgents.

What languages does Shunya Voice Agent support?

Shunya’s voice stack combines global, Asian and 23 Indic language experiences, with 46 documented TTS voices across 23 Indic languages plus English and 216+ language ASR.

Does ElevenAgents support knowledge bases?

Yes. ElevenAgents supports document-based knowledge bases and can use either full context or RAG to retrieve relevant information during conversations.

Does Shunya use RAG?

Shunya’s Voice Agent architecture focuses on knowledge graphs, SOPs, business rules and enterprise data for grounded reasoning.

Can ElevenAgents call external APIs?

Yes. ElevenAgents supports webhooks, code tools, MCP tools, client tools and system tools.

Can Shunya voice agents take actions?

Yes. Shunya documents enterprise workflows including KYC verification, appointment booking, payment reminders and customer support, with connections to enterprise systems.

Does ElevenAgents support inbound and outbound calls?

Yes. ElevenLabs supports both inbound and outbound calls through Twilio and supports SIP trunking for Enterprise customers.

Does Shunya support telephony?

Yes. Shunya integrates with telephony systems including Cisco, Avaya, Exotel and Knowlarity.

Does ElevenAgents support human handoff?

Yes. ElevenLabs supports transfer to external phone numbers and SIP URIs, as well as agent-to-agent transfers.

Does Shunya support human escalation?

Yes. Shunya Voice Agents support escalation and handoff workflows as part of its enterprise agent architecture.

Does ElevenAgents support custom LLMs?

Yes. ElevenLabs lets teams connect a custom LLM server through an external endpoint, including OpenAI-compatible APIs.

Does Shunya support custom models?

Yes. Shunya’s wider platform supports purpose-trained custom SLMs and enterprise-specific intelligence layers.

Does ElevenLabs support enterprise data residency?

Yes. ElevenLabs currently advertises enterprise data residency in the US, EU and India, along with SSO, enterprise access controls and custom DPA/SLA terms.

Does Shunya support private deployment?

Yes. Shunya supports Private VPC, on-premise and edge deployment, in addition to cloud.

What does ElevenAgents cost?

ElevenLabs currently charges $0.08 per additional call minute on its published self-serve plans, with LLM and telephony costs billed separately. Subscription plans range from Free to Business, with Enterprise pricing custom.

What does Shunya Voice Agent cost?

Shunya currently lists Meera Voice Agents at $0.0526 per minute, with recognition, reasoning, TTS, turn-taking, barge-in and orchestration included in the published rate.

How should enterprises compare ElevenLabs Voice Agent alternatives?

Use the same customer workflows, knowledge sources, tools, languages, telephony environment and traffic profileon each platform. Measure latency, speech accuracy, grounding, task completion, interruption handling, handoff quality, reliability and total cost per completed interaction.