GreyLabs AI and Shunya: Enterprise Voice Agent Comparison

GreyLabs AI is building a BFSI-focused Voice AI platform for customer interactions across collections, recoveries, customer support, renewals, outbound sales and lead qualification. Its current Voice AI Agents product emphasizes Hindi, English and Hinglish conversations, sub-second response times, CRM and telephony integrations, compliance recording, and India-region data residency.

Shunya approaches enterprise voice agents from a broader speech and intelligence architecture.

Its Voice Agent platform combines STT, a knowledge-grounded reasoning layer, TTS, business workflows and telephony, with conversations moving through five stages: Listen, Ground, Decide, Translate and Speak.

The difference is important.

GreyLabs is deeply focused on BFSI customer operations in India. Shunya is designed as a broader enterprise voice-agent platform that can connect speech, business knowledge and actions across industries.

That makes this comparison less about feature checklists and more about the architecture behind a production voice agent.

What is GreyLabs AI?

GreyLabs AI describes itself as an agentic AI platform for BFSI and fintech, with Voice AI Agents alongside speech analytics and other communication-intelligence products.

Its Voice AI product currently highlights four main application areas:

Collections & recoveries

Customer support

Renewals

Outbound sales & lead qualification

The platform is therefore closely connected to customer-facing financial operations.

A collections agent, for example, may call a customer about an overdue EMI, understand the customer’s response, record a repayment commitment, and move the interaction into the appropriate workflow.

GreyLabs also combines its Voice AI products with Speech Analytics, which covers transcription, keyword and phrase spotting, sentiment and emotion analysis, compliance verification, voice biometrics and acoustic analysis.

That creates a broader conversation-intelligence story around the voice agent.

Shunya approaches the voice agent as an end-to-end system

Shunya’s Voice Agent platform is not positioned as a speech interface sitting in front of a generic chatbot.

Its architecture is explicitly:

STT → Knowledge-Grounded LLM → TTS

with the full call moving through:

Listen → Ground → Decide → Translate → Speak.

The distinction is what happens in the middle.

Shunya says responses can be grounded in:

Knowledge graphs

SOPs

Business rules

Enterprise data

rather than relying on generic model knowledge.

The agent can also connect to existing systems to complete actions such as:

KYC verification

Appointment booking

Payment reminders

Customer support

and other enterprise workflows.

This makes the voice agent an operational layer, not just a conversational layer.

The architecture difference matters

A simple customer-service voice bot can be thought of as:

Speech → AI → Speech

A production enterprise agent often looks more like:

Customer

↓

Speech recognition

↓

Intent + context

↓

Enterprise knowledge

↓

Business rules

↓

Backend systems

↓

Action

↓

Voice response

GreyLabs is strongly oriented around the operational customer journey within BFSI.

Shunya’s architecture is designed to generalize the same model across contact centers, BFSI, healthcare, telecom, retail and e-commerce.

That distinction becomes important when a company wants to use the same voice platform across multiple business units.

BFSI is where GreyLabs has the clearest specialization

GreyLabs explicitly focuses on banking, financial services and insurance.

Its current platform highlights:

Collections

Recoveries

Telesales

Renewals

Customer service

and lead qualification.

Its campaign management examples also include workflows such as:

Loan collections

Payment reminders

Lead qualification

Account opening.

This specialization is significant because BFSI conversations have requirements that generic customer-service agents don’t necessarily handle well.

For example:

“Meri salary late aayi hai. EMI paanch din baad de sakta hoon?”

A production collections agent needs to understand the request, follow the appropriate communication policy, determine whether a promise-to-pay can be recorded, update the relevant system, and confirm the next step.

The conversation is not successful simply because the AI produced a natural sentence.

The workflow has to be completed correctly.

Shunya also targets BFSI, but across a wider enterprise stack

Shunya’s BFSI Voice AI offering includes:

Collections and recovery

KYC and onboarding

Fraud alerts

Loan servicing

Card services

Policy and claims.

The platform is designed to connect with systems containing:

Customer profiles

Loan and account information

CRM data

Telephony

Payment systems

and other enterprise data sources.

Shunya also documents workflows where an agent can log a promise-to-pay, raise a service request or initiate an account-related workflow, while preserving context for human escalation.

So the comparison in BFSI is less about whether either platform can handle collections.

Both are designed for it.

The more useful question is:

How much of the enterprise workflow can the agent understand, ground and execute?

Hindi, Hinglish and Indic speech

This is one of the most important areas for an India-focused voice-agent deployment.

GreyLabs explicitly highlights Hindi, English and Hinglish with natural intonation as part of its Voice AI offering.

That is highly relevant for BFSI because customers rarely speak in carefully structured English.

A real call may sound like:

“Sir, payment kal kar dunga, but amount kaafi zyada hai.”

The agent needs to understand the mixed-language conversation without forcing the caller into a particular language.

Shunya’s speech architecture is designed for multilingual and code-switched conversations, with 216+ language ASRaccording to its current Voice Agent documentation. Its broader voice stack combines global, Asian and 23 Indic languages.

Its TTS documentation also supports 23 Indic languages plus English, with a language-aware preprocessing layer for numbers, dates and script-specific rules, including code-switched text handling.

For an Indian voice-agent benchmark, test:

Hindi

English

Hinglish

Regional terms

Names

Currency

Dates

Numbers

Financial terminology

The language label alone does not tell you how good the conversation will be.

Latency and conversational turn-taking

GreyLabs currently describes its Voice AI Agents as offering sub-second response times and “near-zero latency” for realtime conversations. These are GreyLabs’ own product claims.

Shunya publishes a more detailed end-to-end breakdown.

Its current Voice Agent documentation reports:

<1.5 seconds end-to-end voice-to-voice

with approximately:

300 ms ASR

100 ms translation

400 ms synthesis

and remaining headroom for the rest of the pipeline.

These measurements should not be treated as directly equivalent benchmarks because the vendors may use different environments and definitions.

For a real comparison, measure:

User stops speaking

→ ASR

→ grounding

→ reasoning

→ tool/API action

→ TTS

→ first audible response

That is the latency the customer experiences.

Knowledge grounding and enterprise context

This is one of the clearest architectural areas to investigate.

GreyLabs describes its Voice AI Agents as industry-specific and focused on BFSI conversation workflows. Its platform is designed to connect with CRM, telephony and collections systems.

Shunya explicitly describes grounding responses against a customer’s knowledge graph, SOPs and business rules, rather than relying on generic knowledge.

That becomes important for questions such as:

“Can you waive my late-payment fee?”

The agent shouldn’t improvise.

It should know:

What the policy says

Whether the customer qualifies

What information needs verification

What action is permitted

When to escalate

This is where grounding + business rules + tool execution become more important than conversational fluency alone.

From answering to actually taking action

An enterprise voice agent should be evaluated by what happens after it understands the request.

Consider:

“Please update my registered mobile number.”

A production flow might require:

Identity verification

→ Customer lookup

→ Eligibility check

→ OTP or verification workflow

→ CRM/core-system update

→ Confirmation

Shunya’s current Voice Agent platform explicitly describes agents connecting to enterprise systems to perform workflows such as KYC, appointment booking, payment reminders and customer support.

GreyLabs’ platform similarly focuses on workflow-driven BFSI operations including collections, customer support, renewals and lead qualification, with CRM, telephony and collections-system connectivity.

The right benchmark is therefore:

Task completion rate

rather than simply:

Conversation quality

A beautiful conversation that doesn’t complete the requested action is still an unsuccessful customer interaction.

Telephony and calling workflows

Both platforms are designed for phone-based interactions, which is important for enterprise deployments.

GreyLabs emphasizes telephony integration as part of its Voice AI stack.

Shunya supports telephony integrations including Cisco, Avaya, Exotel and Knowlarity, alongside CRM, e-commerce and messaging integrations.

Shunya also supports telephony-oriented audio formats such as μ-law and A-law through its speech stack.

For a production deployment, evaluate more than whether the platform can place a call.

Test:

Inbound calls

Outbound campaigns

Call routing

Barge-in

Interruption handling

Call transfer

Human escalation

Call recording

Audio quality

Concurrency

A voice agent that performs well in a web demo can behave very differently at scale over a real telephone network.

CRM and enterprise integrations

GreyLabs currently describes native connectivity with CRM, telephony and collections systems. Its wider product suite also integrates with platforms such as Salesforce, Microsoft Dynamics and HubSpot.

Shunya provides a broader set of documented integrations across:

CRM: Salesforce, Zoho, HubSpot

Telephony: Cisco, Avaya, Exotel, Knowlarity

E-commerce: Shopify, WooCommerce, Odoo

Messaging: WhatsApp, LINE, KakaoTalk.

Shunya also supports APIs and webhooks for connecting to existing systems of record.

The important distinction is not the number of logos on an integration page.

It is whether the agent can use those integrations during a conversation to retrieve information and complete an approved action.

Analytics and post-call intelligence

GreyLabs has a notable advantage in that its product portfolio already spans Voice AI Agents and Speech Analytics.

Its Speech Analytics product covers:

Transcription

Keyword and phrase spotting

Emotion and tone detection

Compliance verification

Voice biometrics

Acoustic analysis.

Its Voice AI product also includes campaign monitoring and analytics, including call-level campaign information such as attempts, completed calls and conversion metrics.

Shunya provides conversation intelligence capabilities within its broader platform, including intent, sentiment, diarization, summarization and other transcript-level intelligence.

This creates two different ways of approaching the conversation lifecycle:

GreyLabs: voice agents alongside a dedicated speech-analytics product suite.

Shunya: voice agents as part of a wider speech + intelligence + TTS + agent platform.

For enterprises, both approaches can be relevant depending on whether the priority is BFSI-specific analytics or a broader speech infrastructure layer.

Security, compliance and data residency

Security requirements are particularly important for BFSI voice AI.

GreyLabs currently states that its Voice AI platform provides:

Encryption in transit and at rest

India-region data residency

Comprehensive audit logs

Compliance recording.

Its broader company site currently lists ISO, SOC 2 and DPDP credentials.

Shunya offers multiple deployment models:

Cloud

Private VPC

On-premise

Edge.

Shunya describes Private VPC as deployment inside the customer’s cloud account, on-premise as deployment inside the customer’s data center, and edge as deployment at the branch or device layer.

The right enterprise architecture depends on the organization’s specific security and regulatory requirements.

Neither a compliance badge nor an on-prem checkbox should be treated as sufficient on its own.

A proper review should ask:

Where is audio processed?

Where are transcripts stored?

Where are logs retained?

Can data remain in India?

What happens during human escalation?

How is access controlled?

Deployment flexibility

Deployment is one area where the platforms take different approaches.

GreyLabs is strongly oriented toward BFSI enterprise deployments in India, with its platform built around customer operations and regional compliance requirements.

Shunya explicitly supports four deployment shapes:

Cloud for managed scaling.

Private VPC for dedicated infrastructure.

On-premise for stricter data-sovereignty requirements.

Edge for applications where local processing and resilience are important.

This matters when the voice agent needs to operate under different infrastructure constraints across business units or geographies.

Pricing and total cost of ownership

GreyLabs does not currently publish a detailed public Voice AI pricing table on its Voice AI product page. The current product flow is pilot / demo / sales-led rather than a public per-minute rate.

That makes it important to request a commercial model based on the actual deployment:

Monthly call minutes

Concurrent calls

Inbound vs outbound

Telephony

Integrations

Analytics

Deployment

Support

Shunya currently publishes a public pricing model.

Its Voice Agent service, Meera, is priced at $0.0526 per minute, with recognition, reasoning, synthesis, turn-taking, barge-in and orchestration included in the published all-inclusive rate. Enterprise plans offer higher concurrency, self-hosted deployment and dedicated support.

That makes the two commercial approaches quite different.

GreyLabs: enterprise quote and deployment-specific pricing.

Shunya: public usage pricing plus Enterprise plans.

For procurement, compare cost per completed customer task, not simply cost per minute.

Where GreyLabs fits

GreyLabs is particularly relevant when the primary requirement is India-focused BFSI voice automation.

Its current product is explicitly designed around:

Collections and recoveries

Customer support

Renewals

Outbound sales

Lead qualification.

It also brings together voice automation and speech analytics for financial-services operations.

GreyLabs’ current positioning makes it particularly relevant for organizations that want a voice-agent platform closely aligned with BFSI customer operations and India-region requirements.

Where Shunya fits

Shunya is particularly relevant when the voice-agent requirement extends beyond a single industry or workflow.

The platform is designed around:

Knowledge-grounded enterprise conversations

Global, Asian and 23 Indic language voice experiences

216+ language speech recognition

Code-switched conversations

Enterprise actions

Telephony

CRM and backend integrations

Cloud, private VPC, on-premise and edge deployment.

It also connects voice agents to a wider stack including STT, TTS, speech intelligence and custom SLMs.

That makes Shunya relevant when a business wants voice to become a common intelligence and interaction layer across multiple systems and channels.

GreyLabs AI and Shunya by use case

Use case	GreyLabs AI	Shunya
BFSI collections	Core use case	Core use case
Loan servicing	Strong fit	Strong fit
KYC	Relevant	Core use case
Fraud alerts	BFSI-focused	Core use case
Customer support	Strong fit	Strong fit
Outbound sales	Core use case	Supported
Lead qualification	Core use case	Supported
Renewals	Core use case	Supported
Hindi / English / Hinglish	Core offering	Supported
Indic language voice	Focused Indian-language support	23 Indic TTS languages
Global voice deployment	More India/BFSI focused	Global + Asian + Indic
Knowledge graph / SOP grounding	Product-dependent	Core architecture
Enterprise actions	Workflow-focused	Workflow-focused
Speech analytics	Dedicated product	Integrated intelligence layer
Telephony	Core	Core
CRM integration	Yes	Yes
India-region data residency	Yes	Deployment dependent
Private deployment	Enterprise dependent	Private VPC / on-premise
Edge deployment	Not a primary product message	Available
Public pricing	Not published	Yes
BFSI specialization	Core positioning	One of several enterprise verticals

This table summarizes currently documented capabilities and positioning. Actual deployment suitability should be validated against the customer’s environment.

How to benchmark GreyLabs against Shunya

For this comparison, a meaningful evaluation should use actual BFSI conversations.

Create a test set covering:

EMI reminders

Collections

Promise-to-pay

KYC follow-ups

Loan servicing

Fraud alerts

Card services

Customer support

Lead qualification

Then include the language complexity customers actually use:

Hindi

English

Hinglish

Numbers

Currency

Dates

Customer names

Product names

Financial terminology

Then measure:

Speech recognition

How accurately does the system understand the customer’s words?

Language switching

Can a customer switch between Hindi and English naturally without losing context?

Response latency

Measure the complete:

speech → reasoning → speech

path.

Grounding accuracy

Does the agent provide the answer supported by the organization’s policies and data?

Task completion

Can the agent actually:

retrieve information

update a system

create a request

record a commitment

schedule an action

rather than simply describe what should happen?

Compliance

Does the conversation follow the required script, disclosures, verification and escalation rules?

Human handoff

Can a call be transferred with enough context that the customer doesn’t have to start again?

Voice quality

Evaluate:

naturalness

pronunciation

prosody

expression

telephony clarity

Cost

Measure:

cost per call

cost per connected call

cost per completed task

and total platform cost at production volume.

This makes the benchmark useful to both engineering and business teams.

What an enterprise should actually compare

The most useful decision framework is not:

“Which platform has more features?”

It is:

Speech

Can the system understand your customers and speak their languages naturally?

Intelligence

Can it reason against your actual business knowledge?

Action

Can it complete the workflow?

Conversation

Can it handle interruptions, ambiguity and follow-up questions?

Operations

Can the organization monitor, test and improve thousands or millions of calls?

Compliance

Can the deployment meet the organization’s security, privacy and regulatory requirements?

Economics

Does the cost structure make sense at your expected volume?

A voice agent becomes valuable when all seven work together.

Final words

GreyLabs AI and Shunya are both aimed at production enterprise voice conversations, but their positioning is different.

GreyLabs has built its Voice AI offering specifically around BFSI customer operations in India, with collections, recoveries, support, renewals and outbound sales at the center of the product. It emphasizes Hindi, English and Hinglish, low-latency conversations, telephony and CRM connectivity, auditability and India-region data residency.

Shunya takes a broader enterprise approach.

Its Voice Agent platform combines STT, knowledge-grounded reasoning and TTS, connects conversations to knowledge graphs, SOPs, business rules and enterprise systems, and supports use cases spanning contact centers, BFSI, healthcare, telecom, retail and e-commerce.

The language layer is also broader, combining global, Asian and 23 Indic language voice experiences, with 216+ language ASR and code-switched speech recognition.

The practical distinction is therefore straightforward.

For an organization primarily looking for India-focused BFSI voice automation, GreyLabs’ specialization is directly relevant.

For an organization looking to build knowledge-grounded voice agents across industries, languages, enterprise systems and deployment environments, Shunya provides a broader platform architecture.

Neither comparison should end with a generic “best voice agent” claim.

The meaningful test is the actual workflow.

Take a real customer.

Give the agent real speech.

Connect the real systems.

Use the real business rules.

Then measure:

Did it understand the customer?

Did it answer correctly?

Did it take the right action?

Did it respond quickly?

Did it follow the required policy?

Did the customer need to repeat themselves?

That is what separates a convincing voice demo from a production voice agent.

Frequently asked questions

What is GreyLabs AI?

GreyLabs AI is an enterprise AI platform focused primarily on BFSI and fintech, with products for Voice AI Agents, Speech Analytics and other customer-communication intelligence workflows.

Is Shunya an alternative to GreyLabs AI?

Yes. Shunya provides enterprise Voice Agents that combine speech recognition, knowledge-grounded reasoning, TTS, enterprise integrations and telephony, with deployment options across cloud, private VPC, on-premise and edge.

What does GreyLabs Voice AI specialize in?

GreyLabs currently highlights collections and recoveries, customer support, renewals, outbound sales and lead qualification as its main Voice AI use cases.

What does Shunya Voice Agent specialize in?

Shunya supports enterprise voice workflows across contact centers, BFSI, healthcare, telecom, retail and e-commerce, with conversations grounded in enterprise knowledge and connected systems.

Does GreyLabs support Hindi and Hinglish?

Yes. GreyLabs explicitly lists Hindi, English and Hinglish speech as part of its Voice AI offering.

Does Shunya support Hindi and Hinglish?

Yes. Shunya supports multilingual and code-switched speech, while its broader voice stack includes global, Asian and 23 Indic languages and its ASR platform currently supports 216+ languages.

Does GreyLabs support collections?

Yes. Collections and recoveries are one of GreyLabs’ primary Voice AI use cases, including automated payment reminders and recovery conversations.

Can Shunya voice agents handle collections?

Yes. Shunya’s BFSI platform supports repayment reminders, promise-to-pay conversations and collection outreach, with connected workflows for financial operations.

Can Shunya voice agents access live customer data?

Yes. When connected to core banking, lending, CRM or other enterprise systems, Shunya can retrieve information using the relevant live business context.

Can Shunya voice agents take actions?

Yes. Shunya documents workflows including KYC verification, appointment booking, payment reminders and customer support, with backend system connectivity.

Does GreyLabs integrate with CRM and telephony?

Yes. GreyLabs lists CRM, telephony and collections-system connectivity as capabilities of its Voice AI platform.

Does Shunya integrate with CRM and telephony?

Yes. Shunya documents integrations including Salesforce, Zoho, HubSpot, Cisco, Avaya, Exotel and Knowlarity, along with APIs and webhooks for custom enterprise systems.

Does GreyLabs provide speech analytics?

Yes. GreyLabs has a dedicated Speech Analytics product covering transcription, keyword spotting, sentiment, emotion, compliance verification, voice biometrics and acoustic analysis.

Does Shunya provide speech analytics?

Yes. Shunya’s broader intelligence layer includes capabilities such as intent, sentiment, diarization and summarizationon top of speech transcripts.

Does GreyLabs support India-region data residency?

GreyLabs currently states that its Voice AI platform provides India-region data residency, along with encryption and audit logs.

Does Shunya support private deployment?

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

What is Shunya Voice Agent pricing?

Shunya currently lists Meera Voice Agents at $0.0526 per minute, with recognition, reasoning, synthesis, turn-taking, barge-in and orchestration included in the published rate. Enterprise plans are available for higher concurrency and self-hosted deployments.

Does GreyLabs publish Voice AI pricing?

GreyLabs’ current Voice AI product page does not publish a detailed per-minute pricing table. The current commercial flow is centered on requesting a demo or pilot, so enterprise pricing needs to be obtained from GreyLabs based on the deployment.

How should enterprises compare GreyLabs and Shunya?

Use the same customer workflows, speech samples, languages, knowledge base, integrations and telephony environment on both platforms. Measure speech accuracy, latency, grounding, task completion, compliance, human handoff, call quality and total cost at production volume.

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