Top 12 Voice AI Companies in India (2026): Full Comparison
Voice AI companies in India are no longer competing on novelty. India’s cloud-based contact center market alone is valued at USD 1.4 billion in 2025 and projected to reach USD 7.9 billion by 2034, a shift driven less by curiosity and more by enterprises treating automated calling as core infrastructure for support, sales, and compliance-heavy conversations.
That growth has produced a crowded field, and not every company competing in it is built the same way. Some are specialist platforms tuned for a single workflow, like collections or lead qualification. Others are broad CX suites built to standardize voice alongside chat and WhatsApp across large organizations. A few are infrastructure providers building their own speech models rather than orchestrating third-party ones.
This guide compares the top 12 voice AI companies in India on capabilities, verified pricing, notable clients, and where each one is a genuine fit. This will allow buyers to shortlist based on what a company actually does well rather than how confidently it demonstrates.
TL;DR
- The top voice AI companies in India include DialNexa, Skit.ai, Uniphore, Yellow.ai, Jio Haptik, Kore.ai, Mihup, Rezo.ai, Floatbot, Bolna, Ringg AI, and Gnani.ai, spanning three buying motions: specialist tools, enterprise CX suites, and proprietary speech infrastructure
- For high-volume outbound and inbound calling, DialNexa is built specifically for this with multilingual support and sub-1-second latency. For collections, Skit.ai is voice-first and purpose-built for debt recovery
- Enterprise CX standardization across voice, chat, and WhatsApp is where Uniphore, Yellow.ai, Jio Haptik, and Kore.ai lead, usually at the cost of longer implementation timelines
- Speech accuracy under real conditions matters most for Gnani.ai and Mihup, which build their own speech models instead of orchestrating third-party ones
- Pricing transparency varies a lot across this list. Some companies publish clear per-minute or tiered rates, others are entirely quote-based, so factor that into how long evaluation will take
How We Selected These Companies
- Companies were selected based on relevance to Indian enterprise buyers, not funding size or marketing spend
- Capabilities and positioning are drawn from each company’s own site, cross-checked against reliable sources
- Pricing is included only where publicly disclosed or reliably third-party reported; where a company hasn’t disclosed pricing, client names, or performance numbers, this guide says so directly instead of estimating
- Language coverage is taken from each company’s own stated claims and flagged as such, since production quality on any language varies and should be tested directly with the vendor
- Only companies with evidence of production-scale deployment, not pilot-only claims, were included
- Companies are grouped by buying motion (specialist workflow, enterprise CX suite, or proprietary speech infrastructure) rather than ranked on a single composite score, since fit depends on the buyer’s mandate more than any one company being universally strongest
Top Voice AI Companies in India
1. DialNexa
DialNexa is a Bengaluru-based enterprise voice AI platform. It helps businesses automate high-volume phone conversations using natural, multilingual AI voice agents. Companies use it for lead qualification, sales follow-ups, appointment booking, webinar reminders, collections, recruitment screening, and customer support.
Capabilities
DialNexa’s differentiation centers on cost per minute, reliability (demo call quality matching production quality), sub-1-second p80 latency, multilingual support, and speech-to-speech model support.
DialNexa supports Hindi, Tamil, Telugu, Kannada, Malayalam, Gujarati, and Marathi alongside English. Latency is sub-1-second at p80, and demo call quality matches production. The platform is developer-friendly too, with API access across dashboard functions for teams that want programmatic control.
Key Services
- Outbound voice AI platform(sales, collections, follow-ups)
- Inbound voice AI (support, enquiries)
- Multilingual and regional-language voice agents
- Workflow automation across CRM and WhatsApp with human handoff
Pricing: Starter rate around ₹5/minute, with tiered Growth and Enterprise plans and a structured 30-day pilot. Enterprise pricing drops to roughly ₹2.5/minute at committed volume.
Ideal For: Indian businesses running high-volume outbound or inbound calling operations that want a managed, multilingual platform without assembling their own STT/LLM/TTS stack. A minimum commitment of roughly ₹1 lakh a month applies.
2. Skit.ai
Skit.ai (formerly Vernacular.ai) is a voice AI company founded in Bengaluru in 2016 by Sourabh Gupta and Akshay Deshraj, now headquartered in New York with its engineering base still in Bangalore. It’s built specifically around debt collection and accounts receivable automation rather than general-purpose voice AI.
Capabilities
Skit.ai’s core product is a generative AI-powered Large Collection Model. It analyzes consumer demographics and debt details to predict collection propensity. The bot can switch languages mid-call in real time across 10+ regional Indian languages, with 160+ dialect variations trained in.
The company is SOC 2 Type II, HIPAA, PCI-DSS, and ISO 27001:2022 compliant. Its specialization is also its limit: it isn’t built for voice AI use cases outside collections, marketing, and servicing.
Key Services
- Voice, SMS, email, and chat automation for collections
- Generative AI-powered Large Collection Model for propensity scoring
- First- and third-party collections, early-out collections, creditor services
- Multi-language, region-aware customer engagement
Pricing: Not publicly itemized. The company has described performance-based pricing models for collections work, where it earns more as it collects, alongside standard enterprise licensing.
Ideal For: Banks, lenders, collection agencies, and BFSI teams that need a voice AI platform purpose-built for collections and accounts receivable, with compliance certifications already in place.
3. Uniphore
Uniphore was founded in 2008 by Umesh Sachdev and Ravi Saraogi, incubated at IIT Madras in Chennai. It’s now dual-headquartered in Palo Alto and Chennai, and has grown from a Chennai speech-recognition startup into a large-scale enterprise AI company.
Capabilities
Uniphore’s platform, called the Business AI Cloud, spans conversational AI, video AI, emotion AI, and a governance layer called U-Trust. It combines secure voice and media capture with self-service bots, agent-assist tools, and analytics inside one architecture.
That breadth means it’s a heavier platform to deploy than a single-purpose voice tool. It suits enterprises that already record, audit, and analyze conversations as part of existing operations, but it’s more platform than smaller teams typically need for a single voice AI use case.
Key Services
- Conversational AI and voice/video analytics
- Emotion AI and real-time sentiment detection
- Agent-assist tools for hybrid human-AI environments
- Governed data capture, security, and compliance layer (U-Trust)
Pricing: Not publicly disclosed. Uniphore is enterprise, sales-led, and typically requires custom contract negotiation.
Ideal For: Large enterprises with layered CX operations that need governed data capture, compliance, and agent-assist tools alongside voice automation, not just a standalone voicebot.
4. Yellow.ai
Yellow.ai was founded in 2016 by Raghu Ravinutala, Jaya Kishore Reddy Gollareddy, and Rashid Khan, with roots in Bangalore and headquarters now in San Mateo. It’s raised over $102 million in funding, and in late 2026 announced plans to go public via a $550 million merger.
Capabilities
Yellow.ai’s voice product is VoiceX (also appearing under the newer Nexus Vox branding). It’s built for autonomous, multi-turn phone conversations rather than rigid IVR menus, with claimed sub-400ms response times and support for 35+ channels including chat, WhatsApp, and email.
Voice sits inside a broader omnichannel platform rather than as a standalone product, and Gartner named Yellow.ai a Challenger in its 2025 Magic Quadrant for Conversational AI Platforms.
Key Services
- Omnichannel voice, chat, WhatsApp, and email automation
- VoiceX/Nexus Vox voice AI with low-latency, multi-turn conversation handling
- No-code AI builder for business teams
- Agent-assist and analytics dashboards
Pricing: A free plan exists but is capped at 2 human seats and 500 chat sessions a month, with voice features unlocked only on paid tiers. Enterprise pricing is quote-based; third-party listings put annual contracts anywhere from roughly $10,000 to $58,000+ depending on volume and channels.
Ideal For: Large enterprises that want voice inside a broader customer automation stack spanning chat and messaging, with the internal team and budget to manage a multi-channel implementation.
5. Jio Haptik
Haptik was founded in Mumbai in 2013 by Aakrit Vaish and Swapan Rajdev. Reliance Jio acquired an 87% stake in 2019 for roughly $100 million, and the company now operates as Jio Haptik within the wider Reliance ecosystem.
Capabilities
Jio Haptik’s platform spans voice, chat, and web, and the company offers six autonomous agent types: Voice, Support, Sales, Booking, Lead Qualification, and Insights. It claims support for 100+ languages and holds GDPR and ISO 27001 compliance, with disclosed 99.9% uptime.
The trade-off is procurement: implementation typically runs 6-16 weeks and is enterprise-only, and Reliance’s ownership structure is something some foreign enterprise buyers factor into data governance review.
Key Services
- Multi-channel voice, chat, and web automation
- Autonomous agents for support, sales, booking, and lead qualification
- Cross-channel context continuity
- Enterprise compliance (GDPR, ISO 27001)
Pricing: Enterprise-only, custom quote-based.
Ideal For: Large Indian and multinational enterprises whose customer journeys already span voice, chat, and web, and that want one platform maintaining context across all three.
6. Kore.ai
Kore.ai was founded in 2013 by Raj Koneru, headquartered in Orlando with strong Indian engineering roots. It’s raised roughly $234-300 million across multiple rounds, including a growth round led by AllianceBernstein Private Credit Investors in January 2026, and rebranded from “XO Platform” to “AI Agent Platform” as it shifted from conversational AI positioning to agentic AI.
Capabilities
Kore.ai integrates with Deepgram for speech intelligence and real-time transcription, supporting roughly 120 languages with language-specific models for 25+ of them. It’s built for large enterprises with dedicated IT and automation teams, offering deep integrations across CCaaS platforms and observability tooling.
The trade-off is deployment time: enterprise reviewers report complex rollouts taking six to eighteen months, and recent feedback flags that deployments can be slow to integrate with legacy telephony and backend systems.
Key Services
- No-code/low-code conversational and voice AI builder
- Multilingual voice AI with 120+ language support
- Agentic RAG for enterprise data access
- Pre-built solutions for contact centers, HR, and IT support
Pricing: Not publicly disclosed. Reported enterprise deal sizes start around $300,000 a year.
Ideal For: Large enterprises with mixed technology estates (multiple CCaaS, CRM, or telephony systems) and dedicated solution-engineering capacity to manage a longer, more complex rollout.
7. Mihup
Mihup was founded in Kolkata in 2016 by Tapan Barman, Sandipan Mandal, and Biplab Chakraborty. It’s raised roughly ₹100 crore (about $12 million) across multiple rounds, including a ₹50 crore round in October 2024 backed by Ashish Kacholia and Madhusudan Kela, valuing the company at around ₹1,000 crore.
Capabilities
Mihup builds its ASR, NLP, and TTS stack fully in-house rather than fine-tuning third-party foundation models, with proprietary noise suppression technology tuned for Indian accents and dialects.
Its public voice-bot detail is lighter than its analytics and ASR story, so buyers evaluating it for a general-purpose voicebot use case should push for a live workflow demo rather than relying on the speech-capability narrative alone.
Key Services
- Proprietary ASR, NLP, and TTS built in-house
- Automotive voice AI (AVA) for connected vehicles
- Interaction analytics, QA, and agent coaching for contact centers
- Real-time, noise-tuned speech recognition for BFSI
Pricing: Custom quote
Ideal For: Automotive and BFSI enterprises operating in noisy, accent-heavy call environments, where speech recognition accuracy under real conditions matters more than a polished conversational builder.
8. Rezo.ai
Rezo.ai was founded in Noida in 2017 by Dr. Rashi and Dr. Manish Gupta. It’s a bootstrapped-to-lightly-funded company by comparison to others on this list, having raised seed funding led by Modulor Capital, and reports $4 million in revenue with a 51-person team as of 2024. It’s since expanded operations to the UAE, Singapore, Malaysia, and Nepal.
Capabilities
Rezo.ai automates conversations across voice, email, WhatsApp, social media, and chat, positioning itself around agentic AI for customer experience rather than voice alone. It combines conversation automation with contact center analytics, sentiment and emotion detection, and QA in one stack.
The company has also built a dedicated collections product for NBFCs. Public technical detail on the platform remains lighter than its awards and traction claims, so a proof of concept before committing is advisable, as with several other companies on this list with limited independent benchmarking.
Key Services
- AI voice agents for inbound and outbound calls
- Sentiment and emotion analysis alongside QA
- Omnichannel automation (voice, email, WhatsApp, chat)
- Collections product built specifically for NBFCs
Pricing: Not publicly disclosed.
Ideal For: Enterprises that want voice AI bundled with sentiment analytics and QA in a single stack, particularly e-commerce, finance, and NBFC teams that also want operational visibility into conversations, not just automation.
9. Floatbot
Floatbot was founded in 2017 by Jimmy Padia, originally serving Indian BFSI clients before establishing operations in Milpitas, California. It’s grown from a chatbot provider into a broader no-code conversational AI platform.
Capabilities
Floatbot’s platform includes a no-code builder, generative AI-powered voicebots and chatbots, real-time AI agent-assist (copilot) tools, and its own ASR (Floatbot NEO) and voice biometrics (Floatbot ARMOR). It’s pre-integrated with contact center platforms including Genesys, NICE InContact, and Avaya, and is built around BFSI use cases like KYC, onboarding, and loan servicing.
The trade-off is that ease of starting shouldn’t be confused with enterprise readiness at scale; buyers should test multilingual accuracy, handoff logic, and compliance controls under real volumes before standardizing on it.
Key Services
- No-code voicebot and chatbot builder
- Real-time AI agent-assist (copilot) for contact centers
- Proprietary ASR and voice biometrics
- Pre-built BFSI workflows (KYC, onboarding, servicing)
Pricing: Lite at roughly $119/month (1 bot, 500 sessions), Essential at roughly $2,499/month (2 bots, 10K sessions), Growth at roughly $6,199/month (2 bots, 25K sessions), and custom Enterprise pricing above that.
Ideal For: SMBs and BFSI teams that want to test a contained first deployment, like KYC or onboarding, before committing to a larger rollout, with clear published pricing to model costs early.
10. Bolna
Bolna is a Bengaluru-based voice AI orchestration platform founded in 2024 by Maitreya Wagh and Prateek Sachan. It raised $6.3 million in a seed round led by General Catalyst in January 2026, with participation from Y Combinator’s Fall 2025 batch, Blume Ventures, and others.
Capabilities
Bolna is built specifically for India’s linguistic complexity, supporting 10+ Indian languages with strong Hinglish and accent handling. It uses a bring-your-own-key (BYOK) model, where businesses connect their own LLM, STT, and TTS provider accounts through Bolna’s orchestration layer.
The BYOK model means customers manage and pay for separate provider accounts on top of Bolna’s platform fee, adding overhead compared to fully-managed platforms. Bolna is also voice-only, with no native WhatsApp, SMS, or email orchestration.
Key Services
- Voice AI orchestration with BYOK flexibility
- 10+ Indian languages with Hinglish and Tanglish code-switching
- REST API for developer integration
- Smart routing across STT, LLM, and TTS providers for cost efficiency
Pricing: Usage-based, reported at roughly ₹3-7 per minute depending on call volume, per company statements to YourStory.
Ideal For: Technical teams that want India-specific language handling with more orchestration control than a fully managed platform, and are comfortable running a BYOK provider stack.
11. Ringg AI
Ringg AI is a Bengaluru-based voice AI company founded in October 2023 by Siddharth Shankar Tripathi (ex-Groww, Flipkart) and co-founders from Blinkit and Flipkart backgrounds.
Capabilities
Ringg AI is a no-code, multilingual voice orchestration platform supporting 18+ languages, including 10 Indian regional languages, used across customer support, sales, collections, logistics, lead qualification, appointment scheduling, and candidate screening.
Its no-code approach lowers the barrier for business teams, but its latency and cost-reduction figures are company-reported and worth validating on your own call conditions rather than taken as guaranteed production numbers.
Key Services
- No-code voice AI orchestration for inbound and outbound calls
- Multilingual support across 18+ languages
- Workflows for support, sales, collections, and recruitment screening
- Plans for an AI-native CRM and workflow marketplace
Pricing: Starts around $0.08/minute as an all-in flat rate, per the company’s own pricing page, rather than the modular per-component pricing used by developer-first platforms.
Ideal For: Business teams that want a no-code, fast-to-deploy voice AI platform across common workflows like support, collections, and lead qualification, without assembling a custom provider stack.
12. Gnani.ai
Gnani.ai was founded in 2016 by Ganesh Gopalan and Ananth Nagaraj, headquartered in Bengaluru. Unlike most companies on this list, it builds its own foundation models for speech recognition, synthesis, and speech-to-speech processing rather than orchestrating third-party ones.
Capabilities
Gnani reports processing over 30 million voice interactions daily across 12+ languages for more than 200 enterprise clients, including banks and insurers. Its stack includes voice biometrics for authentication, real-time agent assist, and on-premise and sovereign deployment options for regulated enterprises.
As a full-stack, own-model platform built for large regulated enterprises, it’s not positioned as a fast self-serve option for smaller businesses.
Key Services
- Proprietary STT, TTS, and speech-to-speech model stack
- Voice biometrics for authentication
- Real-time agent-assist and post-call analytics
- On-premise and sovereign deployment options
Pricing: Not publicly disclosed; enterprise, quote-based.
Ideal For: Banks, insurers, and government bodies that need on-premise or sovereign deployment, voice biometrics, and a proprietary (not third-party-orchestrated) speech stack at large scale.
Voice AI Companies in India: Side-by-Side Comparison
| Company | Best For | Standout | Pricing |
| DialNexa | High-volume outbound and inbound calling | Multilingual support, sub-1-second p80 latency, developer API access | From ₹5/min, ₹2.5/min at volume |
| Skit.ai | Debt collection and accounts receivable | Generative AI collection model, 10+ languages with mid-call switching | Not disclosed; performance-based options |
| Uniphore | Governance-heavy enterprise CX | Governed capture + agent-assist inside one architecture | Enterprise, quote-based |
| Yellow.ai | Omnichannel enterprise CX | VoiceX low-latency voice AI across 35+ channels | Free tier; enterprise quote-based |
| Jio Haptik | Cross-channel continuity at scale | 500+ enterprise clients, 100+ languages, Reliance-backed reach | Enterprise, quote-based |
| Kore.ai | Complex, multi-system CX | Deep CCaaS integrations, 120+ language support | Not disclosed; deals reported from ~$300K/year |
| Mihup | Noisy, accent-heavy environments | Proprietary in-house ASR/TTS stack, live in 1M+ vehicles | Not disclosed |
| Rezo.ai | Voice AI plus sentiment/QA analytics | Omnichannel automation with built-in CX analytics | Not disclosed |
| Floatbot | SMB and BFSI prototyping | Published tiered pricing, proprietary ASR and voice biometrics | Lite $119/mo to Enterprise custom |
| Bolna | India-native developer teams | BYOK orchestration, 200K+ calls/day reported | ~₹3-7/min (volume-based) |
| Ringg AI | No-code fast deployment | 18+ languages, ~1.5M conversations/month reported | ~$0.08/min flat |
| Gnani.ai | Regulated enterprise at scale | Proprietary speech-to-speech stack, voice biometrics | Enterprise, quote-based |
How to Choose the Right Voice AI Company in India
Start with purchase intent. Narrow, measurable outcomes like lead qualification or collections follow-up usually favor a specialist company. Mandates spanning multiple business units and channels usually fit a broader CX suite better, since these are different procurement motions with different sponsors and success criteria.
Assess delivery risk before feature breadth. Telephony setup, CRM data quality, escalation logic, and agent handoff design are often what determines ROI, not the size of the product surface.
- Revenue teams should test launch speed and conversion economics
- Operations leaders should check uptime, reporting quality, and integration stability
- Compliance and risk teams should examine consent capture, auditability, and role-based access
- Language claims should be tested live on code-switching, accents, and noisy calls, not taken from a coverage list
Run the same workflow, integration conditions, and success thresholds across two or three shortlisted companies, then compare commercial impact, deployment effort, and compliance fit together.
Conclusion
The best voice AI company in India isn’t a single winner, it’s a fit exercise between business objective, control requirements, and internal execution capacity. Companies built for a single workflow, like DialNexa for outbound calling or Skit.ai for collections, typically deliver faster time to value for narrow mandates.
Broader CX suites like Uniphore, Yellow.ai, Jio Haptik, and Kore.ai fit organizations that need voice standardized alongside chat and other channels across multiple teams.
Companies building their own speech infrastructure, like Gnani.ai and Mihup, matter most where speech accuracy under real conditions, not conversation design, is the harder problem.
FAQs
What are the top voice AI companies in India?
DialNexa, Skit.ai, Uniphore, Yellow.ai, Jio Haptik, Kore.ai, Mihup, Rezo.ai, Floatbot, Bolna, Ringg AI, and Gnani.ai lead the market, each suited to different needs across specialist workflows, enterprise CX, and speech infrastructure.
What is the best AI voice agent for outbound sales in India?
DialNexa is built around revenue-linked outbound workflows like lead qualification and sales follow-ups, with ready-made call flows and CRM integration that shorten deployment time for high-volume calling operations.
Which voice AI company is best for Indian languages?
Gnani.ai, Mihup, Skit.ai, and DialNexa all handle multilingual and code-switched calls. DialNexa currently prioritizes English and Hindi, with strong support for Tamil, Telugu, Kannada, Malayalam, Gujarati, and Marathi.
What is the best voice AI company for collections in India?
Skit.ai is voice-first and built specifically for debt collection and accounts receivable, with SOC 2, HIPAA, and PCI-DSS compliance. DialNexa and Ringg AI also support collections as part of broader outbound automation.
Which AI voice agent can qualify leads and book appointments?
DialNexa is built specifically for this workflow, with pre-built agents for lead qualification, appointment booking, and site-visit scheduling across real estate, EdTech, and SaaS businesses.
What is the best voice AI API for developers in India?
DialNexa offers API access across dashboard functions for programmatic control. Bolna offers a REST API with a bring-your-own-key model for teams that want to assemble their own provider stack.
Which voice AI company is best for regulated BFSI deployment?
Gnani.ai and Uniphore are both built for regulated, governance-heavy enterprise deployment, with on-premise and sovereign options. Floatbot also has a strong BFSI track record for KYC and onboarding workflows specifically.
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