Hindi Voice AI: 22 Indian Languages at ₹2/min

Language counts are the number this category competes on, and almost nobody publishes them next to what the entry tier actually unlocks. Every competitor cell below was read on that vendor's own page on 21 Jul 2026.

Every competitor figure in that table was read on the vendor's own page on 21 Jul 2026 and is stored with the sentence it came from. Rates and counts move quickly in this category — several moved within weeks of each other — so re-check before you buy; the rate side is maintained separately at the India AI voice agent pricing index.

Three things this table is not. It is not a ranking — a bigger count says nothing about whether the agent survives one Hinglish sentence. It is not audited — every count here, ours included, is the vendor describing itself. And it is not a claim that we are cheapest: Agni advertises from ₹2/min and Scalify advertises ₹0.40/min, and both are real published numbers with the conditions shown above attached. Our defensible claim is about terms rather than the number — ₹2/min from the very first minute, in every one of the 22 languages, with no subscription, no minimum volume and no lock-in.

No public benchmark ranks Indian voice AI agent vendors on Hindi quality. What exists is a benchmark of the underlying speech-recognition (ASR) models, and it is worth reading. What does not exist is an independent scoreboard of end products — the thing you are actually buying. Treat any vendor-published Hindi accuracy figure with no linked methodology as marketing copy.

So the practical decision procedure is:

1. Ignore claimed language counts. "50+ languages" and "10+ Indian languages" are unaudited self-descriptions. They tell you nothing about whether the agent survives a Hinglish sentence.
2. Test the demo line yourself, ten times, on a scorecard. The section The 10-call self-test below gives you the exact script. If a vendor will not let you call an unattended demo before a sales conversation, that refusal is your answer.
3. Price the all-in rupee cost, not the headline per-minute rate. Platform fees, minimum commitments and per-language surcharges are where the headline rate stops being true. One vendor admits in its own copy that a ₹3/min quote typically bills at ₹6–₹9/min in production.
4. Check whether regional languages cost extra. In this category they very often do.

Where Dvaarik sits, plainly: we are a build studio, not a model house and not self-serve software. Voice is ₹2/min on simple whole-minute billing as the permanent base rate — not a founding discount — across all 22 languages in the Eighth Schedule of the Indian Constitution, with no per-language surcharge across Indian languages. There is no per-minute platform fee and no usage minimum — the only recurring commitments are the Care Plan for the first three months and the ₹2,000/30-day number recharge, both itemised below. We did not build the Indic speech models and we do not claim to. Our live demo is callable right now, with no sales call, at app.dvaarik.com/dvaarik-ai.

Almost every vendor page collapses a four-layer stack into one checkbox. When a Hindi call goes wrong, it goes wrong in one specific layer, and knowing which one saves you weeks.

The benchmark in the next section measures only the first layer. That is a genuine limitation and I want it stated before I show you the numbers, because the temptation across this SERP is to quote an ASR figure as if it graded the whole product.

The specific Indian hard cases

• Code-mixing mid-sentence. "Sir mera appointment reschedule karna tha, Thursday evening slot available hai kya" is not Hindi and not English. It is how urban India actually books things.
• Regional accent, not broadcast accent. A Purvanchal, Marwari or Deccan-Hindi speaker sounds nothing like a news anchor, and a lot of training audio is closer to the anchor.
• Numbers, dates and money. "Saade teen baje", "pandrah tareekh", "do hazaar paanch sau" — these break systems that handle ordinary sentences fine.
• Proper nouns. Indian names and locality names spelled out over a noisy line.
• Two languages in one household. The caller opens in Telugu, then the family member who takes the phone speaks Hindi.

There is a genuine, named, third-party Indian speech benchmark, and almost nobody selling voice AI in India cites it. It is Voice of India: A Large-Scale Benchmark for Real-World Speech Recognition in India, arXiv:2604.19151v1, dated 21 Apr 2026, built by AI4Bharat at IIT Madras with Josh Talks (verified on arxiv.org, checked 20 Jul 2026).

Why it matters more than lab benchmarks: it is built from unscripted telephonic conversations, and the paper explicitly says it includes code-switched speech (Hindi-English, Tamil-English, Urdu-Hindi), background noise and informal speaking styles (arXiv 2604.19151v1, checked 20 Jul 2026). That is your customer, on your phone line, not a studio reading.

All figures from arXiv 2604.19151v1, checked 20 Jul 2026.

The 14 systems evaluated are a mix of proprietary and open-source speech-recognition models from Indian and global labs. We deliberately do not reproduce the model-by-model table here: we do not publish which models Dvaarik runs on, and printing a vendor leaderboard on our own site invites exactly the inference we avoid. The leaderboard is public if you want the rows — go read it at the source rather than through us.

The useful finding is not who came first. It is the spread.

Across the 14 systems evaluated, published Hindi word error rate on the standard set runs from roughly 6% at the best to about 34% at the worst (voice-of-india.ai.joshtalks.com, checked 20 Jul 2026). That is a more than five-fold difference in how often the system mis-hears a word, between models that are all marketed as production-ready.

Two things follow from that spread, and they matter more than any ranking:

• A vendor saying "we support Hindi" tells you almost nothing. Supporting Hindi and transcribing Hindi accurately on a noisy phone line are different claims, and the gap between the best and worst system is large enough to decide whether your agent works.
• You cannot infer product quality from model quality. The benchmark grades transcription engines, not finished agents. A vendor using a strong engine can still ship a bad agent, and a well-built agent on a middling engine can outperform it.

Four caveats that matter more than the ranking

• This grades transcription, not agents. None of these rows is a voice AI vendor's product. A vendor using a strong ASR model can still build a bad agent, and the reverse is rarer but possible.
• The evaluation sets are not fully open. The benchmark site states a "restricted, private access model", with only a public sample set for each of the 15 languages; the full benchmark is kept closed to protect data integrity and speaker privacy (voice-of-india.ai.joshtalks.com, checked 20 Jul 2026). You cannot independently re-run it, and neither can we.
• WER is a blunt instrument for Hinglish specifically. The paper itself notes that strict single-reference WER penalises natural spelling variation in Indian languages, including non-standardised spellings of code-mixed English-origin words (arXiv 2604.19151v1, checked 20 Jul 2026). A system can be marked wrong for spelling "appointment" the way a human transcriber did not.
• We are borrowing AI4Bharat's credibility here, not our own. Dvaarik ran none of these tests. I am citing other people's work because it is the only real work on the table.

One more thing worth saying out loud: at least one competitor page publishes Hindi WER ranges for "global models" versus "India-tuned models" with no source and no methodology anywhere on the page. I read it and I am not repeating the numbers, because an uncited accuracy claim is not evidence — it is a sentence.

Since no benchmark grades the product you are buying, grade it yourself. This takes under an hour, with nothing but a phone. Run the identical ten calls against every shortlisted vendor's demo line and score each pass/fail. Do not accept a scheduled, sales-supervised demo as a substitute — a supervised demo is a performance.

How to score it

• Mark each call pass / partial / fail. Partial counts as fail — customers do not grade on a curve.
• Run the whole set again for each language you actually need, not just Hindi. A vendor can be strong in Hindi and weak in Telugu or Marathi, and one language's score tells you nothing about another's.
• Record the calls if you are allowed to, and listen back for latency and tone, not just correctness. A technically correct answer delivered three seconds late still loses the caller.
• Ask the vendor, before you pay: *what happens on call 8 in production?* An agent that invents an answer to a pricing question costs more than one that says it will check.

If a vendor cannot give you an unattended number to run this on, that is a real finding. Dvaarik's demo is at app.dvaarik.com/dvaarik-ai and you can point all ten calls at it today without talking to me first — and you should point the same ten at everyone else too.

"Hindi support" is only half of the Indian problem. A Hyderabad clinic gets Telugu, Hindi and English on the same day. A Coimbatore showroom gets Tamil and English. A Pune office gets Marathi.

The Eighth Schedule of the Indian Constitution contains exactly 22 languages: Assamese, Bengali, Bodo, Dogri, Gujarati, Hindi, Kannada, Kashmiri, Konkani, Malayalam, Manipuri, Marathi, Maithili, Nepali, Oriya, Punjabi, Sanskrit, Santhali, Sindhi, Tamil, Telugu, Urdu (Department of Official Language, Ministry of Home Affairs, rajbhasha.gov.in, checked 20 Jul 2026). That is the principled line Dvaarik draws — all 22 Eighth Schedule languages plus code-mixed Hinglish, Tenglish and Tanglish at the same ₹2/min, with no per-language surcharge across Indian languages. Most world languages are supported and priced separately — ask for the rate.

I will be straight about the marketing weakness in that: 22 is not the biggest number on this search results page. At least one competitor advertises "50+" languages. A larger count is easy to print and hard to verify, and my count is deliberately bounded by a constitutional list rather than by ambition. Judge it with the 10-call test, not the number.

What is actually being built underneath

The Indic speech data situation has improved genuinely, and it is worth knowing who did that work. AI4Bharat's IndicVoices-R is described on its own repository as "the largest multilingual Indian TTS dataset derived from an ASR dataset, with 1,704 hours of high-quality speech from 10,496 speakers across 22 Indian languages" (AI4Bharat IndicVoices-R GitHub README, checked 20 Jul 2026). AI4Bharat also states its ASR models IndicWav2Vec and IndicWhisper are trained on the Kathbath, Shrutilipi and IndicVoices datasets — though notably, no WER figures or leaderboard are published on the AI4Bharat ASR page itself (ai4bharat.iitm.ac.in, checked 20 Jul 2026). If you want a research-grade Indic speech vendor rather than an agent builder, that is the direction to look, and I say more about this in the "pick someone else" section.

A practical multilingual checklist

• Does the agent detect language automatically, or does the caller have to press 1 for Hindi — which is just an IVR wearing a new hat? See AI voice agent vs IVR.
• Can it switch mid-call when the phone changes hands?
• Are regional languages priced the same as English? Often they are not — next section.
• Does the written follow-up (WhatsApp confirmation, booking SMS) come in the same language the call happened in?

This is where most buyers get hurt, and unusually, the clearest evidence comes from a competitor's own page.

Caller Digital's voice AI pricing page publishes a headline Indian range of ₹2–₹12 per minute, says ₹3–₹6 is the most common mid-market range, and then states that effective cost is ₹6–₹25/min once you include platform fees, and that "a ₹3/min quote typically costs ₹6–₹9/min in production" — describing this as 2–4x the headline once platform and SaaS fees are added (caller.digital/voice-ai-pricing-india, checked 20 Jul 2026). That is a vendor admitting in writing that category headline rates are not what you pay.

The same page itemises the additions:

All rows: caller.digital/voice-ai-pricing-india, checked 20 Jul 2026.

Note the third row specifically. The same page states non-English languages "can increase your blended rate by 30–50%" (caller.digital, checked 20 Jul 2026). That is a vendor assertion with no cited source, and I am reporting it as an assertion — but it tells you the surcharge question is live in this category, not paranoid. Ask every vendor in writing: is Hindi billed at the same rate as English, and is Telugu billed at the same rate as Hindi.

One more finding worth having: Caller Digital does not publish its own per-minute rate on that pricing page. It asserts outcome-based pricing that "no other Indian voice AI vendor does at this scale" (caller.digital, checked 20 Jul 2026). A page that itemises everyone's hidden costs while omitting its own number is a pattern you should notice.

Published rates I could actually verify

Bolna row: bolna.ai/pricing, checked 20 Jul 2026. Trikon row: trikon.tech/voice-pricing-comparison, checked 20 Jul 2026 — note that page carries no published date. See also AI calling agent price in India 2026.

Why I will not show you a ten-vendor comparison table

Because the ones on this SERP are demonstrably unreliable. Trikon's comparison page lists Bolna AI at ₹8–₹11/min — while Bolna's own pricing page states ₹5.52/min (trikon.tech and bolna.ai, both checked 20 Jul 2026). That is a competitor's price overstated by roughly double on a page whose entire purpose is comparison. Once you catch one row like that, the whole table is unusable, including the rows you cannot check.

MyOperator's ranking page, updated 17 Jul 2026, lists a spread of rupee figures across the category including ₹2/min for self-serve tools, Bolti at ₹6/min, HuskyVoice AI at ₹1,999/month base, Tabbly.io from ₹3.9/min falling to ₹2.7/min at higher usage, Caller Digital at ₹5 per connected minute platform fee plus ₹5–25 per connected call, MyOperator's own at ₹10,000/mo plus ₹20,000 onboarding, and Vyora AI from ₹799/month (myoperator.com, checked 20 Jul 2026). Those are figures published on MyOperator's page, not verified on each vendor's own site — useful as a map of how differently the category prices itself (per minute, per month, per outcome), not as verified rates. Check each vendor's own page. See also Dvaarik vs Bolna AI and Dvaarik vs HuskyVoice.

Three claims circulate constantly on Indian voice AI pages: that AI calls must use the 140/160 number series, that they must announce upfront that they are automated, and that they may only run 10 AM to 7 PM. I went to check them and I am not going to repeat them, because I could not verify them as legal requirements.

Here is what I could confirm:

• TRAI's own official TCCCPR page names only the Telecom Commercial Communication Customer Preference Regulation (TCCCPR), 2018, and contains no mention whatsoever of AI, automated voice calls, or AI-specific calling rules (trai.gov.in/tcccpr, checked 20 Jul 2026).
• Law firm S.S. Rana & Co., in an article dated 9 Mar 2026, states that the Feb 2025 TCCCPR amendment changed the complaint threshold from 10 complaints in 7 days to 5 complaints in 10 days, cut service provider fast-track action time from 30 days to 5 days, extended the complaint window to 7 days, and limits inferred consent to "the duration of the contractual relationship" (ssrana.in, checked 20 Jul 2026).
• The same firm states TRAI's Feb 2025 amendments do not explicitly regulate AI systems, and that TRAI is "further considering to amend" regulations to account for AI-based telemarketing. It cites the 140 series for telemarketing and a separate DoT 160 series for service and transactional calls, and describes penalties as disconnection of telecom resources and blacklisting for up to two years — with no rupee penalty amounts stated (ssrana.in, checked 20 Jul 2026).

So the vendor blogs quoting you a precise rupee fine per violation for AI calling are quoting something I could not find in either source. Being right about this where much of the category is wrong is, frankly, part of why I wrote this page.

What to actually do, regardless of the fine print

The regulation is clearly heading toward tighter consent and faster enforcement, so the safe operating posture is the one that would survive any of the proposed rules:

1. Call your own leads only. People who enquired with you, filled your form, clicked your ad, or are existing customers. Never a purchased list. Dvaarik will not build outbound on bought data.
2. Respect calling hours and stop when someone asks you to stop.
3. Have the agent identify the business at the start of the call. Whether or not a rule requires it today, a caller who feels deceived complains — and the complaint threshold is now five in ten days.
4. Keep the escalation path real. "Talk to a human" must actually reach a human or a same-day callback.
5. WhatsApp is a separate regime with its own template rules — see WhatsApp Business API cost in India.

Same scrutiny, applied inward. Dvaarik is a build studio: I design and build a custom agent for your business. There is no self-serve signup, no plans, no tiers, no per-seat fee, no trial funnel.

The founding-client trade, stated plainly rather than dressed up: the ₹40,000 build is free in return for (a) the Care Plan for the first three months at the founding rate and (b) an honest testimonial and short case study after go-live. If the agent does not work well enough for you to say something honest about it, I have not earned the trade.

The arithmetic where we are a bad deal

A ₹2/min headline is meaningless if your fixed costs dominate. In month 1 for a founding client, fixed costs are ₹5,000 Care Plan plus ₹2,000 number recharge = ₹7,000 before a single minute. Here is the honest effective rate:

From month 4, if you drop the Care Plan, fixed cost falls to the ₹2,000 number recharge — 1,000 minutes then lands at ₹4.00/min effective and 3,000 minutes at ₹2.67/min.

Read that top row honestly. If you take a hundred voice minutes a month, our model costs you ₹72 a minute and you should not buy it. Below roughly 1,000 minutes a month the fixed component dominates and a cheap self-serve tool, or a part-time human, is the better answer. Our model earns its keep when you have real call volume, need genuine multilingual coverage, and want something built around your actual booking and follow-up process rather than configured in a dashboard. Run your own volume through the missed call calculator before you talk to me.

Six situations where Dvaarik is the wrong choice. I would rather lose the enquiry than the argument later.

1. You are optimising for the lowest sticker price. Tabbly.io lists itself at ₹2/min on its own comparison page (tabbly.io, checked 20 Jul 2026), and Trikon's ₹5/min is explicitly inclusive of LLM, STT and TTS (though not telephony). I cannot claim to be cheapest and I am not going to. My claim is transparent all-in pricing with no per-language surcharge across Indian languages and no per-minute platform fee — a different claim.
2. You want a research-grade Indic speech vendor. Sarvam AI and AI4Bharat build actual Indic speech models; a Sarvam system appears in the Voice of India evaluation set. Dvaarik integrates on top of that generation of technology — we are not a model house, and if your requirement is model-level control or custom acoustic training, go to the people who build the models.
3. You need the largest possible language count on paper. We commit to the 22 Eighth Schedule languages plus code-mixed Indian speech; most world languages are supported and priced separately. If your procurement checklist genuinely requires a "50+" line item, someone else prints that number.
4. You are an enterprise buying on scale and formal compliance process. Gnani.ai, SquadStack and Haptik sell into the enterprise segment on custom or outcome-based quotes (as listed on tabbly.io, checked 20 Jul 2026). If you need a vendor security questionnaire answered by a compliance team, that is not me — a home-based studio in Telangana. See enterprise for what I can and cannot do at that end.
5. You want an established telephony brand behind it. MyOperator is an established telephony brand with a long-running product and a large content and support footprint. If buying from an incumbent matters to you, that is a real thing to buy.
6. You want proof from a long client list. We are pre-revenue with founding client slots open. There are no case studies on this site because there are none to show yet. The only proof I can offer is the live demo you can call yourself — which is exactly why The 10-call self-test section exists.

And the honest limit on this whole page: I did not run the Voice of India benchmark. AI4Bharat and Josh Talks did. I am borrowing their credibility because it is the only credible thing available, and I would rather say so than let you assume otherwise.

The build sequence

1. Tell me the problem, not the feature list — which calls are being missed, in which languages, at which hours.
2. I build the agent personally. Seven agent types are available: Receptionist, Leads with speed-to-lead around 60 seconds, Sales, WhatsApp, Instagram, Booking and Payments.
3. You run the 10-call test on your own agent before it goes anywhere near a customer, in every language you need. See how it works.
4. Go live, watch the transcripts for the first week, and tune.

The questions to put to every vendor in writing

• Is Hindi billed at the same per-minute rate as English? Is Telugu billed at the same rate as Hindi?
• Is there a monthly platform fee, a minimum commitment, or an onboarding charge? What is the total first-month rupee outlay?
• Is billing per second or per whole minute? (Ours is whole-minute. Say so plainly and compare like for like.)
• Can I call an unattended demo line today, without a sales call?
• Who owns the phone number and the call recordings?
• What exactly happens when the agent cannot answer?
• Is telephony included in the quoted rate or billed separately?
• Are WhatsApp message charges marked up, or billed by Meta to my own account?

An invented illustration, labelled as invented

*Sunrise Dental, Warangal — a made-up practice, not a client.* Front desk fields Telugu and Hindi enquiries, misses calls during procedures, and loses evening enquiries entirely. Say 1,200 voice minutes a month. At ₹2/min that is ₹2,400 usage; with the founding Care Plan and number recharge, roughly ₹9,400 in month 1, falling to about ₹4,400/month from month 4 if the Care Plan is dropped. Whether that beats a second receptionist is arithmetic you can do in ten minutes — and I would rather you did it before we speak than after. Related reading: AI receptionist for clinics in India and for clinics.