Agni vs Sarvam vs Smallest.ai — three Indian voice AI companies, three different jobs
All three are real, well-funded, and building their own models in India. They are not the same shape of product, which is why “which is best” is the wrong question. Here is what each layer of the stack actually does, what it costs, where Agni wins — and the four rows where it does not.
What each one is actually for
Read these three cards and you have most of the decision. Everything below is the evidence.
Agni by Ravan.ai
New Delhi · India-firstA calling-operations platform for India.
Agents, Indian telephony, campaigns, DND/DLT compliance workflows, transcripts and analytics — in one console a business team runs without engineering. Priced all-in, in rupees, per minute.
Pick it when
Indian-language phone campaigns have to be live this month, compliant, and modelled in INR.
Sarvam AI
Bengaluru · founded 2023India’s sovereign model layer — plus a young agent layer on top.
A 105B Indic chat model, speech-to-text, text-to-speech, translation and document intelligence across 22 Indian languages, built under the IndiaAI Mission mandate. A self-serve Voice Agents builder opened in August 2026.
Pick it when
Sovereign Indian models, model-layer data residency, or Indic APIs across many surfaces are the requirement.
Smallest.ai
Bengaluru · founded 2023Fast, self-owned speech models — plus the Atoms agent platform.
Lightning TTS at a claimed ~100 ms, Pulse STT across 38 languages, and Atoms for inbound, outbound campaigns, phone numbers, knowledge and concurrency control. On-premise deployment is a first-class option.
Pick it when
Raw latency, on-premise deployment, or a global rather than India-first footprint decides it.
Three layers, not three competitors
A voice AI decision has three layers stacked on top of each other. Most buyers compare the middle one, sign, and then discover that the top one is where the work actually was.
The operations layer
Everything between a working agent and a business outcome: campaign lists, calling windows, retries, DND/NCPR scrubbing, DLT templates, consent logs, dispositions, cost per completed call, CRM sync, human handoff.
What Agni is built around, with India’s telecom rules in the product itself.
Batch outbound, call logs, analytics and dashboards are published; TRAI campaign workflows are not documented as product features.
Outbound campaigns, concurrency limits, version history and rollback are published; India-specific compliance is not.
The platform layer
A console to build an agent, attach knowledge, give it tools and put it on a phone number. Where most buyers think the whole decision lives.
No-code agent builder, knowledge bases, tools, REST APIs and webhooks — the original product.
Design, test, telephony, batch outbound and analytics in one workspace. Real, and the newest of the three.
Atoms: agents from scratch or templates, knowledge upload, numbers, integrations, analytics.
The model layer
The speech and language models themselves — and whether you can license, self-host or fine-tune them.
Agni runs its own managed voice stack end to end, but does not license or sell foundation models. If you want the models, this is the wrong vendor.
Sarvam-105B, Saaras v3 STT, Bulbul v3 TTS, Mayura translation, Sarvam Vision OCR. India’s sovereign LLM mandate.
Lightning, Pulse, Electron and Hydra — all their own, tuned for latency and edge deployment.
Read the diagram top to bottom and the decision resolves itself. If you are buying the model layer, Agni is the wrong vendor and we will tell you so on the call. If you are buying the platform layer, all three can do it and you should judge on your ears and your language. If you are buying the operations layer — because your problem is 40,000 DND-scrubbed dials a month inside TRAI calling windows with a compliance officer reading the audit trail — that is the layer Agni was built for, and it is the one that usually turns out to be the real project.
The full comparison
Four of these rows are not wins for Agni. They are in the table anyway, because a comparison nobody loses is a comparison nobody believes.
| Capability | Agni | Sarvam | Smallest.ai |
|---|---|---|---|
| What the company primarily sells | Operations platformA complete Indian calling operation: agents, telephony, campaigns, compliance workflows, analytics — bought, not assembled. | Models + APIsSovereign Indic foundation models and the APIs around them, with a Voice Agents builder layered on top since August 2026. | Models + platformIts own speech and language models, plus the Atoms agent platform built on them. |
| Self-serve agent builder | YesNo-code console for business teams — persona, knowledge, tools, guardrails — alongside REST APIs for engineering. | Since Aug 2026Design agents, test before going live, control prompt, voice, tools and flow — in one workspace, per their own launch note. | YesAtoms: build from scratch or from templates, with full version history and rollback on every agent. |
| Outbound campaigns at scale | YesContact lists, calling windows, retries, caller IDs, concurrency and dispositions as first-class objects — not something you build. | Batch calling“Kick off batch outbound calling at scale”, with call logs and dashboards, per their launch note. Window, retry and disposition controls are not detailed publicly. | Yes“Run outbound campaigns at scale — your agent handles every call, you track the results”, with concurrency limits, per their product page. |
| India compliance workflows — DND/NCPR, DLT, calling windows, consent | In the productDND/NCPR scrubbing before a campaign dials, DLT template workflows (140/160 series), calling-window enforcement, consent logging and audit trails. | Not publishedIndia data residency and a fully self-hosted model stack are published; TRAI campaign workflows such as DND and DLT are not documented as product features. | Not publishedISO 27001, SOC 2 Type 2, GDPR and HIPAA are listed, and press cites GDPR/TCPA; no India-specific DND or DLT workflow is published. |
| Indian languages on live calls | Yes30+ Indian languages and 100+ accents and dialects, tuned for regional familiarity on a phone call — covering 800M+ people. | 10 + EnglishVoice Agents run across Hindi, Tamil, Telugu, Bengali, Marathi, Gujarati, Kannada, Malayalam, Punjabi and Odia, plus English. The model layer covers 22 Indian languages. | 7 Indian on TTSLightning’s current version lists 15 languages, of which Hindi, Tamil, Kannada, Telugu, Malayalam, Marathi and Gujarati are Indian; Pulse STT covers 38 languages. |
| Hinglish and mid-sentence code-switching | YesHinglish-native: real code-switching mid-sentence, with interruption handling, the way Indian customers actually speak on the phone. | YesCode-mixed and regional speech is explicitly part of what Saaras v3 is built to transcribe, per their docs. | YesAutomatic language detection and mid-sentence language switching are published Lightning features. |
| Owns and licenses its foundation models | Not soldAgni runs its own managed voice stack end to end — which is how latency and language behaviour stay consistent — but it does not license or sell models. If you want the models themselves, look elsewhere. | SovereignSelected under the IndiaAI Mission from 67 applicants to build India’s first sovereign LLM; the whole Voice Agents stack is self-hosted by Sarvam. | YesLightning, Pulse, Electron and Hydra are all their own models, built on a “many small specialised models” thesis. |
| On-premise / edge deployment | Not publishedAgni is delivered as a managed cloud platform. If a customer-premises deployment is mandatory, this is not the right fit — say so early in your evaluation. | Sarvam-hostedModels are self-hosted by Sarvam with India data residency including PII, per their docs — that is Sarvam’s infrastructure, not necessarily yours. | YesOn-premise deployment is published as an option on the Enterprise plan, and follows directly from the small-model thesis. |
| Document OCR, translation, dubbing | Not the productAgni is a phone-calling platform. It does not do document intelligence, and does not pretend to. | YesSarvam Vision for OCR across 23 languages, Mayura for translation across 11, and a dubbing service in beta. | Not the productFocused on speech: TTS, STT, speech-to-speech and voice agents. |
| How you are billed | All-in, INROne per-minute rupee rate covering voice, language model, emotion engine and telephony, on top of a monthly plan. No separate STT, TTS, token or hosting line. Excludes 18% GST. | Per API unitPublished in INR per unit: ₹30/hour STT, ₹15–30 per 10K characters TTS, ₹20 per 10K characters translation, ₹29.28/₹73.20 per million tokens in/out. No per-minute Voice Agents price is published. | Per component, USD$0.09–$0.21/min pay-as-you-go depending on models chosen, from $0.05/min at Enterprise, with hosting ($0.01/min), STT (~$0.009/min), TTS (~$0.09/min), numbers ($10/month) and knowledge base ($3/GB) itemised. |
| Telephony | YesTwilio, Airtel India, Telnyx and any SIP provider, with Indian PSTN routing and DLT-compliant outbound. | YesBring your own provider or rent a number from Sarvam; docs cite Twilio, Exotel and LiveKit. | Yes“Pick a number from our inventory or connect the one you already own”, per their product page. |
| Business-system integrations | YesGoHighLevel, Cal.com, Salesforce, HubSpot, Zoho CRM, LeadSquared, Freshdesk, Razorpay and WhatsApp Business are live; anything else through REST APIs and webhooks. | Tools + Work AgentsAgents carry tools, and their Work Agents integrate Gmail, Slack and Notion. A named CRM catalogue for calling is not published. | Yes“Production grade integration tools built to help you scale”; press cites Salesforce, HubSpot and Zoho. |
| Call record and analytics | YesPer-call transcripts, recordings, summaries, sentiment, dispositions and per-minute INR cost, in an operations dashboard and over webhooks. | Yes“Call logs, analytics, and custom dashboards over every conversation”, per their launch note. | YesAnalytics plus full agent version history and rollback, per their product page. |
| Published security posture | Ready, not certifiedSOC 2 ready, GDPR ready and HIPAA ready, with encryption in transit and at rest, RBAC and audit trails. “Ready” is deliberate — we do not claim certificates we do not hold. | India residencyEvery model in the Voice Agents stack is self-hosted rather than called out to a third party, with data residency in India for all data including PII, per their docs. | Certificates listedISO 27001, SOC 2 Type 2, GDPR and HIPAA are listed on their voice-agent product page. |
| Support model | YesGuided onboarding from first agent to first live campaign, with phone, WhatsApp and email support — not documentation alone. | YesDeveloper documentation plus enterprise engagement for larger deployments. | TieredEmail and community support on pay-as-you-go; priority and prompt-engineering support on Enterprise, per their pricing page. |
Sarvam and Smallest.ai details are summarised from each company's own website, product pages, documentation and published pricing, read in August 2026, plus mainstream press for company facts. Both ship quickly — verify current details with each vendor before you decide. All trademarks belong to their respective owners. Spot an inaccuracy? Email info@ravan.ai and we will correct it.
Why the prices look incomparable — and how to compare them
The three vendors bill on three different units. Until you convert them to one number on your own volume, you are not comparing anything.
Agni
Per minute, all-in, in INR- Starter
- ₹2,999/mo · 300 min · ₹8/min after
- Growth
- ₹5,999/mo · 1,000 min · ₹6/min after
- Scale
- ₹12,999/mo · 2,500 min · ₹4/min after
- Enterprise
- Quoted — from ₹2/min at volume
Voice, language model, emotion engine and telephony are inside the rate. Excludes 18% GST.
Sarvam
Per API unit, in INR- Speech-to-text
- ₹30/hour · ₹45/hour with diarisation
- Text-to-speech
- ₹15 per 10K chars (v2) · ₹30 (v3 beta)
- Translation
- ₹20 per 10K characters
- Chat, Sarvam 105B
- ₹29.28 in / ₹73.20 out per 1M tokens
No per-minute price for the Voice Agents product is published on their pricing page as of August 2026 — ask them for one.
Smallest.ai
Per minute + components, in USD- Pay as you go
- $0.09–$0.21/min · 20 concurrent calls
- Enterprise
- From $0.05/min · dedicated infra
- Hosting / STT / TTS
- $0.01 / ~$0.009 / ~$0.09 per min
- Numbers · knowledge
- $10 per number/mo · $3 per GB
$10 in free credits to start. Rates vary with which models you select, so your effective per-minute cost depends on the mix.
On Agni that is the Scale plan: ₹12,999 for the first 2,500 minutes, then 7,500 minutes at ₹4 — ₹42,999 a month, about ₹4.30 a minute all-in, before GST. At that volume Enterprise is quoted instead, from ₹2/min. Nothing else is added: no speech-to-text line, no token bill, no hosting fee, no per-number charge.
We are deliberately not printing the other two totals. On Smallest.ai the honest answer is a range — 10,000 minutes at their published $0.09–$0.21 is $900 to $2,100 plus numbers and knowledge storage, and which end you land on depends on the model mix you choose. On Sarvam there is no per-minute agent price to multiply at all: you would model hours of speech-to-text, characters of speech, tokens of reasoning and your own telephony, and the total moves with how much your agent talks.
Publishing a converted rupee figure for someone else's dollar price list would be stale by the next exchange-rate move, and quoting a competitor's unpublished total would be inventing it. So: get a written per-minute quote from each vendor at your real volume, and check it against a pilot.
The four questions that settle pricing
- What is my all-in cost per completed call minute, in INR, at my volume?
- What is billed separately — speech, tokens, hosting, numbers, storage?
- Does the rate change if my agent talks more, or is it flat per minute?
- Is telephony inside the rate, or a second invoice from someone else?
Three language numbers that are not the same number
Every vendor counts languages differently — model layer versus agent layer, text-to-speech versus speech-to-text, language versus accent. Comparing the headline figures directly is the most common mistake in this evaluation.
Counted as languages an agent will hold a phone conversation in, with regional accent variants treated separately — a Kolkata Bengali agent and a Dhaka Bangla agent are not the same product.
The model layer is broader than the agent layer. If your language is one of the 22 but not one of the 10, that is a real gap to raise with them.
TTS and STT counts differ, and their marketing also cites 100+ voices across 30+ languages. Ask which number applies to a live agent in your language.
The only test that matters: take the ten hardest calls your team handled last week, in the languages they were actually handled in, and run them on each shortlisted platform. A vendor that supports your language on paper and mangles a Marathi name in practice has not supported your language. Ours are listed on the languages page.
India compliance is a product feature, not a policy document
This is the clearest difference between Agni and the other two, and it is the one that decides whether a calling programme survives its first compliance review.
DND and NCPR, before the dial
DLT templates and calling windows
Consent logs and audit trail
To be fair to both: Sarvam publishes something Agni does not match — every model in its Voice Agents stack is self-hosted, with India data residency including PII. Smallest.ai lists ISO 27001 and SOC 2 Type 2, which are certificates Agni does not hold; our posture is SOC 2 ready, GDPR ready and HIPAA ready, and we say "ready" on purpose. Those are different questions from TRAI campaign compliance, and a serious evaluation asks all of them.
Do not take our word for any of this. Interrogate the agent.
You are evaluating voice AI. The fastest way to judge a voice AI vendor is to talk to theirs. Tara runs on the same Agni platform this page is describing, with this comparison as her knowledge base — including the parts where Agni is not the right answer. She is briefed to be fair to Sarvam and Smallest.ai, and to say so when she does not know something.
- Interrupt her mid-sentence — barge-in is where most demos fall apart
- Switch to Hindi, Tamil or Bengali halfway through a question and keep going
- Ask her why you should pick Sarvam over Agni, and see whether she answers straight
- Ask for a discount, or for a SOC 2 certificate — both are things she is not allowed to give you
- Ask something she cannot know, and watch whether she invents an answer
Browser call, microphone only — nothing is installed and no number is required. This is a demo agent: what she says about Sarvam and Smallest.ai is summarised from their own public material as of August 2026, and commercial terms are always confirmed by a person.
Tara — Agni evaluation desk
Ask her the difference between Agni, Sarvam and Smallest.ai. She is briefed to be fair to all three, to name what Agni is not good at, and to never talk down a competitor.
She already knows what this page says. Push her past it.
English · हिन्दी · 30+ Indian languages · demo
When each one is the right answer
Written the way we would say it on a call, including the two columns that send you somewhere else.
- Indian-language phone campaigns need to be live this month
- A business team will run it; engineering must not be on the critical path
- DND/NCPR, DLT templates, calling windows and consent logs must be built in
- You want one all-in INR rate per minute your finance team can model
- You need beyond the big ten languages — 30+ languages, 100+ accents
- You want guided onboarding and humans on the phone, not just docs
- Sovereign Indian model ownership is a board-level or policy requirement
- You are an engineering team building your own voice or language product
- You need Indic models across many surfaces — apps, documents, IVRs
- Model-layer data residency and a fully self-hosted stack are mandatory
- You need OCR, translation or dubbing, which Agni does not do at all
- Per-API-unit metering matches how you meter your own usage
- Raw text-to-speech latency is your single deciding metric
- On-premise or edge deployment is a hard requirement
- Your footprint is global — European languages beside Indian ones
- You want to license the underlying models, not buy an operations layer
- A signed ISO 27001 or SOC 2 Type 2 certificate is a procurement gate today
- USD component billing fits how your finance team already works
Run both on the same campaignwe'll help you benchmark
The honest way to choose between Agni and Sarvam or Smallest.ai is a side-by-side pilot: same contact list, same calling window, same script. We'll help you set it up and read the results even if the answer is "stay where you are."
- Same DND-scrubbed list, call window, and script on both platforms
- Compare connect rates, language quality, and handoff accuracy
- Compare cost per completed call in INR, side by side
- Full transcripts and recordings from the Agni side for your review
Set up a benchmark pilot
Tell us your use case and current setup. We'll scope a like-for-like pilot, usually within one business day.
Or call our AI agent: +91 11 4056 6600The questions buyers actually ask us
Which one is actually the best?
None of the three is best in the abstract, because they are not the same shape of product. Sarvam is strongest at the model layer. Smallest.ai is strongest at raw speed and on-premise deployment. Agni is strongest at the operations layer — campaigns, DND/DLT compliance workflows, INR economics, analytics. Decide which layer you are actually buying, then settle it with a like-for-like pilot on the same list, window and script.
Is Sarvam a competitor to Agni now that it has Voice Agents?
Partly, and more than a year ago. Sarvam opened a self-serve Voice Agents builder in August 2026 — telephony, batch outbound calling, analytics — so there is real overlap at the platform layer, and anyone telling you Sarvam “only does APIs” is working from stale information. The difference sits above that layer: Agni ships India campaign operations — DND/NCPR scrubbing, DLT template workflows, calling-window enforcement, consent logs, dispositions — as product features, and prices calls all-in per minute in rupees rather than per API unit.
Smallest.ai claims ~100 ms and Agni claims under 300 ms. Are they faster?
The two numbers measure different things. The ~100 ms figure is for Lightning, their text-to-speech model — how fast audio starts coming out. Agni's sub-300 ms is end-to-end conversational response on a live phone call: listening, understanding, retrieval and speech together. Neither number settles it. Make real calls on both platforms over Indian telephony, where network conditions swamp both lab figures, and judge with your ears.
Can we use Sarvam or Smallest.ai models inside Agni?
No — Agni manages its own voice stack end to end, which is how latency, language quality and call behaviour stay consistent, so there is no model slot to fill. If your engineering team is already building on either vendor's APIs, the honest comparison is build versus buy: the campaign orchestration, DND/DLT workflows, transcripts, analytics and CRM sync you would still have to build is exactly what Agni ships.
Why is comparing the prices so hard?
Because the three bill on different units, and only one of them is the unit your finance team cares about. Agni publishes an all-in rupee rate per call minute. Smallest.ai publishes dollars per minute plus itemised hosting, STT, TTS, numbers and knowledge base. Sarvam publishes rupees per API unit — per hour of audio, per 10,000 characters, per million tokens — with no per-minute agent price. Model it on your own volume in the ROI calculator, then prove it with a pilot.
Is there anything Agni is genuinely not the right choice for?
Yes — several, and it is worth saying plainly:
- You want to license or fine-tune the underlying models — that is Sarvam or Smallest.ai, not Agni
- Sovereign Indian model ownership is a board-level or policy requirement — that is Sarvam
- You need document OCR, translation or dubbing rather than phone calls — that is Sarvam
- On-premise or edge deployment is mandatory — that is Smallest.ai
- A signed ISO 27001 or SOC 2 Type 2 certificate is a procurement gate today — Agni is SOC 2 ready, which is not the same thing
- You operate outside India, where the India compliance layer is irrelevant to you
Settle it with a call, not a comparison table.
Thirty minutes, your use case, your languages, your volume — and an honest answer about which of the three fits, even when the answer is not us.