Ringg AI
by Ringg AI
Multilingual voice, chat and WhatsApp agents for high-volume enterprise conversations
Ringg AI builds multilingual AI voice and chat agents for enterprises, handling roughly 20 million call attempts a month across voice, chat, WhatsApp and browser channels. It runs its own speech-to-text model tuned for Indian speech alongside bundled telephony, and is used for appointment booking, lead qualification, KYC and collections by companies including CRED, Flipkart, Practo and PolicyBazaar.
Ringg AI builds multilingual AI voice and chat agents for enterprises, and now runs about 20 million call attempts a month. The platform covers inbound and outbound voice, chat, WhatsApp and browser-based agents from one orchestration layer that routes work across speech models rather than betting on a single one, and it runs proprietary components — an in-house speech-to-text model called Parrot tuned for Indian speech, natural TTS, and a fine-tuned LLM the company positions at 4.1-class intelligence — together with bundled telephony. Builders get a visual agent builder with branching logic and conditional execution, a unified context layer that carries conversation memory across channels, voicemail detection, call scheduling and booking, and a QA and analytics module that monitors conversations and flags hallucinations and interruptions. Integrations include HubSpot, Shopify, Calendly, Notion, Google Sheets and Typeform, and the company claims support for more than 20 languages and 120,000-plus interactions per hour of concurrency. Typical deployments are appointment booking in healthcare, lead qualification in education, abandoned-cart recovery in e-commerce, and KYC, onboarding and loan collections in financial services. Founded in Bengaluru as the text-to-speech startup DesiVocal and later pivoted, Ringg is led by Siddharth Tripathi, Utkarsh Shukla and Kali Charan Vemuru, employs around 40 people, and counts CRED, Flipkart, Practo, Groww, PolicyBazaar, Tata 1mg, DCB Bank, smallcase, PharmEasy and Shell among its customers. In August 2026 it extended its Series A by $10 million led by Peak XV Partners, taking the round to $15.5 million.
Heads of customer operations at high-volume consumer businesses in India and adjacent markets — lending, insurance, healthcare and e-commerce — where millions of monthly calls run in Hindi, English and regional languages that generic Western voice stacks handle badly.
Outbound and inbound conversation volume that would need a large call-centre bench runs as AI agents at roughly ₹6 per connected minute, with telephony, speech models and QA analytics included rather than assembled from separate vendors.
At a Glance
- Category
- Audio & Voice
- Pricing
- Usage-based, Freemium, Contact for pricing
- Target Market
- Heads of Customer Operations, CIOs, Contact Centre Leaders, Growth and Revenue Teams
- Deployment
- Cloud-first, API-based, Self-hosted
- Founded
- 2023
- Headquarters
- Bengaluru, India
- Team Size
- 11-50
- Customers
- Named enterprise customers include CRED, Flipkart, Practo, Groww, PolicyBazaar, Tata 1mg, DCB Bank, smallcase, PharmEasy and Shell; ~1,200 clinics via the Practo deployment
Key Features
- ✓Parrot speech-to-text tuned for Indian speech
An in-house STT model trained for Indian accents and code-mixed speech, where generic English models degrade badly on real customer calls.
- ✓Omnichannel agents with unified context
Voice, chat, WhatsApp and browser agents share one conversation memory, so a customer does not restart the conversation on each channel.
- ✓Visual agent builder
A workflow editor with branching logic and conditional execution lets operations teams change call flows without engineering involvement.
- ✓QA and analytics module
Monitors live conversations and flags hallucinations, interruptions and quality issues, which is the control most voice deployments lack.
- ✓Model orchestration layer
Routes tasks across multiple speech and language models rather than depending on one vendor, so quality and cost can be tuned per use case.
- ✓Bundled telephony and concurrency
Telephony, phone numbers and concurrency are sold with the platform, supporting a claimed 120,000-plus interactions per hour.
- ✓Voicemail detection and scheduling
Detects answering machines and handles call scheduling and booking, which materially changes the economics of outbound campaigns.
Capabilities
Use Cases
- •Clinic appointment booking at scale
Voice agents confirm, reschedule and remind patients across a large clinic network, cutting no-shows without adding front-desk headcount.
- •Loan collections outreach
Lenders run repayment reminder and collections conversations in regional languages at volumes a human bench could not economically cover.
- •Insurance and fintech lead qualification
Inbound and outbound agents qualify interest, capture details and hand warm leads to human sales staff with full conversation context.
- •Abandoned-cart recovery in e-commerce
WhatsApp and voice agents follow up on abandoned baskets and coordinate delivery or exchange logistics using shared cross-channel memory.
- •KYC and customer onboarding verification
Agents walk new customers through identity and onboarding steps, logging every exchange for the QA and compliance review trail.
Ideal For
Best For
- ✓High-volume outbound calling in Indian languages, where accent and code-mixed speech break generic speech models
- ✓Appointment booking and reminders for healthcare networks and clinic chains
- ✓Lead qualification and abandoned-cart recovery for consumer e-commerce and education businesses
- ✓KYC, onboarding and loan collection conversations for banks, lenders and insurers
- ✓Teams that want voice, chat and WhatsApp agents sharing one conversation memory rather than three disconnected bots
Not Ideal For
- ✗Enterprises that need US or EU data residency and a mature Western compliance posture — the deployment base, telephony and speech tuning are India-first, with only early Middle East and US presence
- ✗Highly complex, multi-step conversations: the company itself found simple outbound tasks were not sticky, and competitor comparisons report the agents struggle when callers interrupt or ask multi-step questions
- ✗Buyers who need deep CRM-native workflow automation after the call ends — integrations exist, but the platform's centre of gravity is the conversation itself
- ✗Low-volume teams chasing the best per-minute rate, since the meaningful discounts sit at enterprise call volumes
Integrations
Deployment
Market & Ratings
Named enterprise customers include CRED, Flipkart, Practo, Groww, PolicyBazaar, Tata 1mg, DCB Bank, smallcase, PharmEasy and Shell; ~1,200 clinics via the Practo deployment
Market Analysis
Pros
- ✓Real production scale, not a pilot story: roughly 20 million monthly call attempts and named enterprise logos including CRED, Flipkart, Practo, Groww and PolicyBazaar
- ✓Owning the speech-to-text model rather than reselling one is a durable advantage in Indian-language and code-mixed calling, where generic models degrade
- ✓Transparent published per-minute and per-session pricing plus free signup credits, against a category norm of quote-on-request
- ✓Voice, chat, WhatsApp and browser agents share one context layer, so the platform is not the voice-only point tool most competitors ship
- ✓Peak XV Partners led the August 2026 extension with Arkam Ventures and Capital 2B, taking the Series A to $15.5 million
Cons
- ✗Heavily India-concentrated: telephony, speech tuning, pricing currency and nearly all named customers are Indian, with Middle East and US presence still early — a real constraint for global enterprises with EU or US data-residency requirements
- ✗Competitor comparison pages report the agents struggle when callers interrupt or ask multi-step questions, and note constraints on bulk-campaign size on lower tiers
- ✗The company itself concedes the pivot rationale: simple outbound calling tasks 'are not sticky use cases', which is a candid admission that the easy end of the market does not retain
- ✗Add-on costs stack on top of the headline rate — ₹499 per phone number per month, ₹2 per call for advanced analytics, concurrency quoted separately — so per-minute pricing understates the real bill
- ✗Small team of roughly 40 people against far better-funded voice rivals and the speech-model vendors it orchestrates, including Deepgram, ElevenLabs and Sarvam
- ✗No independently verified review score: G2 blocked direct retrieval and the only rating found was cited on a competitor's comparison page, which is not a source worth quoting a number from
Pricing
Pay as You Go
From ₹6 per connected minute
- ✓Voice agents at ₹6 per connected minute
- ✓Chat and WhatsApp at ₹2 per 5-minute session
- ✓Browser agents at ₹15 per minute
- ✓Speech-to-text API at ₹30 per hour of transcription
- ✓Proprietary Parrot STT, natural TTS, fine-tuned LLM, telephony and basic analytics
Enterprise
Contact for pricing
- ✓Custom pricing
- ✓On-premises deployment
- ✓Outcome support
- ✓Custom concurrency
Metering is genuinely usage-based and published, which is unusual in this category: ₹6 per connected voice minute, ₹2 per five-minute chat or WhatsApp session, ₹15 per browser-agent minute and ₹30 per hour of standalone transcription, with free credits on signup so an agent can be built and tested before any contract. Add-ons are separate — ₹499 per month per phone number, ₹2 per call for advanced analytics, and concurrency priced on request — so the headline per-minute rate is not the whole bill. On-premises deployment and outcome-based support sit behind the Enterprise plan with no published price, and a competitor's comparison page reports meaningful per-minute discounts only above roughly 100,000 monthly call minutes.
Security & Compliance
Sources
This page was written from 6 sources, 4 on domains other than ringg.ai.
- 1.ringg.ai — ringg.aivendor
- 2.ringg.ai — pricingvendor
- 3.techcrunch.com — indias ringg gets backing from peak xv as it pushes voice ai
- 4.entrackr.com — voice ai startup ringg raises 10 mn led by peak xv 12435121
- 5.omnidim.io — alternatives ringg
- 6.techstartups.com — startup funding news today august 26 2026 emerald ai gatik s
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