Ringg AI

Ringg markets configurable voice, chat, WhatsApp and web AI agents with shared conversational memory, a no-code flow canvas, retries and voicemail handling, pre/post-call tools, more than 20 languages, sub-400ms latency and capacity for 120,000 interactions per hour. Its current integration examples say agents can read from and write to Google Sheets, Typeform, Shopify, Calendly, Notion and HubSpot; the Shopify example includes taking and tracking orders by voice. The homepage displays customer/logo proof for Flipkart, Tabby, Groww, DCB Bank, FloBiz, GrowthX, CRED, CollegeVidya and Tata 1mg, alongside customers with dedicated stories elsewhere.

The pricing page lists flexible usage at $0.10 per connected minute with up to 50 concurrent calls and 100-call bulk campaigns, a custom number at $6 per month and added concurrency at $10 per channel per month. Enterprise pricing for more than 100,000 minutes is advertised as low as $0.06 per connected minute with 100 concurrent calls, 10,000-call bulk campaigns, priority support and custom integrations. Parrot speech-to-text is $0.35 per hour. The same page also presents conflicting comparison/model figures of $0.08, $0.09 and $0.12 per minute and an FAQ starting price of $0.06. Vendor-hosted testimonial blocks report 80% lead engagement for Roombae and a 43% increase in call confirmations within two weeks across more than five languages for PharmaGrowth.

The current developer overview documents authenticated REST APIs, web calls, scheduled calls, bulk campaigns and webhooks. Calls expose status, duration, transcript, recording and classification; the quickstart says a first outbound AI call can be made in about five minutes using an X-API-KEY.

Ringg documents inbound, outbound and web-call agents for loan collections, lead qualification, reminders, onboarding and order/delivery operations. It claims capacity above 10,000 simultaneous calls, more than 20 languages and 99.9% script adherence in marketing copy, with a workflow of creating an assistant, connecting a number, launching a campaign and reviewing results.

Assistant behavior is configured through an objective, prompt guidelines, primary and secondary languages, variables, knowledge bases, retries, voicemail rules, chat/embed settings, keyword boosting, custom analysis and test calls. The guide demonstrates configured Hindi/English switching and developer handoff; it does not establish unconstrained independent planning.

Workspace settings support members with View & Edit or View Only permissions, an owner, API-key rotation, Twilio, Exotel and Plivo telephony, Zapier, Google Sheets and Shopify triggers, plus webhooks. Shopify triggers can start calls after a new order or delivery event; the documented permissions and single workspace key are less granular than action-specific runtime approvals.

The analytics dashboard reports calls, connections, connectivity rate, duration, cost, registrations and voicemail, with time filters, charts and assistant comparisons. The documentation frames analysis as input to human optimization rather than automatic campaign changes.

Webhook payloads expose lifecycle events, transcripts, recordings, platform and customer-defined analysis, call cost, latency, tool-call logs, action items, final status and error detail, providing machine-readable observability for configured workflows.

The Ameyo guide documents an inbound bot leg followed by a POST to Ameyo and PBX routing to a human agent. It supports explicit human handoff with a CRT identifier and some context, rather than treating escalation as a recommendation only.

Ringg's security guidance recommends HTTPS, data minimization, consent, retention controls, PII handling, CSP/domain allowlists, least privilege, disclosure and opt-out paths. It mentions two-factor authentication only if available; the page is operational guidance, not proof that each control or certification is currently implemented.

The ecommerce page markets cart recovery, order tracking, loyalty/rewards, feedback, delivery rescheduling and global language coverage at $0.12 per minute. It reports anonymous headline outcomes of 20% cart-recovery uplift, 70% faster query resolution, threefold repeat engagement and a 30% response rate versus 1% for IVR, while a named Roombae testimonial says campaigns reached market 35% faster.

Ringg describes production D2C workflows spanning shared voice/WhatsApp/email context, contextual cart recovery, WISMO, order/receipt reconciliation across OMS, logistics and finance, exception flagging/escalation, interaction analysis and campaign generation, and review responses. It claims contextual follow-up converts at three to four times generic outreach, review response is three to five times faster and reconciliation at more than 10,000 orders per month saves work equivalent to two to three full-time employees; customers, baselines and measurement windows are not named.

Ringg reports vendor-attributed ecommerce production ranges: 10–18% cart recovery and 15–45x call-cost ROI; 30–45% RTO reduction; a 15-brand, six-month cohort with 42–51% reduction in preventable RTO; verified customers 15–20% more likely to reorder within 90 days; qualified-lead conversion improvement of 30–50% with callbacks under one minute; and upsell revenue of 2–5%. The same article names Mr Spex with 52% WISMO automation, 70% identity verification and at least 30 seconds saved per call. Broad industry examples and hypothetical arithmetic were not treated as achieved Ringg outcomes.

The current official case-study hub enumerates six dedicated customer stories: Ekart, PlatinumRx, Practo, PolicyBazaar, smallcase and PharmEasy.

Ringg says Ekart uses multilingual agents for NDR follow-up, customer confirmation of reattempts and business-lead qualification/handoff. It reports more than 90,000 calls per month, 30% qualified business leads and five or more languages, with Hindi primary and Tamil, Telugu, Kannada and English included across flows.

Ringg reports that PlatinumRx handles more than 30,000 Hindi/English calls per month with API retrieval of medicine and order data, deterministic controls for sensitive flows and contextual human transfers through Knowlarity. Reported outcomes are 50% L0 containment, 35% L1 qualification/transfer and 90-second average handle time; before deployment response time exceeded two minutes and human capacity was about 500 calls per day.

Ringg says its Practo agent queries appointment availability APIs and completes bookings without a human in most cases. It reports 85% first-call resolution, response below three seconds, 70% lower operational cost and more than 1,000 appointments per day; a customer quote describes collaboration for more than one year.

Ringg reports more than 57,000 connected calls per day for PolicyBazaar, four-minute average qualified calls, a 5–7% qualified-lead rate and 67% containment. It says calls trigger within 60 seconds versus a prior 8–12-minute response; 67% are fully AI handled, 7% transfer to relationship managers and 26% request callback. The same 5–7% qualification rate appears in the before-state, so no rate lift is demonstrated. The story describes Hindi/English/Hinglish, 200 policy documents, BYOT/on-prem deployment and vendor-asserted ISO 27001, SOC 2 Type II, TRAI DND and IRDA disclosure compliance.

Ringg says smallcase deployed 20 agents in a multi-agent setup across KYC recovery, US-equities and lifecycle journeys using n8n and APIs and more than 20 voices. Vendor-reported outcomes are a 45% subscription-renewal uplift, 22% conversion uplift and 40% increase in platform engagement.

Ringg says PharmEasy's internal reorder logic selects users, Ringg voice agents call them and positive intent triggers a CleverTap WhatsApp message. It reports more than 130,000 calls and 27,000 connected minutes per month, more than 2,000 incremental monthly orders and more than ₹57.5 lakh incremental monthly GMV. Cohort selection is customer-controlled, not an independent Ringg decision.

Ringg announced a $5.5 million Series A led by Arkam Ventures with participation from Groww Founder Fund, Kunal Shah, Whitecap Ventures and Capital2B. Founder and CEO Siddharth is quoted. Ringg reports more than 1.5 million customer conversations per month, more than 18 languages and 24,576 assistants created in 2025. On-premise deployment and some deterministic-plus-agentic controls are described as future product direction, not current proof.

Ringg's official LinkedIn company profile lists a 2023 founding year, Bengaluru headquarters, privately held status and an 11–50 employee company-size band; 18 employee profiles were associated with the page at access time.

Ringg's official LinkedIn post describes the Series A as ₹48 crore and names Arkam, Stargazer, White Venture Capital, Capital2B and QED Investors. The participant list conflicts with the company's $5.5 million blog announcement and is preserved rather than reconciled by inference.

A founder-authored announcement says Ringg raised a $1 million seed round led by Capital2B and says production deployments can be completed in hours. Combined with the later Series A, the disclosed rounds sum to at least $6.5 million, but no official source states audited total funding.

Investor Rahul Chandra's statement, reposted by Ringg's founder, identifies the founders as Siddharth, Utkarsh Shukla and Kali Charan Vemuru and says proof-of-concept deployments can go live in 48 hours. It calls Ringg the firm's highest deployed ARR without disclosing an amount, so no revenue figure is supported.

The privacy policy identifies Stoic AI Private Limited and an Indian registered address and covers Ringg's inbound and outbound voice-agent services and processing of account, interaction and communications data.

Ringg publishes a short set of service terms covering use of the platform. The retained terms do not disclose enterprise SLA remedies, data-residency commitments, model-training boundaries, detailed retention periods or a full processing agreement.

Ringg names Kali C. V., CTO, as grievance officer/data protection officer, with a 48-hour acknowledgement target and a 15-day resolution target.

Ringg describes Parrot as its live speech-to-text API optimized for real-time Hindi-heavy and code-mixed speech. Additional languages are presented as roadmap items and were not scored as shipped Parrot capabilities.

Ringg's official product post shows dashboard support for reviewing call ratings and feedback. This supports current evaluation visibility, not automatic self-modification of deployed agents.

A founder post documents a Ringg rescheduling-agent demonstration at Shiprocket SHIVIR. It does not establish a Shiprocket API integration, commercial partnership, production deployment, attach motion or revenue economics.

The official Ringg content reposted by its founder says the company presented Indian-commerce voice use cases at Shiprocket SHIVIR and calls two Shiprocket leaders early adopters who enabled the showcase. Deployment scope and any technical or commercial Shiprocket relationship remain undisclosed.