Build an AI Inbound Hindi Voice Agent in 30 Minutes

In ~30 minutes, build a Hindi/Hinglish inbound voice agent that answers calls, captures clean lead data, books a Google Meet, saves to Google Sheets, and sends an SMS—exactly like the one I deploy for clients.

WORKFLOW DOWNLOAD: https://drive.google.com/file/d/1z3dT...
X/Twitter: https://x.com/TopR9595
Book a strategy call (Calendly): https://calendly.com/shreyasrajsony11...
Done‑for‑you automation: https://rapidxai.com

THE BUILD BREAKDOWN

Setup/Context: We’ll connect Vapi (voice), OpenAI (structured extraction), n8n (routing), Google Sheets (logging), and Twilio (SMS).

Challenge: Missed calls and messy intake lead to lost revenue. Hindi/Hinglish callers need a natural agent that asks one‑by‑one questions and confirms digits clearly.

Solution/Demo: Webhook → AI Agent → Filter → Append Row in Sheet → Send SMS. Name first, Hinglish tone, digit‑by‑digit phone confirmation (for example, 9‑1‑9‑3‑0‑7‑5‑1‑2‑8‑1‑6), online meeting before any on‑site.

Objection Handling: Language mixups, looping, OAuth headaches, and SMS delivery—fixed with model/transcriber settings, structured output, and tested OAuth scopes.

Result: Call → lead captured in Sheets → owner notified via SMS → Google Meet booked in minutes.

TIMESTAMPS

00:00 – Intro and live demo (Hindi/Hinglish) 01:12 – What this agent does and when to use it 02:38 – Create Vapi assistant (assistant speaks first) 04:15 – Voice settings: 11Labs Turbo, background sound off, speaker boost on 05:46 – Transcriber choice (Nova 3 vs. Monty) and Hindi handling 07:05 – Link phone number and quick call test 08:22 – n8n overview: Webhook → AI Agent → Filter → Append Row in Sheet → Send SMS 09:28 – Webhook setup and payload structure 10:40 – AI Agent node (GPT‑4.1 mini) plus structured output schema 12:14 – Fields: name, phone, email, location, requirement, interested 13:32 – Filter logic: keep only interested leads 14:18 – Google Sheets node and column mapping 15:42 – Google Cloud OAuth (consent screen, scopes, test users) 18:36 – Twilio credentials and SMS alert template 20:08 – Fixing transcription loops and mapping issues 22:02 – Live execution test (booking flow) 24:24 – Sheet save plus SMS received 26:05 – Best practices: Hinglish tone, digit confirmation, say “Rupees” 27:42 – Optional: move storage to Supabase 29:10 – Wrap‑up and next steps

KEY LESSONS

Ask one thing at a time. It boosts completion rate and transcript accuracy.

Confirm digits individually. Prevents bad leads and failed follow‑ups.

Structured output beats free text. Reliable fields for Sheets/CRMs.

Online meeting first. Qualify fast, then suggest on‑site if needed.

Hinglish wins. Cultural fit leads to higher trust and better intent signals.

WHY THIS APPROACH WORKS

Inbound calls are high‑intent. A Hinglish agent with structured extraction removes friction: it understands, captures, and books without human wait times. n8n orchestrates deterministic steps; Vapi and OpenAI handle understanding; Sheets and SMS create instant visibility and follow‑through.

CONNECT WITH ME

X (Twitter): https://x.com/shreyasrajsony11

Instagram:   / shreyasrajsony11  

Course: https://educatexai.com

WhatsApp: +91 9307512816

Done‑for‑you automation: https://rapidxai.com

Comment “HINDI” if you want the prompt pack and n8n node JSON!

Tags (YouTube)

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Hashtags (YouTube)

#AI #Hindi #VoiceAgent #InboundCalls #n8n #Vapi #OpenAI #GoogleSheets #Twilio #Automation #Hinglish #BusinessAutomation #AIAgent #VoiceBot #CRM #LeadGen #Booking #SMS #India #tutorial

Voice Agent Prompt:

https://docs.google.com/document/d/1w...

Use the above prompt for Guidance