A Hindi-Speaking AI Caller That Qualifies 200 Leads a Day — Without Adding Telecallers

A basic IVR (press 1 for sales, press 2 for support) can only respond to keypad inputs and fails the moment a caller speaks naturally. An AI voice agent conducts a real conversation — it understands what the caller says in natural language, responds appropriately, handles objections, asks follow-up questions, and takes actions like booking an appointment or updating a CRM record. It behaves like a trained telecaller, not a phone menu.

The most common India use cases: outbound lead qualification (calling fresh leads within 5 minutes), appointment or site-visit booking, EMI payment reminders and collection follow-ups, inbound customer support for FAQs and order status, post-delivery satisfaction calls, and re-engagement calls for inactive customers. Any call with a structured objective and predictable conversation flow is a strong AI voice agent candidate.

Yes — human handoff is a core feature. If the caller asks something outside the agent's scope, expresses frustration, or explicitly requests a human, the call is transferred in real time to a live agent with a full transcript and context summary. The live agent sees everything that was discussed so the caller does not have to repeat themselves. You set the escalation trigger threshold.

Modern neural text-to-speech voices (ElevenLabs, Play.ht, Azure Neural Voice) are significantly more natural than older IVR voices. For Hindi, we use voices trained on native Hindi speakers with natural intonation patterns. That said, many Indian businesses choose to disclose that the caller is an AI — particularly for lead qualification — because transparency builds trust and customers appreciate the quick response time regardless.

Hindi speech recognition has improved significantly with models like Whisper (OpenAI), Azure Cognitive Services, and Google Speech-to-Text. We test recognition accuracy against your specific use case vocabulary — product names, city names, Indian financial terms, and Hinglish mixing patterns — before go-live. For most business call contexts, we achieve 90%+ word accuracy. Regional accents (Bihari Hindi, Rajasthani Hindi) require additional tuning.

Yes. We configure language auto-detection at the start of the call — the AI responds to the caller in whichever language they use. If a caller starts in Hindi and switches to English mid-call, the agent follows. This is essential for Indian business calls where code-switching between Hindi and English is the norm rather than the exception.

We build AI voice agents in Hindi, Hinglish, Marathi, Tamil, Telugu, Gujarati, and Kannada — alongside English. Accuracy and voice naturalness vary by language. Hindi and Marathi are our strongest deployments. Tamil, Telugu, and Kannada require more tuning time but are fully functional. We recommend a language-specific pilot before full deployment for regional language builds.

Yes — Hinglish handling is specifically tuned in our builds because it is the dominant language pattern in Indian urban business calls. The AI uses Hinglish naturally in both text-to-speech output and intent recognition. We test specifically against Hinglish inputs like 'mujhe ek demo book karna hai' mixed with 'I want to know about pricing' to ensure the agent handles both without breaking.

Yes, subject to TRAI regulations. For commercial outbound calls, you must use registered telemarketer headers, call only during permitted hours (9 AM–9 PM), and scrub numbers against the DND registry before calling. FactoryJet builds all AI voice agents with TRAI-compliant infrastructure: registered headers via Exotel or Plivo, automated DND scrubbing, call time enforcement, and mandatory opt-out handling. For BFSI collection calls, we also incorporate RBI fair practice code requirements.

We use Exotel, Plivo, or Twilio India for telephony infrastructure, all of which are registered with TRAI and support Indian PSTN calling. For high-volume deployments (1,000+ calls/day), we recommend Exotel or a direct SIP trunk arrangement for better cost economics. The choice depends on your call volume, geographic coverage (some BSNL regions have better Exotel coverage), and whether you need inbound + outbound or outbound only.

Yes — Zoho CRM integration is standard in our Full Voice AI Platform. After each call, the AI automatically creates or updates the contact record, logs the call outcome, records the disposition (qualified/not interested/callback requested), attaches the call transcript, and moves the lead to the appropriate pipeline stage. For real estate, it also books site visits directly to Google Calendar or Zoho Bookings.

Yes — NBFC and BFSI collection is a common deployment. The AI makes payment reminder calls with personalised EMI and overdue balance information, offers payment options, captures promises-to-pay, and logs outcomes to your collection management system. All collection flows are built with RBI fair practice guidelines: no harassment, calls only during permitted hours, mandatory opt-out handling, and full audit trails.

A focused outbound voice agent for one use case (lead qualification or appointment booking) takes 3–4 weeks from kickoff to live calls. Full inbound + outbound platforms with Zoho integration take 5–6 weeks. Enterprise deployments with multi-language support and custom telephony infrastructure take 8–10 weeks. Timeline depends on script complexity, number of integrations, and language tuning requirements.

We need: your calling use case and current conversation script (or we design one), sample call recordings from your existing telecallers (for voice and style reference), API access to your CRM (Zoho, LeadSquared, or similar), lead data in CSV format for initial test batch, and a 45-minute discovery call. We handle TRAI registration setup and telephony infrastructure from there.

You get a performance dashboard showing call volume, answer rates, qualification rates, call durations, escalation rates, and revenue attribution. Every call has a transcript accessible in the dashboard. You can listen to call recordings, review AI decisions, and adjust the conversation flow through a configuration panel. We set up weekly performance review calls during the first month.

We guarantee a working AI voice agent that meets the agreed qualification or booking metrics in the test environment before go-live. If performance drops below agreed SLAs after launch, our post-launch support window covers diagnosis and remediation at no extra cost. Voice AI performance depends on call answer rates, which vary by lead quality and time of day — we document this clearly upfront so expectations are calibrated.

The most direct calculation: one telecaller at ₹18,000–₹25,000/month handles 50–80 calls/day. An AI voice agent handles 200+ calls/day at the cost of a one-time build plus telephony fees (₹0.50–₹1.50/call on Exotel or Plivo). For a business making 100 qualification calls/day, the AI pays back in 3–5 months and eliminates the recruitment and management overhead of a telecaller team entirely.

Telephony costs are charged per call by your provider: Exotel charges ₹0.50–₹1.00/minute for outbound calls; Plivo is similar. LLM API costs for conversation processing are typically ₹5,000–₹15,000/month for 100–200 calls/day. Text-to-speech costs (ElevenLabs, Azure) add ₹3,000–₹8,000/month. FactoryJet charges nothing ongoing unless you choose a maintenance retainer.

Yes. We offer a 2-week pilot covering one outbound calling campaign — 500–1,000 calls to a real lead segment. The pilot costs ₹80,000 and is credited against the full project if you proceed. You get full call recordings, transcripts, and a performance report showing qualification rate, answer rate, and CRM update accuracy. Most clients convert immediately after seeing the first 100 call transcripts.

Yes — an optional monthly maintenance retainer covers conversation flow tuning, new use case addition, telephony infrastructure management, and model updates. Most Full Voice AI Platform clients take a retainer at ₹20,000–₹45,000/month during the first 6 months. After that, most businesses manage independently through the admin dashboard.