Case Studies
Automotive Manufacturing Conversational AI Omnichannel

24×7 Multi-Channel Customer Support AI — Omnichannel Conversational AI for a Leading Automotive Group

A leading Indian automotive and manufacturing group was fielding 150,000+ monthly support inquiries with 45-minute hold times. BootLabs deployed an omnichannel AI platform across voice, WhatsApp, and web — available around the clock in 12+ Indian languages.

Customer support AI platform
Industry
Automotive / Manufacturing / Farm Equipment
Services
Agentic AI · Conversational AI · Multi-Channel Deployment
Platform
Azure OpenAI · Azure Bot Framework
The Challenge

150,000 monthly inquiries, 45-minute hold times, and information scattered everywhere

One of India's largest automotive and manufacturing groups was operating customer support centres handling over 150,000 monthly inquiries across vehicle breakdowns, maintenance questions, feature explanations, and service scheduling — spanning both automotive and farm equipment divisions. Peak call volumes during Monday mornings and post-holiday periods pushed hold times to 45 minutes, frustrating customers and overwhelming agents. Sixty percent of calls were tier-1 queries easily resolved without a human — yet customers defaulted to calling because information was scattered across owner's manuals, mobile apps, and dealer websites. Support costs ran high, and customer dissatisfaction was driving NPS and retention scores downward. BootLabs deployed an omnichannel conversational AI platform handling voice, text, and image inputs — available 24/7 across web, mobile app, and WhatsApp — with intelligent escalation to human agents for complex cases.

Client Snapshot
Client A Leading Indian Automotive & Manufacturing Group
Divisions Automotive, Farm Equipment, Financial Services
Scale 2,500+ authorised service centres across India
Volume 150,000+ monthly customer support inquiries
Business Challenges

What was holding them back

01
Peak Volume Overload

45-minute hold times during peak periods frustrated customers and overwhelmed agents. 60% of queries were simple enough for self-service but there was no effective channel to handle them at scale — every call landed with a human agent regardless of complexity.

02
Fragmented Information Landscape

Product information, service guides, owner's manuals, and dealer locations were scattered across multiple platforms. Customers couldn't find answers without calling — and agents had to context-switch across the same fragmented sources, slowing every interaction and increasing handle time.

03
Multilingual Support at Scale

Customers across India communicated in 12+ regional languages. The support operation could not cost-effectively scale human agents to cover all linguistic needs with consistent quality — creating unequal service experiences and leaving significant customer segments underserved.

Our Approach

How we solved it

01
Omnichannel Conversational AI

Azure Bot Framework deployed across web chat, WhatsApp Business API, and mobile app. A unified conversation state layer maintains context across sessions — customers can start on WhatsApp and continue on web without repeating themselves. One AI, every channel, coherent experience.

02
Multimodal Input Processing

The AI accepts text, voice (Azure Speech Services), and images. Vision models identify dashboard warning symbols, fluid leaks, or damaged parts from customer-submitted photos — mapping them directly to the diagnostic knowledge base for resolution without agent involvement.

03
Intelligent Escalation & Smart Routing

A fine-tuned BERT intent classifier routes complex issues — safety concerns, warranty disputes, unresolved technical issues after three turns — to human agents with full conversation history and a suggested resolution pre-loaded. Agents take over an informed conversation, not a cold call.

04
Multilingual & Personalisation Engine

12 Indian languages plus English, with cultural localisation. For registered vehicle owners, the system recognises the customer, recalls vehicle history and previous interactions, and tailors responses to their ownership tenure and service record — turning support into a personalised experience.

The Outcomes

Results that proved the approach

60%
Reduction in inbound support call volume through self-service deflection
4.2/5
Customer satisfaction score on AI-handled interactions
12+
Indian languages supported with full localisation

The platform went live across all three channels simultaneously — web, WhatsApp, and mobile — with no disruption to the existing support operation. Call deflection reached 60% within the first full billing cycle as customers discovered they could resolve inquiries instantly, at any hour, in their own language. The same support team now handles 2.5× the effective inquiry volume without headcount increase.

Azure OpenAI Azure Bot Framework Azure Speech Services GPT-4 Multimodal AI WhatsApp Business API BERT Intent Classification Cosmos DB Automotive Multilingual
Business Impact

What changed for the organisation

2.5× Effective Inquiry Capacity

The same support team now handles 2.5 times the effective inquiry volume without headcount increase — AI handles the high-frequency tier-1 queries so agents focus entirely on complex, high-value interactions.

Fully Self-Service Transactions

Service appointment bookings, parts availability checks, and warranty status are now fully self-service — zero agent needed. Customers complete these transactions in under two minutes, any time of day.

Real-Time Sentiment-Based Prioritisation

Real-time sentiment detection automatically prioritises frustrated customers for empathetic human escalation — ensuring the customers who most need a human get one fastest, improving NPS on the interactions that matter most.

Trending Issue Analytics Loop

Trending issue analytics feed back into product teams — warranty failure patterns and regional complaints are now visible within 24 hours, turning the support operation into an early-warning system for quality and design decisions.

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