AI for customer support in India

Customer support in India must be fast, multilingual, and cost-effective. Teams respond to tickets in Hindi, Tamil, Telugu, Kannada, Marathi—sometimes all in one queue. Manual triage, language barriers, and long response times drive churn. unoblox's OpenAI-compatible API lets you automate triage, route tickets, and respond in the customer's language, all billed in rupees.

Multi-language ticket triage

Qwen3.8-27B (₹16.32 / ₹48.96) natively understands Hindi, Tamil, Telugu, Kannada, Marathi, and English. Feed it a raw ticket; it classifies the issue (billing, technical, refund, feature request), suggests urgency (critical, high, normal), and routes to the right team—fast enough for live queues. No translation layer needed; faster and cheaper than English-only models.

Instant FAQ resolution

Qwen3 235B (₹9.07 / ₹55.44) resolves a large share of tickets instantly by searching your FAQ + knowledge base. A customer asks "How do I reset my password in Hindi?"; Qwen3 retrieves the right article, translates/summarizes it, and responds in Hindi. Automatically escalate to human for novel questions.

Sentiment & churn detection

DeepSeek V3.2 (₹26.21 / ₹38.30) analyzes customer tone and flags escalation: "The customer is angry; prioritize this." Over time, build a churn-risk model by analyzing support sentiment patterns.

Use-case	Recommended model	₹ input/output	Why
Multi-language triage	Qwen3.8-27B	₹16.32 / ₹48.96	Native Hindi/regional support
FAQ resolution	Qwen3 235B	₹9.07 / ₹55.44	Fast, cost-effective
Sentiment analysis	DeepSeek V3.2	₹26.21 / ₹38.30	Tone + escalation detection
Complex escalation	Claude Sonnet	₹201.6 / ₹1008	Nuanced reasoning for edge cases

Frequently asked questions

Will customers know they're talking to AI initially? You choose. Many teams respond with AI first, then escalate to human if the customer asks. Transparency is best: "AI support is available 24/7; escalate if needed."

Can AI draft responses for human agents to review? Yes. Route high-complexity tickets to agents; AI drafts a response suggestion. Agents read, edit, and send in under a minute instead of writing from scratch.

How much faster is AI-first support than human-only? First-response time drops from hours to seconds. A meaningful share of tickets resolve without ever reaching a human queue, which is the main lever for customer satisfaction scores.

Which model handles sarcasm and cultural context best? Claude Opus (₹504 / ₹2520) is most robust to sarcasm and cultural nuance. Qwen3 235B costs roughly 50x less on input tokens and handles most day-to-day support queries well — reserve Opus for the genuinely tricky edge cases.

Can I use embeddings to find similar past tickets? Yes. Embed resolved tickets; when a new one arrives, search for similar cases. Show the agent the solution + precedent. This is powerful for consistency and speed.

Is there a free tier to test support automation? Yes. Qwen3-1.7B is free (₹0). Start with free tier; move to 235B once you find it works for your support volume.

Get started in rupees → https://unoblox.ai/sign-in