Ticket Triage & Routing
Reads every incoming ticket, tags it, sets priority and assigns it to the right person or queue automatically.
Result: First-response time drops sharply with zero extra headcount.
04 · AI Support Agents
Support that has already started before anyone logs in
Support cost scales with customers unless something breaks the link. AI agents break it by handling the repetitive 60% completely and making the remaining 40% faster for your humans.
- Starting at
- ₹60,000
- Typical timeline
- 3–5 weeks
- Services in this line
- 6
The problem
Most support tickets are not hard. They are just numerous, and they arrive at the worst possible time.
What we build
6 services in AI Support Agents
Each one is a page of its own — pick the closest match, or tell us your problem and we'll point you at the right one.
Auto-Reply Drafting
Writes a complete, accurate, on-brand reply using your knowledge base and the customer's history. Your agent reviews and hits send.
Result: Agents handle two to three times the tickets without rushing.
Escalation & Sentiment Agent
Spots frustration, repeated contacts and churn language, and pulls a human in before the customer posts a review.
Result: Problems get caught while they are still fixable.
Complaint Resolution Agent
Handles the full complaint flow — acknowledge, investigate, propose a resolution within your policy, and follow up until closed.
Result: Consistent handling instead of it depending who picked up.
Order Tracking Agent
Answers 'where is my order' from your live system across WhatsApp, email and chat, without a human ever seeing it.
Result: The single most common ticket type disappears.
Refund & Cancellation Agent
Applies your refund and cancellation policy consistently, processes the eligible ones, and escalates the edge cases with a recommendation.
Result: Faster refunds, fewer disputes, one consistent standard.
What you get
Included in every engagement
- Auto-triage: category, priority and owner set on arrival
- Draft replies your agents edit and send in seconds
- Sentiment detection that escalates before a customer explodes
- Self-service resolution for the top repeated issues
- Integration with your helpdesk (Zoho Desk, Freshdesk, Zendesk, email)
- Weekly report on what is actually breaking
How it's built
Typical stack
- LLM classification + RAG
- Zoho Desk / Freshdesk / Zendesk
- Email + WhatsApp channels
We pick tools per project rather than forcing every client onto the same stack. If something in your business already works, we build around it instead of replacing it.
In depth
AI Support Agents: what you should know before you commit
The measure of a support agent is not how many conversations it handles. It is whether the ones it could not handle reached a person quickly, with the context intact. Deflection rate on its own is a number that hides angry customers.
The support problem in an Indian SMB
Support in most small and mid-sized Indian businesses is not a department. It is two people who also do something else, a WhatsApp number, and a shared inbox that nobody owns after seven in the evening.
The consequence is predictable. The same fifteen questions consume most of the available hours, genuine problems wait behind routine ones, and anything arriving at night waits until morning.
An agent that handles the routine fifteen properly does not reduce your support headcount. It changes what those two people spend their day on, which is a different and better outcome.
What sits in this category
| Agent | Handles | Escalates |
|---|---|---|
| Customer support agent | Routine product and account questions | Anything with a policy exception |
| Ticket triage agent | Categorising, prioritising, routing | Nothing — it never answers |
| Order tracking agent | Where is my order, delivery changes | Lost or damaged consignments |
| Complaint resolution agent | Acknowledge, investigate, propose | Refunds and goodwill decisions |
| Internal helpdesk agent | IT, HR and policy questions from staff | Anything personal or contested |
| Feedback and survey caller | Post-service calls, NPS collection | Any negative response, immediately |
Deflection rate is the metric that misleads
A support agent reporting 78% deflection sounds excellent. It is meaningless without knowing which conversations were in the 22%.
If the agent handled every simple question and every angry customer escalated within a turn, that is a good system. If it deflected the angry customers by tiring them out until they gave up, the same number describes a business quietly losing its most vocal users.
We measure differently: escalation speed, customer satisfaction on escalated conversations specifically, repeat contact rate — did the customer come back because the first answer did not work — and the list of questions the agent could not answer at all, which is the most useful operational output the system produces.
Where the knowledge comes from
An agent is only as good as the material behind it, and most businesses have more than they think — help pages, product documentation, warranty terms, past email replies, WhatsApp conversation history.
Past support conversations are usually the highest-value source and the most overlooked. They contain the questions customers actually ask, in the words they actually use, with the answers your best agent gave.
The ingestion also produces a by-product worth having: the contradictions. Two policies that disagree, a warranty term stated three different ways across three documents. A person navigates those by knowing which to trust; a system surfaces them, which is uncomfortable and useful.
Working in the channels Indian customers use
Support in India happens on WhatsApp far more than on a website widget or an email thread. Any agent that does not work there is solving the problem where it is not.
That brings specifics: Meta bills per 24-hour conversation window rather than per message, so a long back-and-forth costs the same as a short one; template messages are required to initiate contact and must be registered in advance; and customers expect an immediate reply because that is how the channel behaves socially.
We usually deploy WhatsApp first, then the website, then email — in the order the volume actually arrives rather than the order that is easiest to build.
The tone question, which matters more than it sounds
A support agent's register has to fit the business. A premium furniture brand and a spare parts distributor should not sound the same, and neither should sound like a generic assistant.
It also has to handle irritation without escalating it. A customer who opens angrily needs acknowledgement before information — a system that responds to a complaint with a policy quotation makes the situation worse in one message.
We define this from your own past replies rather than from a brief, and we test it against real angry messages from your history before go-live. That test catches more problems than any amount of happy-path testing.
Realistic scope and cost
Four to twelve weeks depending on the agent, from ₹1,50,000 to ₹4,00,000. Running costs for a business handling a few thousand conversations a month typically land between ₹4,000 and ₹15,000 including WhatsApp charges.
You receive the agent on your infrastructure, the knowledge base as editable content your team owns, the escalation rules, the conversation log, and full source. The unanswered-question report is delivered weekly, because acting on it is what makes the system improve rather than plateau.
FAQ
Questions people actually ask
Do we lose the human touch?
Only if you build it badly. The point is to remove the tickets that never needed a human so your team has time to be genuinely helpful on the ones that do.
Can it work over WhatsApp as well as email?
Yes. In India, WhatsApp is usually the higher-volume support channel and we treat it as first-class.
Other AI service lines
Next step
Let's work out what's worth building.
A 30-minute call. We'll tell you what we'd do, roughly what it costs, and whether it's worth doing at all.