2-minute response times. 24/7 availability. 80% query automation. Typical setup in 7–14 days.
Same 20 questions answered 50 times a day by overwhelmed support agents
No support after 6 PM — customers frustrated, reviews suffering
Scaling support requires hiring — expensive and slow to train
AI customer support works by combining a knowledge base of your products, policies, and FAQs with an AI that can converse naturally in Hindi and English. When a customer asks a question — on WhatsApp, your website, or app — the AI retrieves the relevant answer from your documentation and responds conversationally within seconds.
For queries it cannot resolve (complex complaints, refunds above a threshold, sensitive situations), the AI detects the need for human escalation and hands off seamlessly — passing the full conversation context so the human agent doesn't need to ask the customer to repeat themselves.
Support pages convert when buyers can see reduced response time, fewer repeat tickets, and a cleaner handoff path. This page makes the value obvious: customers get answers faster and your team gets time back.
We automate order status, refund policy questions, product troubleshooting, account help, and escalation intake. Each workflow is built to solve the most repetitive support requests first.
When the AI cannot confidently solve a case, it escalates with full context, preserving the conversation history and the customer’s details so your human team can step in without starting over.
We map your top support intents, build the answer knowledge base, design the handoff rules, and deploy the bot where your customers already ask for help. The goal is a fast launch with practical adoption.
You get a working support bot, a structured FAQ and policy knowledge base, escalation rules, and deployment support. That means your team can start resolving the right queries automatically from day one.
We build support automation that is practical, bilingual, and easy for your team to maintain. The focus is not just on answering faster, but on building a cleaner support system that actually lowers operational pressure.