®AI chatbots that answer like your best support rep.
Custom AI chatbots trained on your products, docs, and policies. They understand context, answer accurately, hand off to a human when they should, and quietly improve from every conversation. Built for web, WhatsApp, Slack, or anywhere your customers are.
When to hire us
- Your support team answers the same 50 questions every day
- Generic ChatGPT / off-the-shelf bots embarrass your brand
- You want a bot that knows your product, not just general knowledge
- You need multi-channel: web + WhatsApp + Slack with one source of truth
What is an AI chatbot?
An AI chatbot is a software system that holds natural-language conversations with users and responds based on a combination of trained knowledge and retrieval from a connected knowledge base — rather than matching keywords to scripted responses. Modern AI chatbots built on large language models like Claude or GPT understand context across a conversation, remember what was said earlier, interpret implicit intent, and adapt tone to the user. The difference from a traditional rule-based bot is substantial: a rule-based bot gives a fixed response to 'What's the return policy?' and breaks if the customer phrases it differently; an AI chatbot understands the intent and answers based on your actual policy documentation.
Nowgray builds AI chatbots trained specifically on your business — your products, your policies, your past support tickets, and your FAQs — not on the open internet. We use Retrieval-Augmented Generation (RAG) architecture, which means the bot retrieves relevant documents at query time rather than having all knowledge baked in at training. This makes it updatable as your policies change without retraining, and every answer is grounded in your documentation — citable, accurate, and specific to your business. We deploy to wherever your customers are: a web widget, WhatsApp Business, Slack, Microsoft Teams, or an in-app integration. One AI brain, multiple surfaces.
The most important design question with any AI chatbot is what happens when it doesn't know the answer. Our bots are designed to recognise the boundary of their knowledge and transfer cleanly to a human agent — with the full conversation context carried over, so the customer doesn't have to repeat themselves. Every conversation is logged, and we implement a feedback loop: conversations where customers seem unsatisfied or where the bot escalated to a human get flagged for review and feed back into improving the knowledge base. Accuracy doesn't degrade over time — it improves. We also implement hallucination guardrails: the bot will not answer a factual question unless the answer is grounded in your documentation. If it doesn't know, it says so.
The capabilities, spelled out.
Trained on your knowledge
We ingest your docs, FAQs, policies, and past tickets to ground the bot in your reality — not the open internet.
Human handoff
Smart escalation — bot recognises when it should pass to a human, with full context handed over (not 'how can I help you today?' again).
Multi-channel deploy
One bot, multiple surfaces — web widget, WhatsApp, Slack, Microsoft Teams, in-app. Single brain, many faces.
Multi-language
Speak to customers in English, Hindi, regional Indian languages — naturally, with the same accuracy.
Safety & accuracy
Refuses to answer outside its knowledge. Cites sources. Hallucination guardrails. PII redaction in logs.
Analytics & feedback loop
See top questions, deflection rate, customer satisfaction. Failed conversations feed back into improvements.
Our default stack.
We'll pick the right tools for your project — but if you don't care, this is what we usually reach for.
Outcomes, not just hours.
- Deflect 40–70% of repeat support questions automatically
- Reply in under 2 seconds, 24/7, in every language your customers speak
- Cite sources — every answer traceable to your real documentation
- Improves over time as you label conversations — no static script
Common questions.
How is an AI chatbot different from a traditional chatbot?
Traditional chatbots match keywords to scripted responses — they break when customers phrase questions differently. AI chatbots built on large language models understand natural language, context, and intent. They can answer questions they've never been specifically programmed for, as long as the answer exists in their knowledge base. The experience is closer to a knowledgeable support representative than a phone menu.
Can the chatbot be trained on our specific products and policies?
Yes — that's the entire premise. Generic off-the-shelf AI bots know nothing about your pricing, your return policy, your product variants, or your procedures. We train the bot on your knowledge base, product documentation, FAQ lists, and support ticket history. The result is a bot that gives accurate, specific answers about your business, not general-internet guesses.
What happens when the chatbot doesn't know the answer?
It says so and transfers to a human agent — with the full conversation context so the customer doesn't have to repeat themselves. We design explicit escalation rules: categories of questions the bot should always hand off, frustration signals that trigger escalation, and VIP customer detection. The bot is designed to know its limits, not pretend it knows everything.
How long does it take to build and deploy an AI chatbot?
A web-channel chatbot trained on an existing knowledge base typically takes 3–6 weeks. Multi-channel deployments (web + WhatsApp + Slack) and those requiring integrations with existing support systems (Intercom, Freshdesk, Zendesk) take 6–10 weeks. We run a pilot on a limited audience first, tune based on real conversations, then broaden the rollout.
Let's scope your chatbots that actually know your business.
Tell us what you have in mind — we'll come back with a clear plan, timeline, and quote.