Use-case definition
We decide what the assistant should handle, what it must never answer, and when it hands over — before choosing any technology.
03.3.2AI chatbot integration
AI chatbot integration for websites and apps
A good AI assistant answers the questions your team answers every day — timings, prices, eligibility, how something works — accurately and in your tone, and knows when to pass the conversation to a person. We build assistants grounded in your own content, with limits on what they'll say, so they help customers instead of inventing answers.
Who it’s for
- Businesses answering the same customer questions all day
- Clinics, schools and service businesses with detailed FAQs
- SaaS products that want in-app help grounded in documentation
- Teams with large knowledge bases staff struggle to search
- Websites that want to capture and qualify enquiries after hours
What’s included
Knowledge preparation
Your website pages, documents and FAQs organised into a clean source the assistant answers from, so replies come from your content rather than the open internet.
Chat interface
A chat widget designed to match your site, accessible, and usable on mobile.
Guardrails
Instructions and checks that keep answers on topic, stop the assistant guessing, and show a fallback when it isn't sure.
Handover and lead capture
Conversations that need a person are passed on by email or to your existing tools, with the context attached.
Review and improvement
Conversation logs reviewed after launch to find gaps in the content and questions the assistant should or shouldn't handle.
What you get
- Knowledge sources
- Your website, documents and FAQs
- Channels
- Website widget (others TODO: from Dev)
- AI model/provider
- TODO: confirm with Dev
- Data handling
- TODO: confirm storage and privacy approach
How it works
- 01Define
Questions to handle, tone, limits and handover rules.
- 02Prepare
Content gathered, cleaned and structured for retrieval.
- 03Build
Assistant, guardrails and chat interface developed and connected.
- 04Test
Tested against real questions, including ones it should refuse.
- 05Launch and tune
Go live, review conversations, improve the content and rules.
Tools & tech
Next.js / ReactNode.js / ExpressMongoDBAWSTODO: AI model/provider from Dev
Timeline
TODO: typical duration from Dev
Starting from
TODO: ₹ from Dev
Questions we get asked
Will the chatbot make things up?
Any AI model can produce wrong answers, so we design against it: the assistant answers from your content, is told to say when it doesn't know, and hands over to a person for anything outside its scope. We test it on tricky questions before launch.
What content does it learn from?
The pages, documents and FAQs you choose. It doesn't need to be trained from scratch — your content is organised so the assistant can look up the right passage when answering.
Is customer data safe?
We agree up front what the assistant can collect and where conversations are stored. TODO: add Dev's standard data-handling approach and provider details.
How much does AI chatbot integration cost?
Cost depends on the amount of content, the channels, integrations with your tools, and ongoing usage fees charged by the AI provider. TODO: add a ₹ starting price once Dev confirms it.
Can it book appointments or take orders?
It can hand those requests to your booking or order system where that system has an API. We scope integrations case by case.
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