Chatbots that know your business
A chatbot that hallucinates answers is worse than no chatbot at all. I build assistants that retrieve answers from your documents, product catalogue or knowledge base, cite their sources, and refuse gracefully when they do not know.
The retrieval pipeline chunks your content sensibly, embeds it into a vector store, and grounds every answer in retrieved passages - which makes answers auditable and trustworthy.
Use cases that work
Customer support deflection on high-volume pages. Internal policy and documentation lookup for teams. Sales qualification on landing pages that captures leads while answering questions. Onboarding walkthroughs inside a product.
Each use case has different requirements for tone, data access and escalation - the architecture handles all of them.
Production hardening
Topic boundaries, refusal handling, per-user rate limits and cost controls keep the bot useful and affordable at scale. Model routing sends cheap questions to fast models and hard questions to stronger ones.
Conversation logging, satisfaction signals and a dashboard show what users actually ask - which often reveals content gaps and product issues.
Frequently asked questions
Can the chatbot use our private documents?
Yes. Documents are indexed into a private vector store that only your deployment can query. No data is shared with other customers.
How long does a chatbot project take?
A grounded assistant on an existing content set typically ships in two to four weeks.
Which platforms can the chatbot live on?
Website widget, WhatsApp, Slack, internal tools or any interface with an API. The backend is platform-agnostic.
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Tell me what you need and you get a written scope, a fixed quote and a delivery timeline before any work starts — no obligation.
Ananth N · Madurai, Tamil Nadu · serving Madurai, Coimbatore, Chennai and clients across India · remote-first.
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