Chatbot on Demand
A privacy-first assistant that turns any website into an interactive, source-cited AI layer — real-time indexed, with no manual dataset prep and no hallucinated answers.
Challenge
Teams sitting on large websites — documentation, blogs, SaaS platforms — have no fast way to get a straight answer out of them. Nobody wants to read fifty pages to find one fact, and generic chatbots either need a manual data pipeline or invent answers with no way to check them.
Approach
Chatbot on Demand indexes a target site in real time, with no manual dataset preparation, and answers questions through LangChain-orchestrated retrieval over that live index, running on Ollama for the LLM layer. FastAPI and MongoDB handle the retrieval and storage layer, Next.js serves the assistant UI, and the whole thing deploys on Vercel so it can be stood up for a new site in minutes. Every answer returns with the source URL it came from — retrieval stays grounded, not generative guesswork.
Outcome
Any website — docs, blog, SaaS product, competitor site — gets a context-aware assistant without a data-prep project first. Answers are cited by design, which removes the open question of whether the bot is making things up, and the scalable, production-grade architecture means a new deployment is a configuration step, not a rebuild.