Chatbot development, built on real language models.
The old "chatbot" — a rigid decision tree that breaks the moment someone phrases a question differently — isn't what we build. Modern LLM-powered chat is genuinely useful for support, lead qualification, and internal knowledge lookup, when it's scoped to what it can reliably do.
Chatbots, applied.
Customer support chat
Answering common questions accurately, and knowing when to hand off to a human.
Lead qualification chat
Gathering the right information from a website visitor before a sales conversation.
Internal knowledge chat
Letting your team ask questions against your own docs instead of searching manually.
Guardrails against bad answers
Scoped to what it actually knows, with fallbacks so it doesn't confidently make things up.
Tools we pair it with
When a chatbot helps — and when it annoys.
A chatbot earns its place when it answers the same handful of questions your team fields every day — opening hours, service areas, availability, order status, booking a call — and when it can hand over to a person the moment it is out of its depth. Done that way it captures enquiries outside office hours and takes repetitive work off your staff. It becomes a liability when it is placed between a customer and a human being they actually need, when it guesses at answers it does not have, or when it opens unprompted and covers the page on a phone. The deciding factor is honesty: a bot that says it does not know and fetches someone builds trust, while one that improvises loses it, and recovering a frustrated customer costs more than the bot saved.