Chatbots that don't just answer - they do the work.
The chatbot stuck to the bottom of this page is the same kind of system we'd deploy for you. It books calls, recalls case studies, escalates to a human when it should, and never makes up a price. The most common shape is a web bot that lives inside your site, navigates customers around it, and answers questions from your knowledge base - but the same engine runs as a sticky bottom bar, an expanded right-hand panel, an embedded section in a page, or as a Telegram / WhatsApp / Slack / Teams bot. The form follows the use case.
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Most "AI chatbots" are clever paragraph generators with a chat skin.
They don't connect to your systems. They hallucinate prices. They can't actually book the meeting they're offering to book. They send every customer the same generic answer regardless of what page they're on. The reason teams reach out to us is rarely 'we want a chatbot' - it's 'we tried a chatbot and got burned, and now we need one that works.'
Seven things every chatbot engagement gets.
Discovery
What the bot needs to know, who it's for, what it's allowed to do, what it must escalate.
Knowledge base sync
Pulled from your existing docs / website / KB / Notion / Confluence, kept in sync as content updates.
Tool layer
Typed wrappers around your CRM, ticketing, calendar, email - so the bot can act, not just answer.
Web placement options
Sticky bottom bar, expanded right-hand panel, floating bubble in the corner, or embedded as a section inside a page. Same engine; different surface for different sites.
Multi-channel
Web (the main one), plus Telegram, WhatsApp, Discord, Slack, Teams, Signal, Mattermost. Pick the ones that fit your customers.
Escalation
Slack / Teams handoff with full conversation context, plus email fallback when the team is offline.
Admin dashboard
Conversations list, lead pipeline, metrics, content management. For non-engineers.
Security pack
Prompt-injection defence, output filtering, rate limiting, role-based access on tools.
Why these chatbots usually fail - and how we build them so they don't.
Two patterns dominate the chatbot market and both fail, in different ways. The third - the one we build - is what works.
- Predictable but dumb - rigid decision-trees that cannot adapt
- Hallucinates prices, policies, and product details with confidence
- Cannot reach your systems - answers questions but cannot act on them
- Cannot book the meeting it is offering to book
- Customers learn to route around it within a week
- Connected to your CRM, ticketing, calendar - typed tool layer underneath
- Cites sources from your knowledge base; says when it does not know
- Books real calls and creates real tickets inside the chat
- Escalates with full conversation context to a human in Slack or Teams
- Same architecture as the chatbot stuck to the bottom of this page
Real chatbots running in production.
Web bot inside your site
The most common shape. Lives on every page, navigates customers around the site ('the pricing page is here'), answers product questions from your knowledge base, captures a lead when it makes sense, and books a call without leaving the chat.
Customer support, tier-1
Triage incoming questions, fetch context from your KB, draft a response, send if confidence is high, otherwise escalate to a human with the conversation handed over cleanly.
Internal copilot in Slack / Teams
Answers "what is our policy on X?" or "show me last quarter’s pipeline by rep." Gated by role, audit-logged per query.
B2C support on WhatsApp / Telegram
For consumer-facing operations where chat is the primary channel - works in any market where customers prefer messaging over web forms.
Booking + scheduling
Calendar inside the chat - availability across your team, smart timezone handling, confirmation email automatic.
Knowledge-base concierge
Internal chatbot fronting your docs / wiki / Confluence. Cites sources, says when it does not know.
A tutor that guides students towards the answer - never hands it out.
An AI tutor for grades 4 to 7 at a US online school. The instruction layer is strict: when a student asks a question, the bot points them to where the answer lives in the curriculum, asks them to try a step, and rephrases the question - but never gives the worked solution outright. The goal is for the student to learn, not to copy. Quiz scores lifted 27% against baseline; teachers reclaimed 10-15 hours per week each. Across 4 grades, with 4 years of carry-forward memory as the student moves from 4th to 7th.
Three things people always ask.
Can it use our existing knowledge base?
What about hallucinations?
Can it run on our hardware?
Bring us the questions your team answers a hundred times a week.
30-min diagnostic call walks through which conversations are worth automating and which should stay human. Free; written summary either way.