Conversational assistants that answer customers instantly, trained on your own knowledge base — on your website, app, and WhatsApp. Built to escalate to a human the moment a conversation needs one.
Assistants that answer common questions instantly and qualify leads before a human ever joins the conversation.
One knowledge base, deployed everywhere your customers already are — website widget, WhatsApp, or inside your own app.
Grounded in your docs, FAQs, and policies via RAG, so answers reflect your actual business — not a generic script.
Clean escalation to a human agent the moment a conversation needs judgment, empathy, or an exception to policy.
Seven steps, one continuous conversation — from your first brief to a chatbot live on your channels.
We listen first. Your support volume, tone, and edge cases become a shared definition of what the bot should handle.
Scope, channels, and escalation rules — a roadmap for what the bot answers and when it hands off.
Conversation flows and knowledge base prototyped and tested against real customer questions.
Sprint-based builds with working demos every two weeks, tested on real conversations, not scripts.
Accuracy and tone testing across real questions — before customers ever see it.
Staged rollout across channels with monitoring, so the bot earns trust before full traffic.
Monitoring, retraining, and improvements — we stay on after launch day.
LLM Agents, RAG, LangChain, Vector DBs, Node.js — the technologies we use to build and ship.
Technical explainers and a real engagement — the kind of detail we'd want before making the same call ourselves.
A practical comparison of rule-based and LLM-powered chatbots — cost, predictability, and how to decide which one your use case actually needs.
Read the guideA practical checklist for taking a chatbot from a working demo to a production deployment that holds up against real customers.
Read the guideChatbots answer; agents act. What actually separates the two, and how to pick the right one for the job.
Read the guideMost booking requests came in after hours, when no one was there to answer. A chatbot picked up the slack and started closing bookings.
Read the case studyIt's grounded in your knowledge base via retrieval (RAG), so it answers from your actual docs and policies — and we configure it to say "I don't know, let me connect you with someone" rather than guess.
Yes — we build for web widgets, WhatsApp Business API, and in-app channels, and integrate with helpdesk tools like Zendesk or Intercom so handoffs and ticket history stay in one place.
Depends on your ticket mix, but for FAQ-heavy support queues, clients typically see 40-60% of tier-1 volume handled without a human, with clean escalation for anything more complex.
Yes — multilingual conversation is standard, and the bot detects and responds in the customer's language automatically rather than defaulting to English.
No. It's configured to recognize the limits of its knowledge and hand off to a human with full conversation context, so the customer never has to repeat themselves.
A focused chatbot on one or two channels typically launches in 3-6 weeks, from knowledge base setup through testing to production deployment.